Abstract
Background
Urinary incontinence (UI) is a frequent yet often neglected issue in patients with chronic heart failure (HF), significantly impacting their quality of life (QoL) and possibly hindering adherence to treatment. However, there is limited research on its prevalence, risk factors, and effects in low- and middle-income countries. This study seeks to assess the prevalence of UI among individuals with HF, identify related demographic, clinical, and treatment factors, and evaluate its influence on the patients’ QoL.
Methods
This cross-sectional study included 148 HF patients from two major hospitals and used convenience sampling. Data on demographics, medical characteristics, and UI were obtained via the Urogenital Distress Inventory-6 (UDI-6) and the Incontinence Impact Questionnaire-7 (IIQ-7). Statistical methods were applied to determine associations between patient factors and UI severity.
Results
The prevalence of UI among HF patients was 46.6% (69 out of 148 participants). Compared with male participants, female participants had significantly higher median UDI-6 scores (27.7 [16.6–38.8] vs. males, p = 0.007) and higher IIQ-7 scores (mean rank 84.36, p = 0.002). Diuretic use was significantly associated with greater UI severity, reflected by higher median UDI-6 scores (27.7 [11.1–33.3], p = 0.025) and higher IIQ-7 scores (p = 0.04). Nonsmoking status was significantly associated with higher UI burden, with a median UDI-6 score of 27.7 (16.6–38.8) and a higher IIQ-7 mean rank (83.77; both p < 0.05). Similarly, participants who did not consume caffeine demonstrated significantly higher UI scores, with a median UDI-6 score of 33.3 (19.4–54.1) and a higher IIQ-7 mean rank (98.53; both p < 0.05). In contrast, age, body mass index, duration of heart failure, hypertension, and diabetes mellitus were not significantly associated with UI severity.
Conclusions
UI is prevalent among HF patients and adversely affects their QoL. Recognizing associated factors such as sex and diuretic use can help clinicians design targeted management strategies.
Keywords: urinary incontinence, heart failure, prevalence, risk factors, quality of life
Introduction
Urinary incontinence (UI), defined as involuntary urine leakage, 1 is widespread among people with chronic heart failure (HF).2–5 Estimates indicate that 35–50% of HF patients develop UI, with higher rates seen in advanced disease stages. 6
Several mechanisms may contribute, including frequent diuretic use, increased intra-abdominal pressure from fluid retention, and autonomic disturbances impairing bladder control. 4 Despite its frequency, UI often remains underreported, significantly worsening quality of life (QoL) through physical discomfort, emotional distress, and social withdrawal.3,4,6 Moreover, UI may disrupt HF management if patients adjust or skip diuretic therapy to minimize leakage, risking deterioration of cardiac symptoms. 3
Identifying UI incidence and associated factors in HF is essential for developing preventive and therapeutic approaches. Advanced age, female sex, obesity, and comorbidities such as diabetes and hypertension are recognized risk factors for UI in the general population.7–14 However, the precise relationships between these elements and HF-related factors, including disease duration, severity, and treatment protocols, have still not been fully explored. 4 This knowledge gap is particularly evident in low- and middle-income regions like Palestine, where cultural considerations and resource availability may influence the burden. Due to this lack of data, implementing holistic care plans for HF patients remains challenging.
The present study aims to determine the prevalence of UI among HF patients in Palestine, identify demographic and clinical associated factors, and assess the impact of UI on QoL. As the first study of its kind in this context, these findings provide vital evidence to inform clinical decision-making and emphasize the importance of routine UI screening to enhance patient-centered cardiovascular care.
Methods
Study design and setting
A cross-sectional design was used, and HF patients were recruited from two major hospitals in Nablus, Palestine. Data were collected between December 2023 and December 2024.
Study population, sampling procedure, and sample size calculation
The study employed a convenient sampling method, inviting all HF patients from the two hospitals who met the inclusion criteria to voluntarily participate. The sample size was calculated via an online Raosoft sample size calculator, which yielded a convenient sample size of 140. A 95% confidence level and a 5% margin of error were applied in the calculation.
Inclusion and exclusion criteria
Inclusion criteria
We enrolled patients aged 18 years or older with HF lasting more than three months. Eligible participants were stable on their treatment regimen, had a left ventricular ejection fraction (LVEF) of less than 40%, as determined by echocardiography or ventriculography, and possessed the mental and physical ability to communicate with the interviewer and provide complete clinical and demographic data. 15 Chronic heart failure in this cohort was defined as heart failure with reduced ejection fraction (HFrEF), corresponding to an LVEF <40%, of either ischemic or non-ischemic etiology. The specific etiological subtype (for example, ischemic heart disease, hypertensive heart disease, valvular disease, or non-ischemic cardiomyopathy) was not systematically recorded as a discrete study variable and was therefore unavailable for subgroup analysis.
Exclusion criteria
Participants were excluded from the study if they had a history of previous urological disease, recent documented urinary tract infections (UTIs) or psychiatric disease.
Data collection instruments
Participants demographics and characteristics
Age, sex, body mass index (BMI), smoking status, and employment status were included. The duration of HF, diuretic usage, presence of HTN and DM, and BMI were classified as underweight, healthy weight, overweight and obese (<18.5; 18.5–24.9; 25–29.9; >30, respectively).
The Urogenital Distress Inventory-6 (UDI-6) short form 16
Six questions covering irritative, stress, and obstructive symptoms were scored 0–3 per item, for a total of 0–18. Scores were converted to a 0–100 scale for better comparability. Reliability (Cronbach α = 0.71). The internal consistency of the short form of the UDI-6 was 0.71, as tested by the Cronbach’s alpha coefficient. 17
Incontinence Impact Questionnaire-7 (IIQ-7) short form 18
A tool designed to assess the impact of urinary incontinence on QoL. It consists of 7 items: household chores, physical recreation, entertainment activities, travel more than 30 minutes from home, social activities, emotional health (e.g., nervousness, depression), and feelings of frustration. Symptom severity is rated on a scale from 0 to 3, with 0 representing the least severe and 3 representing the most severe. The maximum possible IIQ-7 score is 21. To facilitate comparisons with other measures, the IIQ-7 scores were standardized to a 0–100 scale.
Statistical analysis
Social Sciences Statistical Package (SPSS) software (version 21) was used for statistical analysis. Continuous variables are summarized as the means ± standard deviations, whereas categorical data are presented as frequencies and percentages. The Kruskal‒Wallis and Mann‒Whitney U tests were used to examine associations. Generalized linear models (GLM) were used for multivariable regression analysis. The adjusted models including age, gender, BMI, employment status, diuretic use, diabetes mellitus, smoking, and caffeine intake. No collinearity was present between the independent variables (variance inflation factor <2). Effect estimates are presented as exponentiated coefficients with 95% confidence intervals. The significance threshold was p < 0.05.
Results
Participants demographics and characteristics
One hundred forty-eight participants met our inclusion criteria. There were 88 (59.5%) males. A total of 131 (88.5%) participants were 50 years or older, whereas only 17 (11.5%) were younger than 50 years. Most of the participants had a BMI of 25--29.9 kg/m2, with 51 (34.5%) participants. A total of 110 (74.3%) were not employed, and 44 (29.7%) were smokers. Regarding caffeine intake, 132 (89.2%) participants drank caffeine, and the majority of participants had a history of diuretic usage, 124 (83.8%). Seventy-two (48.6%) patients had 3 or more years of HF. A total of 104 (70.3) patients had a history of HTN, and 94 (63.5) had diabetes (Table 1).
Table 1.
Demographics and clinical data of the study participants.
| Demographics and clinical data | N = 148 |
|---|---|
| Age | 67 [61 – 75] |
| Age | 17 (11.5) |
| <50 | |
| ≥50 | 131 (88.5) |
| Gender | |
| Male | 88 (59.5) |
| Female | 60 (40.5) |
| BMI | |
| BMI | |
| <18.5 | 2 (1.4) |
| 18.5-24.9 | 45 (30.4) |
| 25-29.9 | 51 (34.5) |
| >30 | 50 (33.8) |
| Occupational Status | |
| Unemployed | 110 (74.3) |
| Employed | 38 (25.7) |
| Smoker | |
| Yes | 44 (29.7) |
| No | 104 (70.3) |
| Caffeine intake | |
| Yes | 132 (89.2) |
| No | 16 (10.8) |
| Duration of heart failure | |
| </= 1 | 47 (31.8) |
| 2 | 29 (19.6) |
| ≥3 | 72 (48.6) |
| Chronic Medical disease | |
| Hypertension | 104 (70.3) |
| Diabetes | 94 (63.5) |
| Diuretics use | |
| Yes | 124 (83.8) |
| No | 24 (16.2) |
| IIQ-7 Score | 199.8 [41.6-357.9] |
| UDI-6 Score | 166.5 [66.6-199.8] |
BMI: Body mass index, IIQ-7: Incontinence Impact Questionnaire-7, UDI-6: Urogenital Distress Inventory-6.Data are presented as the number of patients (out of the total number of patients in that group) followed by the percentage in parentheses unless otherwise indicated.
Relationships between the participants’ characteristics and their UDI-6 scores
In univariate analysis, Gender was significantly correlated with the UDI-6 score, with a higher median score in females 27.7 (16.6-38.8) (p =0.007). A significant correlation was found between diuretic usage and the UDI-6 score, with a median of 27.7 (11.1-33.3) (p=0.025). Histories of no caffeine intake and nonsmoking were significantly correlated, with medians of 33.3 (19.4-54.1) and 27.7 (16.6-38.8), respectively (p <0.05). The duration of HF, age, occupational status, presence of HTN or DM and BMI did not reach any significant level (Table 2).
Table 2.
Associations between UDI-6 scores and demographic and clinical data.
| Variables | Mean rank | Median (Q1-Q3) | P Value |
|---|---|---|---|
| Age | |||
| <50 | 69.54 | 24.9 (9.7-33.3) | 0.647 a |
| ≥50 | 75.02 | 27.7 (11.1-33.3) | |
| Gender | |||
| Male | 66.71 | 22.2 (11.1-33.3) | 0.007 a |
| Female | 85.93 | 27.7 (16.6-38.8) | |
| BMI | |||
| <18.5 | 58.00 | 19.4 (-) | 0.355 b |
| 18.5-24.9 | 66.36 | 16.6 (5.5-38.8) | |
| 25-29.9 | 72.86 | 22.2 (11.1-33.3) | |
| >30 | 81.18 | 27.7 (16.6-33.3) | |
| Occupational Status | |||
| Unemployed | 78.06 | 27.7 (11.1-38.8) | 0.084 a |
| Employed | 64.18 | 22.2 (11.1-33.3) | |
| Smoker | |||
| Yes | 52.58 | 11.1 (5.5-27.7) | < 0.001 a |
| No | 83.77 | 27.7 (16.6-38.8) | |
| Caffeine intake | |||
| Yes | 71.9 | 22.2 (11.1-33.3) | 0.037 a |
| No | 95.53 | 33.3 (19.4-54.1) | |
| Duration of heart failure | |||
| </= 1 | 80.73 | 27.7 (12.4-38.8) | 0.070 b |
| 2 | 83.59 | 33.3 (11.1-41.6) | |
| ≥3 | 65.84 | 22/2 (11.1-33.3) | |
| Hypertension | |||
| Yes | 74.56 | 27.7 (11.1-38.85) | 0.978 |
| No | 74.36 | 27.7 (11.1-38.85) | |
| Diabetes Milletus | |||
| Yes | 75.69 | 27.7 (11.1-33.3) | 0.543 a |
| No | 71.33 | 22.2 (11.1-33.3) | |
| Diuretics use | |||
| Yes | 77.96 | 27.7 (11.1-33.3) | 0.025 a |
| No | 56.6 | 19.4 (0-27.7) | |
BMI: Body mass index.
The bold values indicate p<0.05.
aStatistically significant values were calculated via the Mann–Whitney U test.
bStatistically significant values were calculated via the Kruskal‒Wallis test.
In the adjusted model, diuretic use remained independently associated with higher UDI-6 scores (exp(b) 1.38, 95% CI 1.00 to 1.90, p = .049). Smoking was independently associated with lower UDI-6 scores (exp(b) 0.64, 95% CI 0.47 to 0.87, p = .004). Age, gender, BMI, employment status, diabetes mellitus, and caffeine intake were not independently associated with UDI-6 scores in this multivariable analysis (Table 3).
Table 3.
Multivariable regression of factor associated with UDI-6 scores.
| Variables | exp(b) (95%CI) | P-value |
|---|---|---|
| Gender | 1.06 (0.79–1.43) | 0.70 |
| Age | 1.00 (0.99–1.01) | 0.59 |
| BMI | 1.00 (0.98–1.02) | 0.77 |
| Employed | 0.99 (0.73–1.35) | 0.97 |
| Diuretics use | 1.38 (1.00–1.90) | 0.049 |
| Diabetes Milletus | 1.04 (0.80–1.34) | 0.77 |
| Smoker | 0.64 (0.47–0.87) | 0.004 |
| Caffeine intake | 0.81 (0.55–1.19) | 0.28 |
BMI: Body mass index.
Relationships between the participants’ characteristics and their IIQ-7 scores
In univariate analysis, Female sex, with a mean rank of 84.36, was significantly correlated with the IIQ-7 score (p =0.002). Unemployment was significantly correlated with IIQ 7, with a median of 33.3 (9.5-57.08) (p =0.03). The use of diuretics was significantly correlated with the IIQ-7 score (p =0.04). Both nonsmoking and no history of caffeine intake were significantly correlated, with mean ranks of 83.77 and 98.53, respectively. The presence of HTN or DM, BMI, age and duration of HF were not significantly correlated (Table 4).
Table 4.
Associations between IIQ-7 scores and demographic and clinical data.
| Variables | Mean rank | Median (Q1-Q3) | P Value |
|---|---|---|---|
| Age | |||
| <50 | 77.96 | 47.5 (3.5-53.5) | 0.750 a |
| ≥50 | 74.14 | 28.5 (9.5-47.5) | |
| Gender | |||
| Male | 67.78 | 19.02 (4.7-47.5) | 0.020 a |
| Female | 84.36 | 33.3 (14.2-67.08) | |
| BMI | |||
| <18.5 | 109.00 | 40.4 (19.0-65.4) | 0.305 b |
| 18.5-24.9 | 70.58 | 28.5 (4.7-52.4) | |
| 25-29.9 | 68.10 | 19.0 (4.7-47.5) | |
| >30 | 80.00 | 33.3 (13.0-53.5) | |
| Occupational Status | |||
| Unemployed | 78.95 | 33.3 (9.5-57.08) | 0.031 a |
| Employed | 61.61 | 14.2 (4.7-39.2) | |
| Smoker | |||
| Yes | 55.08 | 9.5 (1.1-38.0) | < 0.001 a |
| No | 82.72 | 33.3 (14.2-57.0) | |
| Caffeine intake | |||
| Yes | 71.59 | 23.7 (4.7-47.5) | 0.017 a |
| No | 98.53 | 47.5 (28.5-61.8) | |
| Duration of heart failure | |||
| </= 1 | 75.53 | 28.5 (4.7-48.7) | 0.623 b |
| 2 | 79.47 | 38.0 (7.1-57.0) | |
| ≥3 | 70.82 | 21.4 (5.9-47.5) | |
| Hypertension | |||
| Yes | 77.62 | 28.5 (9.5-52.3) | 0.179 a |
| No | 67.36 | 14.2 (2.3-47.5) | |
| Diabetes Milletus | |||
| Yes | 78.08 | 23.7 (7.1-47.5) | 0.354 a |
| No | 71.42 | 33.3 (7.1-52.3) | |
| Diuretics use | |||
| Yes | 77.64 | 28.5 (9.5-47.5) | 0.042 a |
| No | 58.37 | 4.7 (0-52.3) | |
BMI: Body mass index.
The bold values indicate p<0.05.
aStatistically significant values were calculated via the Mann–Whitney U test.
bStatistically significant values were calculated via the Kruskal‒Wallis test.
In the adjusted model, smoking remained independently associated with lower IIQ-7 scores (exp(b) 0.58, 95% CI 0.40 to 0.83, p = .003). Age, employment, gender, BMI, diuretic use, diabetes mellitus, and caffeine intake were not independently associated with IIQ-7 scores in this multivariable analysis (Table 5).
Table 5.
Multivariable regression of factor associated with IIQ-7 scores.
| Variables | exp(b) (95%CI) | P-value |
|---|---|---|
| Gender | 0.97 (0.67–1.38) | 0.85 |
| Age | 0.99 (0.97–1.00) | 0.07 |
| BMI | 1.01 (0.98–1.03) | 0.51 |
| Employed | 0.71 (0.48–1.04) | 0.07 |
| Diuretics use | 1.37 (0.89–2.12) | 0.15 |
| Diabetes Milletus | 0.79 (0.57–1.09) | 0.15 |
| Smoker | 0.58 (0.40–0.83) | 0.003 |
| Caffeine intake | 0.77 (0.48–1.25) | 0.29 |
BMI: Body mass index.
Discussion
The results of this cross-sectional study demonstrate a significant prevalence of UI in patients with HF, which is consistent with global reports suggesting that UI affects approximately 35%–50% of HF patients. 6
The significant association between female sex and higher UI scores reinforces the findings of previous studies, which have consistently identified women as being at greater risk of UI both in the general population and specifically within HF cohorts. 12
Several mechanisms may account for this sex disparity, including anatomical differences such as shorter urethral length, hormonal changes associated with menopause leading to pelvic floor weakness, and the cumulative effects of childbirth on bladder support structures.19–21 These factors may act synergistically with HF-related contributors, such as fluid retention and the use of diuretics, to increase vulnerability to UI in women. 4 The higher UDI-6 and IIQ-7 scores among the female participants in this study further highlight the disproportionate impact of UI on their functional status and psychosocial well-being.
An additional important observation from this study is the influence of diuretic therapy on the occurrence and severity of UI. Participants receiving diuretics demonstrated higher median UI scores, indicating that while diuretics remain a cornerstone in controlling fluid retention in HF, they may simultaneously aggravate or trigger urinary symptoms. 3 This finding emphasizes the importance of balancing HF management with the possible side effects of treatment, necessitating a personalized approach to diuretic therapy.
In contrast to expectations and findings from broader epidemiological studies, variables such as age, BMI, duration of HF, and the presence of HTN or DM did not significantly correlate with UI scores in our study cohort. This deviation from broader epidemiological trends7,13,22,23 may be attributed to specific characteristics of the study population, regional factors, or the relatively limited sample size. Larger-scale investigations across more diverse populations are necessary to clarify these relationships and determine their clinical significance.
The link between UI and QoL observed in this study is of particular concern. Patients with higher UI scores reported a greater degree of QoL impairment, reflecting the combined physical discomfort, psychological strain, and social limitations imposed by incontinence. This finding mirrors prior studies documenting how UI can negatively affect daily functioning, emotional health, and interpersonal relationships among HF patients.3,4,6 Depression and anxiety, which are common in HF patients, may be exacerbated by UI, creating a bidirectional cycle of worsening mental health and poor adherence to treatment. 24 Moreover, UI may negatively affect sleep quality due to nocturia, further compounding fatigue and functional decline. 25 These findings highlight the urgent need to integrate QoL assessment into HF management, with UI as a key determinant.
An interesting finding of this study was that nonsmokers and patients without caffeine intake presented higher UI severity scores. This contradicts much of the literature, which typically identifies smoking and caffeine consumption as modifiable risk factors for UI.26–29 Both active cigarette smoking and waterpipe smoking have been associated with detrusor overactivity and a higher prevalence of urgency urinary incontinence, particularly among younger women,30,31 and several large population-based surveys have linked higher caffeine intake to increased UI prevalence and severity. 32 The evidence is nonetheless inconsistent: a meta-analysis of observational studies found no significant overall association between coffee or caffeine consumption and UI risk, 33 and this heterogeneity across populations is relevant when interpreting our counterintuitive findings. Several explanations could be considered. One possibility is that patients with severe UI may have already adopted lifestyle changes—such as quitting smoking or reducing caffeine intake—in response to their symptoms, leading to reverse causality. Another explanation could be cultural or behavioral differences in this population that modify the relationship between these exposures and urinary symptoms. However, further longitudinal studies are needed to clarify these associations.
In light of these outcomes, it is imperative that healthcare providers incorporate routine UI screening into the standard management of HF patients. Early identification of UI can facilitate timely interventions, such as pelvic floor muscle exercises, lifestyle modifications, and adjustments to diuretic regimens, which may alleviate symptoms and improve QoL. 34 Additionally, patient education should emphasize the importance of reporting UI symptoms and adhering to prescribed HF treatments, addressing potential concerns that may lead to noncompliance.
Implications for clinical practice and future research
The current study emphasizes the importance of the identification of UI as a common and troublesome comorbidity of chronic HF patients. Clinically, the study supports the inclusion of routine UI screening and patient counselling as a regular aspect of the care of HF. Early recognition of high-risk patients—namely women and diuretic users—can enable timely lifestyle modifications, pelvic floor exercises, timed voiding, or optimizing the timing of diuretic administration—ideally administering loop diuretics in the morning and, when a second daily dose is required, no later than the early afternoon (approximately six hours before the patient’s usual bedtime), 35 thereby preventing urinary symptoms with no adverse effects on cardiac outcomes. Proper counselling and patient education also remain central to enabling easy UI discussions free of stigma and improving adherence to the HF treatment plan.
Future research should utilize larger, multicenter longitudinal designs to further clarify the associations between HF-related factors and UI. Further investigation is warranted to explore the biological and behavioral mechanisms underlying the unexpected findings regarding smoking and caffeine consumption, specifically investigating the possibility of reverse causality. Additionally, research should evaluate cost-effective, culturally appropriate non-pharmacological interventions tailored to various socioeconomic settings. Ultimately, integrating UI-focused assessments into comprehensive HF care has the potential to enhance patients’ QoL and support better overall clinical management.
Strengths and limitations
Strengths include being the first study in this setting to examine UI incidence in HF patients and the use of validated questionnaires (UDI-6 and IIQ-7). Clinical implications are clear for guiding practice. Limitations include cross-sectional design (limiting causality), convenience sampling (risking selection bias), and single-region data (reducing generalizability). Unmeasured factors such as activity level, diet, and adherence may also have influenced the results. Furthermore, our characterization of heart failure was primarily based on LVEF (<40%). While all patients were clinically stable, we did not categorize participants by The New York Heart Association (NYHA) functional class or quantify congestion status and diuretic dosages. The use of a binary variable for diuretic therapy (Yes/No) may oversimplify the relationship between medication intensity and urinary symptoms. Future studies should incorporate these clinical parameters to better delineate the impact of HF severity on urogenital distress. In addition, the underlying etiology of heart failure (ischemic versus non-ischemic) was not captured as a study variable, precluding etiology-stratified analysis; future work should record heart-failure etiology to determine whether it modifies the risk and severity of urinary incontinence.
Conclusions
UI is highly prevalent among HF patients and associated with lower reported QoL. Female sex, diuretic use, nonsmoking, and the absence of caffeine consumption were associated with UI, whereas age, BMI, comorbidities, and HF duration were not. Integrating UI assessment into HF care can enhance patient management and well-being. Future large-scale, multicenter studies are needed to confirm these findings and to evaluate targeted interventions for managing UI in HF patients.
Supplemental material
Supplemental Material for Prevalence, associated factors, and quality of life impact of urinary incontinence in heart failure patients: A multicenter cross-sectional study from a low- and middle-income country by Faris Abushamma, Abdallah Abdallah, Thabit Sweileh, Osama Faqih, Yunis Daralammouri, Rola Abu Alwafa, Amir Aghbar in Sage Open Medicine
Acknowledgement
We thank Prof. Sa'ed Zyoud, Clinical Research Center of An-Najah National University Hospital, for his wise advice.
Author contributions: AA, TS and OF contributed to data collection and curation and drafted the initial manuscript. AAG contributed to the clinical interpretation of the findings and drafted the initial manuscript, YD contributed to the clinical interpretation of the findings and critically revised the manuscript. FA and RA conceived the study question, refined the overall study design, provided senior scientific supervision and mentorship, performed the statistical analysis and write the finical version of manuscript. All the authors contributed to the interpretation of the findings, revised the manuscript for important intellectual content, approved the final version, and agreed to be accountable for all the aspects of the work.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
All authors declare that they have no competing interests.
Supplemental material: Supplemental material for this article is available online
ORCID iDs
Faris Abushamma https://orcid.org/0000-0002-0530-5466
Thabit Sweileh https://orcid.org/0009-0003-6847-3728
Amir Aghbar https://orcid.org/0000-0002-4402-7278
Ethical considerations
All aspects of the study protocol, including the procedure for obtaining verbal informed consent, were reviewed and approved by the Institutional Review Board (IRB) of An-Najah National University (Ref: Med. Dec. 2023/93). The IRB specifically approved the use of verbal (rather than written) informed consent, which was deemed appropriate given the non-interventional, questionnaire-based design of the study and the need to preserve participant anonymity. Verbal informed consent was accordingly obtained from all participants prior to enrollment and was documented by the interviewer. All data used in this research have been anonymized to ensure the privacy and confidentiality of our participants. The study was conducted in accordance with the Declaration of Helsinki.
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Supplementary Materials
Supplemental Material for Prevalence, associated factors, and quality of life impact of urinary incontinence in heart failure patients: A multicenter cross-sectional study from a low- and middle-income country by Faris Abushamma, Abdallah Abdallah, Thabit Sweileh, Osama Faqih, Yunis Daralammouri, Rola Abu Alwafa, Amir Aghbar in Sage Open Medicine