Original Article
Frequency, Associated Factors, and Quality of Life in Men with Lower Urinary Tract Symptoms (LUTS) in Lahore, Pakistan
Authors: Barak Waris , Nauman Ismat Butt , Usama Javed , Asyhveen Baber
DOI: https://doi.org/10.37184/lnjpc.2707-3521.8.33
Year: 2026
Volume: 8
Received: Sep 17, 2025
Revised: Nov 08, 2025
Accepted: Jan 30, 2026
Corresponding Auhtor: Nauman Ismat Butt (nauman_ib@yahoo.com)
All articles are published under the Creative Commons Attribution License
ABSTRACT
Background: Lower urinary system symptoms (LUTS) are a group of clinical complaints characterized by irregular urinary patterns. LUTS tremendously affect patient functioning and quality of life (QOL). Despite its impact, many men do not seek medical attention, which can be attributed to the low level of awareness and costs associated with healthcare resources and the stigmatization of urinary symptoms.
Objective: To assess the frequency of LUTS, its associated factors, and QOL among men at a urology clinic in Lahore, Pakistan.
Methods: This cross-sectional clinic-based study was conducted from May 2025 to July 2025 at the Urology Outpatient Department of Chaudhary Muhammad Akram Teaching and Research Hospital, Lahore, Pakistan, on 165 male participants. To evaluate LUTS and QOL, the International Prostate Symptom Score (IPSS) was used. The QOL item is scored from 0 ("delighted") to 6 ("terrible"), with scores of 0-2 representing good QOL and 3-6 indicating poor QOL. Data were analyzed using SPSS version 23.0.
Results: Mean age was 52.1 ± 14.7 years. Mean IPSS score was 13.6 ± 12.1, with 73.9% of participants reporting LUTS. In univariate analysis, LUTS were associated with age, lower education, lower income, diabetes, and hypertension; however, none of these remained significant in multivariable logistic regression. The mean QOL score was 3.1 ± 1.8, and 2/3 (66.7%) reported poor QOL. In univariate analysis, poor QOL was associated with age, diabetes mellitus, absence of alcohol use, tea intake, and LUTS; however, in multivariable logistic regression, poor QOL was associated with LUTS severity, while alcohol use was inversely associated with poor QOL.
Conclusion: LUTS were highly prevalent among adult males presenting to the urology clinic, significantly affecting QOL. Routine screening and early management are essential to reduce symptom burden and improve QOL.
Keywords: Lower urinary tract symptoms (LUTS), Quality of Life (QOL), males, incomplete emptying, urgency, weak urinary stream, nocturia, urology, Pakistan.
INTRODUCTION
Lower urinary tract symptoms (LUTS) comprise a range of clinical complaints related to abnormal urinary patterns arising from dysfunction of the lower urinary tract [1]. Broadly classified as obstructive (voiding) or irritative (storage), LUTS often occur in combination [1]. LUTS are commonly associated with underlying urological or neurological disorders such as benign prostatic hyperplasia (BPH), which is recognized as one of the most prevalent conditions among men over 50 years [1, 2]. Globally, the burden of LUTS increases with age. More than half of men aged 61-70 years report at least one LUTS, and the prevalence of moderate to severe symptoms rises from 13% in men aged 40-49 years to 28% in those over 70 years [3]. A recent meta-analysis estimated that 63.2% of adults worldwide experience LUTS, with 31.3% reporting moderate to severe symptoms [4]. Studies from South Asia show comparable or higher figures. In India, Kant et al. observed LUTS in 85% of men over 50 years, most frequently nocturia (85.4%) and a weak urinary stream (35%), with symptom severity strongly linked to poor quality of life (QOL; p<0.001) [5].
Within Pakistan, reported prevalence varies by region. Salman et al. reported a prevalence of LUTS of 33.7% among adult men in the Punjab Province [6]. This prevalence was found to be significantly associated with higher age, unemployment, diabetes, hypertension, and smoking history [6]. In contrast, Shahzad et al. reported that the prevalence of LUTS symptoms was 23.5% in the Hazara Division; there was substantial evidence of underutilization of treatment facilities for these symptoms [7]. Factors such as stigma, poor awareness, or financial constraints are some essential reasons for men's reluctance towards seeking health care [6, 8]. LUTS substantially impair QOL by disrupting sleep, daily activities, social interactions, and emotional well-being [1, 9]. Up to half of affected individuals modify their behavior, such as restricting fluid intake or travel, to manage symptoms [1]. Untreated LUTS can lead to complications, including sexual dysfunction, psychological distress, and increased risk of nocturnal falls [6, 10].
Although data exist from other Pakistani regions, there is limited published evidence from Lahore, one of the country's largest and most demographically diverse cities. Understanding the local prevalence, risk factors, and association with QOL is essential to guide early detection and intervention strategies in urban male populations. Therefore, this study aimed to assess the frequency of LUTS, its associated factors, and QOL among adult men attending a urology clinic in Lahore, Pakistan.
METHODOLOGY
This cross-sectional clinic-based study was conducted from May 2025 to July 2025 at the Urology Outpatient Department (OPD) of Chaudhary Muhammad Akram Teaching and Research Hospital, affiliated with Azra Naheed Medical College, Superior University, Lahore, Pakistan, following approval from the Institutional Ethical Review Committee (IRB#ANMC/IRB/2025/024) on April 30, 2025. The study followed the standards laid down in the 1964 Declaration of Helsinki, revised in 2000.
Written informed consent was obtained from each patient before inclusion in the study. Patient confidentiality and data privacy were strictly maintained throughout the research, and no patient-identifiable information was used in the analysis. All men aged 30 years and above who visited the urology OPD clinic during the study period were considered eligible. The patients with urinary tract infection, chronic kidney disease, renal stones, prostate or bladder malignancy, neurogenic bladder, or previous urological surgeries were excluded.
The sample size was calculated using a 89.8% prevalence rate of LUTS [11], with a 5% margin of error and a 95% confidence level; the required sample size was determined to be 141 using the Openepi online calculator. However, to improve the study's robustness, a total of 165 male participants were ultimately included. The participants were selected using a non-probability, consecutive sampling method. Data collection was conducted using a structured questionnaire, which collected information on respondents' personal characteristics, such as age, marital status, education level, employment status, and monthly family income. Medical history regarding conditions such as diabetes mellitus and hypertension was also recorded, along with lifestyle factors including smoking, alcohol use, and tea intake. The urinary symptoms, LUTS, and QOL were subsequently assessed using the International Prostate Symptom Score (IPSS) questionnaire [8, 12]. The questionnaires were administered as face-to-face interviews in the presence of a medical doctor to ensure the participants' understanding.
Assessments of urinary symptoms and their impact on QOL were made using the IPSS questionnaire. This is a standardized instrument comprising seven questions on urinary symptoms, including incomplete emptying, intermittency, frequency, weak stream, urgency, straining, and nocturia, with one additional question on QOL related to difficulties with urination [8, 12]. Symptoms are scored from 0 ("not at all") to 5 ("almost always"), yielding a total score of 0 to 35. Symptom severity was then categorized as: 0 = none, 1-7 = mild, 8-19 = moderate, and 20-35 = severe [8, 12]. The QOL item was scored from 0 ("delighted") to 6 ("terrible"), with scores of 0-2 representing good QOL and 3-6 indicating poor QOL.
Data entry and statistical analyses were performed using SPSS version 23.0. Descriptive statistics were used to summarize participant characteristics. Summary measures included frequencies and percentages for categorical data and mean ± standard deviation (SD) for continuous data. Associations between independent variables and LUTS or QOL were first examined using Pearson's Chi-square test or Fisher's exact test, as appropriate. Analyses were used to determine potential associations or to select variables for inclusion in a multivariable model. Binary logistic regression was performed to identify factors independently associated with LUTS and QOL.
For the LUTS model, the dependent variable was the presence of LUTS (IPSS ≥ 1, coded as 1) versus its absence (IPSS = 0, coded as 0). Variables entered into the multivariable LUTS model included age, marital status, education status, employment status, hypertension, smoking status, alcohol use, and tea intake. Although family income and diabetes mellitus showed statistically significant associations with LUTS in univariate analysis, they were not included in the multivariable LUTS model due to the complete separation of data. Specifically, all participants with diabetes mellitus and all participants with a monthly family income ≤50,000 PKR reported LUTS, resulting in zero observations in the LUTS-absent category for these variables. As standard logistic regression cannot provide valid estimates under conditions of complete separation, these variables were excluded from the multivariable analysis. Given the limited number of participants without LUTS (n=43) relative to those with LUTS (n=122), the multivariable model included only a limited number of predictors to reduce the risk of overfitting and unstable estimates.
For the QOL model, binary logistic regression was conducted with QOL as the dependent variable, coded as poor QOL (QOL score 3-6 = 1) versus good QOL (QOL score 0-2 = 0). Independent variables included age, marital status, educational status, employment status, family income, diabetes mellitus, hypertension, smoking status, alcohol use, tea intake, and presence of LUTS to assess the association between LUTS and QOL while adjusting for potential confounders. Poor QOL was coded as 1 and good QOL as 0. Age categorization (≤48 vs. ≥49 years) was based on the study sample distribution (median split). At the same time, family income (≤50,000 vs. >50,000 PKR/month) and tea intake (≤2 vs. >2 cups/day) were aligned with thresholds used in previous studies to maintain consistency. It is acknowledged that dichotomization may reduce statistical power and obscure potential dose-response relationships. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were reported. All statistical tests were two-tailed, and a p-value ≤0.05 was considered statistically significant.
RESULTS
The study included 165 men presenting to the urology clinic, with a mean age of 52.1 ± 14.7 years, of whom 92 (55.8%) were aged ≥49 years. Most participants were married (80.0%), had less than 10 years of education (83.6%), and reported a family income >50,000 PKR/month (153, 92.7%). Comorbidities included diabetes mellitus in 46 (27.9%) and hypertension in 52 (31.5%). Lifestyle factors showed 73 (44.2%) smokers, 14 (8.5%) alcohol users, and 127 (77.0%) consumed more than two cups of tea per day (Table 1).
The mean IPSS score was 13.6 ± 12.1, with 122 (73.9%) participants reporting LUTS. Symptom severity was categorized as mild (24, 14.5%), moderate (25.5%), and severe (33.9%) as presented in Fig. 1. The most frequently reported LUTS were frequency (67.8%) and urgency (63.0%) as depicted in Table 2.
Table 1: Demographic and clinical variables of the patients (N=165).
Characteristic | Value (N=165) |
|---|---|
Age (years), mean ± SD | 52.1 ± 14.7 |
Age ≥49 years, n(%) | 92 (55.8) |
Married, n(%) | 132 (80.0) |
Education <10 years, n(%) | 138 (83.6) |
Family income >50,000 PKR/month, n(%) | 153 (92.7) |
Diabetes mellitus, n(%) | 46 (27.9) |
Hypertension, n(%) | 52 (31.5) |
Smoking, n(%) | 73 (44.2) |
Alcohol use, n(%) | 14 (8.5) |
Tea intake >2 cups/day, n(%) | 127 (77.0) |
Table 2: Symptoms of LUTS in the patients (N=165).
Symptoms of LUTS | Mean IPSS Score | Range | Frequency | Percentage | |||
|---|---|---|---|---|---|---|---|
Incomplete Emptying | 1.8±1.8 | 0-5 | 92 | 55.7 | |||
Frequency | 2.4±1.9 | 0-5 | 112 | 67.8 | |||
Intermittency | 1.8±1.8 | 0-5 | 96 | 58.2 | |||
Urgency | 2.2±1.9 | 0-5 | 104 | 63.0 | |||
Weak Stream | 1.6±2.0 | 0-5 | 78 | 47.2 | |||
Straining | 1.7±2.0 | 0-5 | 84 | 50.9 | |||
Nocturia | 1.8±1.9 | 0-5 | 90 | 54.5 | |||
Patient Variables | Sub-Groups | LUTS Absent n(%) | LUTS Present n(%) | Pearson Chi-Square Value | p-value |
|---|---|---|---|---|---|
Age | ≤48 years | 35 (47.9) | 38 (52.1) | 32.541 | <0.001* |
>48 years | 08 (8.7) | 84 (91.3) | |||
Marital Status | Married | 30 (22.7) | 102 (77.3) | 3.806 | 0.051 |
Unmarried | 13 (39.4) | 20 (60.6) | |||
Education Status | ≤10 standards | 30 (21.7) | 108 (78.3) | 8.173 | 0.004* |
>10 standards | 13 (48.1) | 14 (51.9) | |||
Employment Status | Employed | 22 (29.7) | 52 (70.3) | 0.937 | 0.333 |
Unemployed | 21 (23.1) | 70 (76.9) | |||
Family income | ≤50,000 PKR/month | 0 (0.0) | 12 (100) | 4.561 | 0.037* |
>50,000 PKR/month | 43 (28.1) | 110 (71.9) | |||
Diabetes mellitus | Present | 0 (0.0) | 46 (100) | 22.480 | <0.001* |
Absent | 43 (36.1) | 76 (63.9) | |||
Hypertension | Present | 08 (15.4) | 44 (84.6) | 4.491 | 0.034* |
Absent | 35 (31.0) | 78 (69.0) | |||
Smoking | Present | 15 (20.5) | 58 (79.5) | 2.065 | 0.151 |
Absent | 28 (30.4) | 64 (69.6) | |||
Alcohol Use | Present | 02 (14.3) | 12 (85.7) | 1.101 | 0.294 |
Absent | 41 (27.2) | 110 (72.8) | |||
Tea Intake | ≤2 cups/day | 10 (26.3) | 28 (73.7) | 0.002 | 0.967 |
>2 cups/day | 33 (26.0) | 94 (74.0) |
LUTS: Lower Urinary Tract Symptoms; IPSS: International Prostate Symptom Score; *Significant at p<0.05
Table 4: Multivariable binary logistic regression analysis of data about LUTS.
Demographic and clinical variables | Beta Coefficient (B) | S.E. | Wald | p-value | Adjusted Odds Ratio (OR) | 95% CI for OR | |
|---|---|---|---|---|---|---|---|
Lower | Upper | ||||||
Age | 1.655 | 0.861 | 3.691 | 0.055 | 5.233 | 0.967 | 28.307 |
Marital Status | 0.837 | 0.779 | 1.154 | 0.283 | 2.308 | 0.502 | 10.622 |
Education Status | 0.167 | 0.395 | 0.178 | 0.673 | 1.181 | 0.545 | 2.560 |
Employment Status | 0.184 | 0.638 | 0.083 | 0.774 | 1.201 | 0.344 | 4.200 |
Hypertension | 0.473 | 0.858 | 0.304 | 0.581 | 1.604 | 0.299 | 8.615 |
Smoking | 0.745 | 0.651 | 1.310 | 0.252 | 2.107 | 0.588 | 7.553 |
Alcohol Use | -0.814 | 1.393 | 0.342 | 0.559 | 0.443 | 0.029 | 6.788 |
Tea Intake | 0.756 | 0.697 | 1.178 | 0.278 | 2.130 | 0.544 | 8.345 |
CI: Confidence Interval, LUTS: Lower Urinary Tract Symptoms; S.E.: Standard Error
Table 5: Stratification of data about Quality of Life (N=165).
Variables | Sub-Groups | Good QOL n(%) | Poor QOL n(%) | Pearson Chi-Square Value | p-value |
|---|---|---|---|---|---|
Age | ≤48 years | 37 (50.5) | 36 (49.3) | 17.738 | <0.001* |
>48 years | 18 (19.6) | 74 (80.4) | |||
Marital Status | Married | 40 (30.3) | 92 (69.7) | 2.727 | 0.099 |
Unmarried | 15 (45.5) | 18 (54.5) | |||
Education Status | ≤10 standards | 42 (30.4) | 96 (69.6) | 3.188 | 0.074 |
>10 standards | 13 (48.1) | 14 (51.4) | |||
Employment Status | Employed | 22 (29.7) | 52 (70.3) | 0.784 | 0.376 |
Unemployed | 33 (36.3) | 58 (63.7) | |||
Family income | ≤50,000 PKR/month | 02 (16.7) | 10 (83.3) | 1.618 | 0.203 |
>50,000 PKR/month | 53 (34.6) | 100 (65.4) | |||
Diabetes mellitus | Present | 06 (13.0) | 40 (87.0) | 11.816 | 0.001* |
Absent | 49 (41.2) | 70 (58.8) | |||
Hypertension | Present | 12 (23.1) | 40 (76.9) | 3.594 | 0.058 |
Absent | 43 (38.1) | 70 (61.9) | |||
Smoking | Present | 23 (31.5) | 50 (68.5) | 0.197 | 0.658 |
Absent | 32 (34.8) | 60 (65.2) | |||
Alcohol Use | Present | 08 (57.1) | 06 (42.9) | 3.903 | 0.048* |
Absent | 47 (31.1) | 104 (68.9) | |||
Tea Intake | ≤2 cups/day | 20 (52.6) | 18 (47.4) | 8.274 | 0.004* |
>2 cups/day | 35 (27.6) | 92 (72.4) | |||
Lower Urinary Tract Symptoms (LUTS) | Absent | 27 (62.8) | 16 (37.2) | 22.709 | <0.001* |
Present | 28 (23.0) | 94 (77.0) |
*Significant at p<0.05
Table 6: Multivariable binary logistic regression analysis of data about poor QOL.
Demographic and clinical variables | Beta Coefficient (B) | S.E. | Wald | p-value | Odds Ratio (OR) | 95% CI for OR | |
|---|---|---|---|---|---|---|---|
Lower | Upper | ||||||
Age | 0.899 | 0.756 | 1.413 | 0.235 | 2.457 | 0.558 | 10.815 |
Marital Status | 0.181 | 0.738 | 0.060 | 0.806 | 1.198 | 0.282 | 5.090 |
Education Status | -0.006 | 0.402 | 0.000 | 0.989 | 0.994 | 0.453 | 2.185 |
Employment Status | 0.817 | 0.632 | 1.673 | 0.196 | 2.264 | 0.656 | 7.810 |
Family income | 0.004 | 1.359 | 0.000 | 0.998 | 1.004 | 0.070 | 14.404 |
Diabetes Mellitus | 0.685 | 0.882 | 0.603 | 0.437 | 1.983 | 0.352 | 11.171 |
Hypertension | 0.488 | 0.761 | 0.411 | 0.521 | 1.629 | 0.367 | 7.236 |
Smoking | -0.290 | 0.613 | 0.223 | 0.637 | 0.748 | 0.225 | 2.489 |
Alcohol Use | -1.866 | 0.942 | 3.927 | 0.048* | 0.155 | 0.024 | 0.980 |
Tea Intake | -1.216 | 0.674 | 3.260 | 0.071 | 0.296 | 0.079 | 1.110 |
Lower Urinary Tract Symptoms (LUTS) | 1.464 | 0.679 | 4.649 | 0.031* | 4.324 | 1.142 | 16.363 |