Evaluation of Quality of life Among Cardiovascular Disease patients in outpatient Clinics in Ibb City, Yemen

Evaluation of Quality of life Among Cardiovascular Disease patients in outpatient Clinics in Ibb City, Yemen | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of Quality of life Among Cardiovascular Disease patients in outpatient Clinics in Ibb City, Yemen Mohammed Al-Mujahid, AbdulraKeeb shomais, Yasmin Sinan, Ghada Al-Khatib, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9202220/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Health-related quality of life (HRQoL) is a crucial patient-centered outcome in the management of chronic diseases, particularly cardiovascular disease (CVD). Objective To assess the health-related quality of life and its associated socio-demographic and clinical factors among patients with cardiovascular disease attending outpatient clinics in Ibb City, Yemen. Methods cross-sectional study was conducted from February 1 to November 29, 2025, in outpatient cardiology clinics in Ibb City, Yemen. A convenience sample of 379 patients with a confirmed diagnosis of CVD by a consultant cardiologist was enrolled. Data were collected using a two-part instrument: a structured questionnaire for socio-demographic and clinical information, and the validated Arabic version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire. Data were analyzed using SPSS version 27. Results The study included 379 CVD patients (53.8% female; nearly half aged ≥ 50 years). A majority were unemployed (68.3%), and high rates of khat chewing (70.4%), hypertension (52.2%), and diabetes (41.2%) were reported. The overall quality of life was moderately low, with a total mean score of 70.87 (SD = 9.06), representing 59.0% of the maximum possible score. The Social Relations domain scored highest at 63.0% (mean = 9.49, SD = 1.93), followed by the Psychological Health domain at 59.8% (mean = 17.95, SD = 2.94). The Environmental and Physical Health domains scored 58.5% (mean = 23.41, SD = 4.16) and 57.2% (mean = 20.02, SD = 2.99), respectively, indicating compromised quality of life across all measured domains A statistically significant association was found between total QOL scores and age, education, employment status, residence, hypertension (p = 0.001), and diabetes (p = 0.002). Younger age (p ≤ 0.013) and higher education (p = 0.001) were significantly associated with better scores across all four domains. Urban residence (p ≤ 0.029), employment (p ≤ 0.05), and the absence of diabetes (p ≤ 0.027) and hypertension (p ≤ 0.001) were associated with better outcomes in the physical, psychological, and environmental domains. Gender, marital status, smoking, and khat chewing showed no significant association with total or domain-specific QOL scores. Conclusion his study reveals that CVD patients in Ibb, Yemen, experience a significantly impaired quality of life, particularly in the Physical Healthl domain. This low HRQoL is influenced by a complex interplay of educational, economic, and clinical factors. These findings underscore the urgent need for holistic care strategies that address not only the physical but also the psychological and social well-being of CVD patients in this settin. Cardiovascular Disease Quality of Life HRQoL WHOQOL-BREF Yemen Introduction Cardiovascular diseases (CVDs) remain the leading cause of mortality and morbidity worldwide, accounting for an estimated 18 million deaths annually (Chatzinikolaou et al., 2021; Soleimani et al., 2024). This global burden is not confined to high-income nations; it is increasingly prevalent in low- and middle-income countries, including those in the Middle East and North Africa (MENA) region. The MENA region has witnessed a significant rise in CVD prevalence, with a 30% increase from 1990 to 2021, driven by demographic shifts, urbanization, and a high prevalence of risk factors such as hypertension, diabetes, and dyslipidemia (Soleimani et al., 2024; Al-Hajj et al., 2024(. While mortality rates are a crucial metric, the profound impact of CVDs extends beyond survival, significantly impairing patients' functional status, psychological well-being, and social interactions. Consequently, the assessment of Health-Related Quality of Life (HRQoL) has emerged as a critical patient-centered outcome, essential for comprehensive healthcare evaluation and planning (Asrie et al., 2025; Komalasari et al., 2020). HRQoL is a multidimensional construct encompassing physical, psychological, and social domains of health (Alharbi et al., 2022). In patients with CVD, the disease and its treatment often lead to debilitating symptoms like angina, dyspnea, and fatigue, which directly impair physical functioning. Furthermore, the psychological burden of living with a chronic, life-threatening condition frequently results in anxiety and depression, which in turn negatively affect social functioning and overall life satisfaction (Bahall et al., 2020; Dąbek et al., 2024). International research has consistently identified key factors influencing HRQoL in CVD patients. Advanced age is associated with poorer outcomes, particularly in physical functioning (Chatzinikolaou et al., 2021; Alharbi et al., 2022). Lower educational attainment and socioeconomic status are also significant predictors of reduced QOL, likely due to limited health literacy and higher psychosocial stress (Asrie et al., 2025). Clinical factors, including the presence of comorbidities like diabetes and hypertension, are strongly correlated with diminished QOL (Chatzinikolaou et al., 2021). The high prevalence of such comorbidities in the region, for instance among diabetic patients in Yemen, underscores the potential for a compounded negative impact on patient well-being (Al-Hajj et al., 2024(. Within the Arab world, studies from Saudi Arabia, Sudan, and Libya have begun to document the QOL challenges faced by CVD patients, consistently highlighting impairments in physical functioning and the role of comorbidities and demographic factors (Alharbi et al., 2022; Abdalla et al., 2024; Abduelkarem et al., 2012). In Yemen, a country grappling with a severe humanitarian crisis and a strained healthcare system, the burden of CVD is particularly acute. A foundational study conducted in Aden by Ba-Saddik and Obeid (2019) revealed that CVD patients in Yemen experience notably low QOL, especially in physical functioning and general health, with age, comorbidities, and educational level being significant influencing factors. However, research in this context remains scarce, and the situation may vary significantly across different regions of the country due to local socioeconomic and healthcare disparities. To date, no published study has specifically assessed the HRQoL of CVD patients in Ibb City, a densely populated region with unique demographic and socioeconomic characteristics. Providing crucial baseline data for local healthcare planning and the development of targeted interventions Therefore, this study aims to fill this gap by evaluating the HRQoL and its associated factors among CVD patients attending outpatient clinics in Ibb City, Yemen,. Method Study Design and Setting This cross-sectional study, conducted in major outpatient cardiology clinics in Ibb City, Yemen, collected data over ten months (February 1 – November 29, 2025). Study Population and Selection criteria The study population comprised patients with a confirmed diagnosis of cardiovascular disease attending follow-up appointments at the selected outpatient clinics. Inclusion Criteria : Patients were eligible to participate if they were: ( 1 ) Yemeni citizens, ( 2 ) aged between 20 and 75 years, and ( 3 ) had a confirmed diagnosis of cardiovascular disease (e.g., hypertension, heart failure, coronary artery disease) by a consultant cardiologist for at least six months prior to data collection. Exclusion Criteria : Patients were excluded if they: ( 1 ) had any other major chronic illness (e.g., active cancer, end-stage renal disease) not clearly related to their CVD, ( 2 ) had cognitive or communication impairments that prevented them from understanding or completing the questionnaire, or ( 3 ) refused to provide informed consent. Sampling and Sample Size A convenience sampling technique was employed. The sample size was calculated using a single population proportion formula, assuming a 50% proportion of poor QOL (to maximize sample size), a 95% confidence level, and a 5% margin of error, which yielded a minimum required sample of 384. Anticipating a potential non-response rate, 400 questionnaires were distributed, and 379 completed questionnaires were returned and deemed valid for analysis, giving a response rate of 94.75%. Data Collection Tools Data were collected using a two-part, interviewer-administered questionnaire to accommodate varying literacy levels among participants. Socio-demographic and Clinical Questionnaire : This structured section collected data on participants' age, gender, marital status, educational level, employment status, residence (urban/rural), and lifestyle factors such as smoking and khat chewing. Clinical information, including the presence of hypertension and diabetes as comorbidities, was obtained from patients' medical records and verified during the interview. Health-Related Quality of Life Questionnaire : HRQoL was assessed using the validated Arabic version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF). This 26-item instrument is an abbreviated version of the WHOQOL-100 and is widely used in chronic disease populations. It comprises four domains: Physical Health (7 items), Psychological Health (6 items), Social Relationships (3 items), and Environmental Health (8 items). Two additional items measure overall QOL and general health. Each item is scored on a 5-point Likert scale. Domain scores were calculated according to the WHOQOL-BREF user manual by computing the mean score of items within each domain. These scores were subsequently linearly transformed to a 0-100 scale to facilitate interpretation and comparison, with higher scores indicating better QOL. The Arabic version of the WHOQOL-BREF has demonstrated high validity and reliability in similar Arab populations (Ba-Saddik & Obeid, 2019). In the current study, the instrument showed excellent internal consistency, with a Cronbach's alpha coefficient of 0.88. Ethical Considerations The study protocol was reviewed and approved by the Institutional Review Board (IRB) of the Faculty of Medicine and Health Sciences, Ibb University ( Approval Number: (INSERT REAL APPROVAL NUMBER HERE ) All participants were provided with detailed information about the study's objectives. informed consent was obtained from each participant prior to data collection. Participants were assured of the confidentiality of their information and their right to withdraw from the study . Data Analysis Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 27.0. Descriptive statistics, including frequencies, percentages, means, and standard deviations (SD), were used to summarize the socio-demographic, clinical, and QOL data. The normality of the QOL domain scores was checked using the Kolmogorov-Smirnov test, which indicated a non-normal distribution (p < 0.05). Consequently, non-parametric tests were employed for inferential analysis. The Mann-Whitney U test was used to compare QOL domain scores between two independent groups (e.g., gender, presence of hypertension). The Kruskal-Wallis H test was used to compare scores among three or more groups (e.g., different educational levels). A p-value of less than 0.05 was considered statistically significant for all tests. Result Socio-demographic and Clinical Characteristics of Participants A total of 379 patients with cardiovascular disease were included in the study. The majority of patients were female (53.8%, n = 204). Regarding age distribution, nearly half of the patients (49.9%, n = 189) were aged 50 years or older, followed by those aged 41–50 years (23.0%, n = 87), 31–40 years (15.6%, n = 59), and 20–30 years (11.6%, n = 44). Most participants were married (72.8%, n = 276), while 15.8% (n = 60) were divorced or widowed, and 11.3% (n = 43) were single. Concerning educational attainment, approximately one-third of patients (32.7%, n = 124) were illiterate, 29.3% (n = 111) had completed primary education, 14.2% (n = 54) had secondary education, and 23.7% (n = 90) held a university degree or higher. Slightly more than half of the participants (51.5%, n = 195) resided in rural areas, while 48.5% (n = 184) lived in urban areas. The majority of patients (68.3%, n = 259) were unemployed, with only 31.7% (n = 120) reporting current employment. Regarding lifestyle factors, more than two-thirds of patients (70.4%, n = 267) reported chewing khat, and 28.8% (n = 109) were current smokers. With respect to clinical comorbidities, over half of the patients (52.2%, n = 198) had hypertension, and 41.2% (n = 156) had diabetes mellitus. ( In Table 1 ). Table 1 Socio-demographic and Clinical Characteristics of Patients with Cardiovascular Disease (N = 379) Variable Categories Frequency (n) Percentage (%) Gender Male 175 46.2 Female 204 53.8 Age 20–30 years 44 11.6 31–40 years 59 15.6 41–50 years 87 23.0 ≥ 50 years 189 49.9 Marital Status Single 43 11.3 Married 276 72.8 Divorced / Widowed 60 15.8 Educational Level Illiterate 124 32.7 Primary 111 29.3 Secondary 54 14.2 University or Higher 90 23.7 Residence Urban 184 48.5 Rural 195 51.5 Employment Status Employed 120 31.7 Unemployed 259 68.3 Smoking Yes 109 28.8 No 270 71.2 Khat Chewing Yes 267 70.4 No 112 29.6 Diabetes Yes 156 41.2 No 223 58.8 Hypertension Yes 198 52.2 No 181 47.8 Overall Quality of Life and Domain-Specific Scores The mean scores for the overall rating of quality of life, general health satisfaction, and the four WHOQOL-BREF domains are presented in Table 2 . The overall self-rating of quality of life (Q1) had a mean score of 2.69 (SD = 0.93) out of 5, corresponding to 53.8% of the maximum score. The mean score for general health satisfaction (Q2) was 2.94 (SD = 0.99), representing 58.8% of the maximum score. Among the four QOL domains, the Social Relations domain exhibited the highest relative score, with a transformed mean of 63.0% (raw score mean = 9.49, SD = 1.93). This was followed by the Psychological Health domain (59.8%; mean = 17.95, SD = 2.94), the Environmental domain (58.5%; mean = 23.41, SD = 4.16), and the Physical Health domain (57.2%; mean = 20.02, SD = 2.99). The overall total mean score for QOL was 70.87 (SD = 9.06), representing 59.0% of the maximum possible score. These findings indicate generally low to moderate levels of perceived quality of life across all domains among the study participants.,. Table 2 Mean Scores of Overall Quality of Life and WHOQOL-BREF Domains (N = 379) Quality of Life Domain Minimum Maximum Mean SD % of Max Score Overall Self-Rating of QOL (Q1) * 1.00 5.00 2.69 0.93 53.8% General Health Satisfaction (Q2) * 1.00 5.00 2.94 0.99 58.8% Physical Health Domain ** 10.00 30.00 20.02 2.99 57.2% Psychological Health Domain ** 10.00 28.00 17.95 2.94 59.8% Social Relations Domain ** 4.00 14.00 9.49 1.93 63.0% Environmental Domain ** 13.00 34.00 23.41 4.16 58.5% Total QOL Score 13.00 34.00 70.87 9.06 59.0% *Note: Scores for overall QOL and health satisfaction range from 1 to 5. ** Domain scores are transformed to a 0–100 scale. SD: Standard Deviation. %=Percentage Factors Associated with Total Quality of Life Scores The association between patients' socio-demographic and clinical characteristics and their total QOL scores was examined. The results revealed several statistically significant associations. Age demonstrated a significant inverse relationship with QOL (p = 0.001), with younger patients (20–30 years; mean rank = 248.02) reporting higher QOL scores compared to older patients (≥ 50 years; mean rank = 153.27). Educational level was positively associated with QOL (p = 0.001); patients with a university education or higher had the highest mean rank (232.19), whereas illiterate patients had the lowest (150.14). Employment status also showed a significant association (p = 0.001), with employed patients reporting higher QOL (mean rank = 230.57) than unemployed patients (mean rank = 171.20). Regarding residence, urban dwellers had significantly higher QOL scores (mean rank = 214.73) compared to their rural counterparts (mean rank = 164.72; p = 0.001). Clinically, the presence of diabetes was associated with significantly lower QOL scores (mean rank = 169.69) compared to non-diabetics (mean rank = 202.48; p = 0.002). Similarly, patients with hypertension had significantly lower QOL scores (mean rank = 159.00) than those without hypertension (mean rank = 220.10; p = 0.001). In contrast, no statistically significant associations were found between total QOL scores and gender (p = 0.744), marital status (p = 0.150), smoking (p = 0.247), or khat chewing (p = 0.785), as detailed in Table 3 Table 3 Association Between Total Quality of Life Scores and Patient Characteristics (N = 379) Variable Categories N Mean Rank P-value Gender Male 175 191.86 0.744 Female 204 188.40 Age 20–30 years 44 248.02 0.001 * 31–40 years 59 242.31 41–50 years 87 199.80 ≥ 50 years 189 153.27 Marital Status Single 43 182.74 0.150 Married 276 187.50 Divorced / Widowed 60 160.70 Education Illiterate 124 150.14 0.001 * Primary 111 162.05 Secondary 54 182.47 University or Higher 90 232.19 Residence Urban 184 214.73 0.001 * Rural 195 164.72 Employment Employed 120 230.57 0.001 * Unemployed 259 171.20 Smoking Yes 109 201.66 0.247 No 270 185.29 Khat Chewing Yes 267 191.40 0.785 No 112 186.67 Diabetes Yes 156 169.69 0.002 * No 223 202.48 Hypertension Yes 198 159.00 0.001 * No 181 220.10 *Statistically significant at p < 0.05 (Mann-Whitney U or Kruskal-Wallis H test).* Factors Associated with Quality of Life Domains A detailed analysis of the association between patient characteristics and each of the four QOL domains (physical, psychological, social, and environmental) is presented in Table 4 . Gender showed no statistically significant association with any of the four QOL domains (p > 0.05 for all). Residence was significantly associated with the psychological domain (p = 0.029) and the environmental domain (p = 0.001), with urban residents consistently reporting higher mean ranks than rural residents. No significant association was found with the physical or social domains. Age demonstrated a highly significant association with all four QOL domains: physical (p = 0.001), psychological (p = 0.001), social (p = 0.013), and environmental (p = 0.001). Younger age groups (20–30 and 31–40 years) consistently had higher mean ranks compared to the oldest age group (≥ 50 years). Educational level exhibited a significant positive association with the physical, psychological, and social domains (p = 0.001 for all), where patients with a university education or higher had the highest mean ranks. No significant association was found with the environmental domain (p = 0.40). Marital status was significantly associated with the physical domain (p = 0.014), psychological domain (p = 0.012), and environmental domain (p = 0.04). Single or married individuals generally reported better QOL in these domains compared to those who were divorced or widowed. No significant association was found with the social domain. Employment status was a significant factor, with unemployment being associated with lower scores in the physical (p = 0.001), psychological (p = 0.05), and environmental (p = 0.001) domains. No significant association was found with the social domain. Smoking and khat chewing did not show a statistically significant association with any of the four QOL domains (p > 0.05 for all). Clinically, the presence of diabetes was significantly associated with lower scores in the physical (p = 0.001), psychological (p = 0.001), and environmental (p = 0.027) domains. Similarly, hypertension showed a significant negative association with the physical, psychological, and environmental domains (p = 0.001 for all). Neither comorbidity was significantly associated with the social relations domain. Table 4 Association Between Quality of Life Domains and Patient Characteristics (N = 379) Variable Categories Physical Health Psychological Health Social Relations Environmental Health Mean Rank P Mean Rank P Mean Rank P Mean Rank P Gender Male 191.34 0.824 196.15 0.309 194.93 0.909 191.01 0.866 Female 188.85 184.73 190.69 189.40 Residence Urban 199.96 0.084 202.61 0.029 * 196.84 0.232 221.88 0.001 * Rural 180.61 178.11 183.55 159.92 Age 20–30 Y 238.15 0.001 * 250.51 0.001 * 223.95 0.013 * 240.36 0.001 * 31–40 Y 227.89 245.96 214.37 224.34 41–50 Y 212.53 200.31 187.64 184.41 ≥ 50 Y 156.59 153.70 175.57 170.13 Education Illiterate 165.65 0.001 * 164.24 0.001 * 191.67 0.001 * 159.34 0.40 Primary 169.73 158.79 177.14 184.05 Secondary 180.24 198.52 190.59 196.46 ≥ University 254.39 258.87 203.21 235.69 Marital Status Single 211.59 0.014 * 194.99 0.012 * 183.57 0.066 197.74 0.04 * Married 194.41 197.60 197.71 195.34 Div./Widowed 154.24 151.48 159.16 159.91 Employment Employed 235.70 0.001 * 224.87 0.05 * 195.21 0.523 206.17 0.001 * Unemployed 168.82 173.85 187.59 182.51 Smoking Yes 206.90 0.05 197.64 0.386 185.85 0.636 197.33 0.406 No 183.18 186.92 191.67 187.04 Khat Yes 187.22 0.443 194.73 0.192 187.30 0.454 190.45 0.902 No 196.63 178.72 196.43 188.93 Diabetes Yes 166.22 0.001 * 166.30 0.001 * 192.16 0.745 175.21 0.027 * No 206.63 206.58 188.49 200.35 Hypertension Yes 171.34 0.001 * 155.40 0.001 * 182.83 0.177 169.81 0.001 * No 210.42 227.85 197.84 212.09 *Statistically significant at p < 0.05 (Mann-Whitney U or Kruskal-Wallis H test).* Discussion The current sample comprised 379 patients, with a notable majority being female (53.8%). This finding contrasts sharply with studies from Pakistan (Khan et al., 2024), Greece (Chatzinikolaou et al., 2021), and Poland (Dąbek et al., 2024), where male patients predominated (70.7%, 65%, and approximately 66%, respectively). This disparity may reflect gender-specific healthcare-seeking behaviors in Yemen, where women may be more likely to utilize outpatient services, or could indicate epidemiological differences in the types of CVD prevalent in the region. Alternatively, cultural factors influencing hospital attendance may also play a role. The age distribution, with nearly half of the participants (49.9%) aged 50 years or older, aligns with the global trend of increasing CVD prevalence with advancing age. However, a significant proportion (27.2%) were under 40 years old, indicating a substantial burden of premature CVD in this population. This finding is consistent with reports from the North Africa and Middle East (NAME) region, where years of life lost due to CVD are notably high (Soleimani et al., 2024). It also echoes concerns raised in previous Yemeni studies regarding the rising prevalence of CVD risk factors among younger adults (Al-Hajj et al., 2024). From a socioeconomic perspective, a high rate of illiteracy (32.7%) and unemployment (68.3%) was observed. Low educational attainment and unemployment are well-established social determinants of health that negatively impact QoL and disease management (Schultz et al., 2018). Compared to a study conducted in Tabriz, Iran, where 41.5% of participants had higher education (Azami-Aghdash et al., 2020), and to the Greek study where 25% had higher education (Chatzinikolaou et al., 2021), the educational level in our sample is considerably lower. This, coupled with the high unemployment rate—far exceeding the 8.8% reported in the Greek sample (Chatzinikolaou et al., 2021) and the 38.8% in the Iranian sample (Azami-Aghdash et al., 2020)—suggests significant socioeconomic vulnerability among Yemeni CVD patients. Such vulnerability can limit access to medications, healthy nutrition, and regular follow-up care, thereby severely impairing QoL (Bahall et al., 2020; Asrie et al., 2025). The prevalence of hypertension (52.2%) and diabetes (41.2%) in our cohort is alarmingly high. These figures are substantially higher than those reported by Khan et al. (2024) for hypertension and diabetes combined (39.3%) and by Chatzinikolaou et al. (2021) for hypertension alone (36.3%). This indicates a severe comorbidity burden among Yemeni CVD patients, which is a strong predictor of poorer HRQoL (Asrie et al., 2025; Alharbi et al., 2022). The systemic nature of these diseases exacerbates the physical limitations imposed by CVD and increases the psychological burden of managing a complex chronic illness (Al-Hajj et al., 2024). Regarding lifestyle factors, the high rate of khat chewing (70.4%) represents a distinctive regional risk factor. Khat is a known sympathomimetic substance associated with hypertension, cardiomyopathy, and acute coronary events, posing a unique challenge to CVD management in Yemen (Abduelkarem et al., 2012; Ba-Saddik & Obeid, 2019). Interestingly, while khat chewing was highly prevalent, it showed no statistically significant association with QoL scores in this study. This suggests that its impact on perceived QoL, as measured by the WHOQOL-BREF, may be complex and potentially mediated through other clinical variables such as hypertension, rather than exerting a direct effect. Smoking prevalence (28.8%) was similar to the Pakistani study, in which 51.7% of participants had a history of smoking (Khan et al., 2024), but higher than in the Greek sample. The findings indicate a generally low to moderate level of perceived QoL among participants, with a total mean score of 70.87 (SD = 9.06) out of a possible 120, representing 59% of the maximum score. This overall reduction in QoL is a consistent finding in the global literature on CVD. Similar studies in Greece, Saudi Arabia, Poland, and other regions have uniformly reported that CVD significantly impairs patients' QoL across physical, psychological, and social domains (Chatzinikolaou et al., 2021; Alharbi et al., 2022; Dąbek et al., 2024). The quality of life (QOL) profile of cardiac patients in the current study, conducted in Ibb, Yemen, and assessed using the WHOQOL-BREF, reveals a distinct pattern when compared to findings from Trinidad (Bahall et al., 2020) and Aden, Yemen (Ba-Saddik & Obeid, 2019). The most notable finding from this study is the Social Relations Domain, which attained the highest score at 63.0% of the maximum. This contrasts markedly with Ba-Saddik and Obeid's (2019) Aden study, which reported the social relations domain as the most impaired, with a mean score of 33.5 on a transformed 0-100 scale. This discrepancy between the two Yemeni studies may be attributable to differences in sample characteristics, healthcare settings, or the timing of data collection amid the dynamic humanitarian contexts in each governorate. Nevertheless, both Yemeni studies consistently demonstrate compromised QOL among cardiac patients, with the current study's overall QOL score reaching 59.0% of the maximum, indicating moderate impairment. Although direct comparison with Bahall et al. (2020) is constrained by their use of the SF-12 instrument, the present findings of moderate physical (57.2%) and psychological (59.8%) domain scores align with the broader evidence that cardiac disease substantially diminishes both physical and mental well-being. The moderate psychological domain score observed in this study may indirectly corroborate Bahall et al.'s conclusion regarding depression as a critical comorbidity, suggesting that undetected depressive symptoms could contribute to the observed QOL reduction. The domain-specific variations, particularly the relative strength of social relations in the current study compared to Aden, warrant interpretation through socio-cultural and contextual frameworks. These findings suggest that family and community networks may function as a resilient buffer against the dual burden of chronic illness and environmental adversity, serving as an essential coping mechanism for patients in this setting. This contrasts with Bahall et al.'s (2020) Trinidadian context, where significant age-ethnicity interactions affecting QOL were identified, revealing different socio-demographic determinants. The lower General Health Satisfaction score (58.8%) relative to the overall QOL score in the present study may indicate that patients perceive their health status more negatively than their overall life quality, potentially due to adequate social support mitigating the full impact of physical limitations. The environmental domain score (58.5%) further reflects the prevailing context of instability and resource constraints in the study setting, a factor less prominent in research from more stable environments. These comparisons collectively underscore that while the physical and psychological burdens of cardiac disease exhibit universal patterns, perceived QOL is profoundly modulated by local cultural, social, and environmental determinants. A key finding of this study is the significant association between several socio-demographic factors and QoL. Higher educational level was strongly associated with better QoL in the physical, psychological, and social do mains (p = 0.001). This aligns with research from Greece and Ethiopia, which found that patients with lower education had significantly poorer QoL scores (Chatzinikolaou et al., 2021; Asrie et al., 2025). This relationship can be explained by the fact that higher education often leads to better health literacy, enabling patients to understand their illness more effectively, adhere to complex treatment regimens, and maintain healthier lifestyles (Sarkar et al., 2007). Furthermore, unemployment was a major determinant of poorer QoL, particularly in the physical and environmental domains (p = 0.001). This finding is corroborated by studies in Poland and other settings (Dąbek et al., 2024; Schultz et al., 2018). Employment provides not only financial independence to afford better care and living conditions but also a sense of purpose and social integration, all of which are crucial for overall well-being. The lack of association between unemployment and the social domain in our study may suggest that unemployed individuals in Yemen still maintain strong family and community ties, buffering some of the social isolation often associated with job loss. The significant negative impact of older age on all QoL domains (p = 0.001) is also a common thread in existing literature (Alharbi et al., 2022; Dąbek et al., 2024; Hwang et al., 2014). Older age in CVD patients is often compounded by multimorbidity, reduced physical capacity, and social isolation, which collectively diminish QoL. The finding that the youngest age group (20–30 years) had the highest QoL scores across all domains reinforces the importance of early intervention and secondary prevention to preserve QoL over the long term. Regarding residence, urban dwellers reported significantly better QoL, particularly in the psychological and environmental domains (p = 0.029 and p = 0.001, respectively). This association highlights the disparities in resource allocation and access to services between urban and rural areas—a problem exacerbated in low-income countries like Yemen with limited health infrastructure (Soleimani et al., 2024). Rural residents often face greater barriers to accessing specialized care, medications, and health information, all of which can negatively impact both psychological well-being and perceptions of the environment. The strong negative association between clinical comorbidities (hypertension and diabetes) and QoL is a critical concern. Both conditions were significantly associated with lower scores in the physical, psychological, and environmental domains. This finding is consistent with a study in Saudi Arabia, which identified comorbidities as a key predictor of low QoL (Alharbi et al., 2022). The synergistic effect of multiple chronic conditions likely amplifies symptom burden, complicates treatment regimens, and increases healthcare costs, all of which contribute to diminished QoL. Interestingly, marital status showed significant associations with the physical, psychological, and environmental domains, with divorced or widowed individuals reporting the poorest QoL. This finding underscores the importance of social support in chronic disease management, consistent with research demonstrating that married individuals often have better health outcomes due to emotional support and practical assistance with disease management (Bahall et al., 2020). In contrast to expectations, gender showed no significant association with any QoL domain. This finding diverges from some studies that have reported gender differences in QoL among CVD patients (Chatzinikolaou et al., 2021). It is possible that in the Yemeni context, the shared burden of disease and socioeconomic hardship outweighs gender-based differences in perceived QoL. Similarly, khat chewing and smoking showed no significant associations with QoL domains, which may reflect the complex, multifactorial nature of QoL perception or potential under-reporting of these behaviors due to social desirability bias. Conclusion and Recommendations This study reveals that cardiovascular disease patients in Ibb City, Yemen, experience a low to moderate quality of life, with the psychological domain being the most impaired. HRQoL was significantly influenced by educational level, employment status, age, residence, and the presence of hypertension and diabetes. These findings underscore the urgent need for a holistic, patient-centered approach that integrates psychological screening into routine care. Policymakers must develop multifaceted interventions addressing socioeconomic determinants, including patient education and risk factor awareness programs. Longitudinal and qualitative research is warranted to explore causal pathways and inform contextually appropriate strategies for improving patient well-being. Abbreviations (HRQoL) Health-related quality of life (CVD) Cardiovascular disease (WHOQOL-BREF) World Health Organization Quality of Life-BREF (QOL ) quality of life (MENA) Middle East and North Africa (SPSS) Statistical Package for the Social Sciences (SD) Standard deviation Declarations Ethics Approval and Consent to Participate The study protocol received approval from the Institutional Review Board of Ibb University (approval number: IU-RB-2025-009, dated January 12, 2025). Given the retrospective nature of the research involving anonymized data collected during routine clinical care, the requirement for informed consent was waived by the ethics committee. Patient confidentiality was safeguarded throughout by anonymizing all data during collection and analysis, with no personal identifiers included in the research database. The study was conducted in accordance with the principles of the Declaration of Helsinki and applicable local regulations governing observational research. Competing Interests All authors declare that they have no competing interests to disclose. Consent for publication Not applicable. Contributors Mohammed A, A Shomais : Investigation, Methodology, Project Administration, Writing – Review & Editing Y Sinan, Wadee A: Conceptualization, Data Curation, Formal Analysis, Writing – Original Draft Ghada A, Manar A, Reem A, Rehab A ,: Investigation, Methodology, Project Administration, Writing – Review & Editing Sohila Q, Hanan A ,Ghadeer A : Conceptualization, Data Curation, Formal Analysis, Writing – Original Draft Wadee A: Supervision, Validation, Visualization, Writing – Review & Editing Wadee A: Writing – Review & Editing, Corresponding Author Corresponding author Correspondence to Wadee Abdullah Al-Shehari Clinical trial number not applicable Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors Author Contribution Mohammed A , A Shomais : Investigation, Methodology, Project Administration, Writing – Review & EditingY Sinan , Wadee A: Conceptualization, Data Curation, Formal Analysis, Writing – Original DraftGhada A , Manar A , Reem A , Rehab A ,: Investigation, Methodology, Project Administration, Writing – Review & EditingSohila Q , Hanan A ,Ghadeer A : Conceptualization, Data Curation, Formal Analysis, Writing – Original DraftWadee A: Supervision, Validation, Visualization, Writing – Review & EditingWadee A: Writing – Review & Editing, Corresponding Author Acknowledgements Not applicable Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Abdalla MHA, Alkhalifamohamed HMA, Mohamed A, Abdalla RMSE, A. H. A., Eltoum HAA. Assessment of quality of life in patients with heart failure in Khartoum state in 2022. Archives Microbiol Immunol. 2024;8(4):493–500. https://doi.org/10.26502/ami.936500197 . Abduelkarem R, Shareif E, J., Sharif I. Evaluation of risk factors in acute myocardial infarction patients admitted to the coronary care unit, Tripoli Medical Centre, Libya. East Mediterr Health J. 2012;18(4):332–6. Al-Abedi G, Naji A. Impact of physical activity program upon elderly quality of life at Al-Amara City/Iraq. Medico Legal Update. 2020;20(3):1223–8. Al-Asadi J, Habib S, Al-Naama M. Cardiovascular risk factors among college students. Bahrain Med Bull. 2006;28(3):126–30. Al-Hajj S, Khan Z, Gul A, Ahmed O, Gupta A, Mlawa G. The prevalence of cardiovascular risk factors in patients with diabetes mellitus in Yemen: A systematic review and meta-analysis. Cureus. 2024;16(11). https://doi.org/10.7759/cureus.72848 . Article e72848. Alharbi M, Alharbi F, AlTuwayjiri A, Alharbi Y, Alhofair Y, Alanazi A, AlJlajle F, Khalil R, Al-Wutayd O. Assessment of health-related quality of life in patients with heart failure: A cross-sectional study in Saudi Arabia. Health Qual Life Outcomes. 2022;20(1). Article 128. https://doi.org/10.1186/s12955-022-02040-7 . Alkafaji A, Risun H. Prevalence rate of depression among ischemic heart diseases patients in Al-Diwaneya Province/Iraq. Medico Legal Update. 2020;20(1):1030–5. Altaleb F, Alshammari M, Alanazi M, Alenazi M, Alshammari B, Alshammari A, Alshammari A, Alenezi M. Pattern and factors associated with cardiovascular diseases among patients attending the cardiac center in Arar City, Northern Saudi Arabia. Electron Physician. 2017;9(10):5459–65. https://doi.org/10.19082/5459 . Asrie AB, Dereje M, Getachew A, Genetu B. (2025). Assessment of health-related quality of life and its associated factors among cardiovascular disease patients at a teaching hospital in Northwest Ethiopia: A cross-sectional study. BioMed Research International, 2025 , Article 1159456. https://doi.org/10.1155/bmri/1159456 Azami-Aghdash S, Gharaee H, Aghaei MH, Derakhshani N. Cardiovascular disease patient's quality of life in Tabriz City in Iran in 2020. J Community Health Res. 2020;8(4):245–52. https://doi.org/10.18502/jchr.v8i4.2080 . Bahall M, Legall G, Khan K, Ali A. Quality of life among patients with cardiac disease: The impact of comorbid depression. Health Qual Life Outcomes. 2020;18(1). Article 189. https://doi.org/10.1186/s12955-020-01453-4 . Ba-Saddik AS, Obeid FA. Assessment of quality of life among cardiovascular disease patients in Al-Gamhoria Teaching Hospital, Aden, Yemen. Yemeni J Med Health Res. 2019;8(12):1–7. Chatzinikolaou E, Daglas M, Kouzoupis A, Papathanasiou IV, Malli F. Assessment of quality of life in patients with cardiovascular disease using the SF-36, MacNew, and EQ-5D-5L questionnaires. Cureus. 2021;13(10). https://doi.org/10.7759/cureus.19017 . Article e19017. Comin-Colet J, Anguita M, Formiga F, Ruiz S, González B, Manito N. Health-related quality of life of patients with chronic systolic heart failure in Spain: Results of the VIDA-IC study. Revista Española de Cardiología (English Edition). 2016;69(3):256–71. https://doi.org/10.1016/j.rec.2015.10.017 . Dąbek J, Styczkiewicz M, Kamiński K, Kubica A, Kosior DA, Wolfshaut-Wolak R, Rajzer M, Szynal M, Jankowski P, Gąsior Z. Quality of life in patients with coronary artery disease—Multicenter POLASPIRE II study. J Clin Med. 2024;13(13). https://doi.org/10.3390/jcm13133630 . Article 3630. Fiorin BH, Moreira RSL, Lopes AB, Sipolatti WGR, Furieri LB, Fioresi M. Quality of life assessment after acute myocardial infarction. Rev Rene. 2020;21:e44265. https://doi.org/10.15253/2175-6783.20202144265 . & [additional authors if available] Hwang L, Liao C, Huang Y. Predictors of quality of life in patients with heart failure. Japan J Nurs Sci. 2014;11(4):290–8. https://doi.org/10.1111/jjns.12033 . Khan AN, Masih S, Sial JA, Aziz T, Jaseem N. Health related quality of life and associated factors among patients treated for ischaemic heart disease in two public sector hospitals of Karachi, Pakistan. J Pak Med Assoc. 2024;74(10):1773–8. https://doi.org/10.47391/JPMA.9745 . Komalasari R, Nurjanah N, Yoche MM. Quality of life of people with cardiovascular disease: A descriptive study. *Asian/Pacific Island Nurs J. 2020;4(2):92–6. https://doi.org/10.31372/20200402.1045 . Roca-Cusachs A, Dalfo A, Badia X. Relation between clinical and therapeutic variables and quality of life in hypertension. J Hypertens. 2001;19(10):1913–9. & Grupo de Estudio de la Calidad de Vida en la Hipertensión Šafaříková I, Bulava A. (2021). Assessment of the quality of life in patients with atrial fibrillation – Critical view on the current methods and insights for the future [Manuscript submitted for publication? / Unpublished manuscript?]. University of South Bohemia in České Budějovice, Faculty of Health and Social Sciences; Hospital České Budějovice, Department of Cardiology. Sarkar U, Ali S, Whooley MA. Self-efficacy and health status in patients with coronary heart disease: Findings from the heart and soul study. Psychosom Med. 2007;69(4):306–12. https://doi.org/10.1097/PSY.0b013e31805152dc . Schultz WM, Kelli HM, Lisko JC, Varghese T, Shen J, Sandesara P, Quyyumi AA, Taylor HA, Gulati M, Harold JG, Mieres JH, Ferdinand KC, Mensah GA, Sperling LS. Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation. 2018;137(20):2166–78. https://doi.org/10.1161/CIRCULATIONAHA.117.029652 . Soleimani H, Nasrollahizadeh A, Razeghian I, Molaei MM, Hakim D, Nasir K, Al-Kindi S, Hossein K. Cardiovascular disease burden in the North Africa and Middle East region: An analysis of the Global Burden of Disease study 1990–2021. BMC Cardiovasc Disord. 2024;24(1). Article 712. https://doi.org/10.1186/s12872-024-04301-9 . World Health Organization. WHOQOL: Measuring quality of life. World Health Organization; 1998. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 08 May, 2026 Reviewers agreed at journal 03 May, 2026 Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers invited by journal 21 Apr, 2026 Editor invited by journal 27 Mar, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 23 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9202220","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631109892,"identity":"324ffccf-1772-440e-9aa9-62e2e87c78d8","order_by":0,"name":"Mohammed Al-Mujahid","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Al-Mujahid","suffix":""},{"id":631109893,"identity":"0bb1c003-41ca-4302-ae4f-1fb8e61e94ff","order_by":1,"name":"AbdulraKeeb shomais","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"AbdulraKeeb","middleName":"","lastName":"shomais","suffix":""},{"id":631109896,"identity":"43f1b140-a370-417f-96ad-e60aa61b1549","order_by":2,"name":"Yasmin Sinan","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Yasmin","middleName":"","lastName":"Sinan","suffix":""},{"id":631109898,"identity":"5ac0e3d1-17be-4dec-bcd9-2be7a66dfb5c","order_by":3,"name":"Ghada Al-Khatib","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Ghada","middleName":"","lastName":"Al-Khatib","suffix":""},{"id":631109901,"identity":"7e590739-5a97-4054-b1e4-5c648c792e1e","order_by":4,"name":"Manar Almaghrabi","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Manar","middleName":"","lastName":"Almaghrabi","suffix":""},{"id":631109902,"identity":"6e342570-f9d4-4ae0-b411-a2eb0861576b","order_by":5,"name":"Reem Al shamiri","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Reem","middleName":"Al","lastName":"shamiri","suffix":""},{"id":631109904,"identity":"6f151cf7-152c-489b-8be2-d8e89d1e6572","order_by":6,"name":"Rehab Al-Wadei","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Rehab","middleName":"","lastName":"Al-Wadei","suffix":""},{"id":631109906,"identity":"4da04ad3-aaf1-43f7-8bd0-8a06317f13c2","order_by":7,"name":"Sohila Qasha","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Sohila","middleName":"","lastName":"Qasha","suffix":""},{"id":631109914,"identity":"b7b16375-2f24-4ca8-8541-b998fa40b13f","order_by":8,"name":"Hanan AL Amar","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Hanan","middleName":"AL","lastName":"Amar","suffix":""},{"id":631109917,"identity":"eed46034-984f-48e0-9025-186813164947","order_by":9,"name":"Ghadeer Alnahmy","email":"","orcid":"","institution":"Ibb University","correspondingAuthor":false,"prefix":"","firstName":"Ghadeer","middleName":"","lastName":"Alnahmy","suffix":""},{"id":631109924,"identity":"bbb06325-450a-4de9-8b12-21934f8ef676","order_by":10,"name":"Wadee Abdullah Al-shehari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACezDJxsDA2Mx8gIGxgQgthg1QLcztbQnEaTE4ANXC3nPGgEgttw+wSfwos5HjnZHzTeLnDhs5BvbDRzfg1XIugU2y51yaseSM3G2SvWfSjBl40tJu4NVyhoHtBm/b4cSNQC0SIEaDBI8ZQS03/7b9r99/I+eZ5F9itdzmbTuQwNhzhk2aKFsMexjbf8ucSzZsbG8ztpZtSzNmI+QXex7mw4ZvyuzkgVH58ObbNhs5fvbDx/BqYUCKCxYJEMmGXzkqYP5AiupRMApGwSgYOQAAF5NMxd9doRsAAAAASUVORK5CYII=","orcid":"","institution":"Ibb University","correspondingAuthor":true,"prefix":"","firstName":"Wadee","middleName":"Abdullah","lastName":"Al-shehari","suffix":""}],"badges":[],"createdAt":"2026-03-23 15:08:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9202220/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9202220/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182505,"identity":"c0e4273f-e0fd-44a1-99cd-9445fdc5c83c","added_by":"auto","created_at":"2026-04-30 08:59:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":530794,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9202220/v1/877bad35-4dc0-429a-aadd-93be1e8f6bf8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Quality of life Among Cardiovascular Disease patients in outpatient Clinics in Ibb City, Yemen","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases (CVDs) remain the leading cause of mortality and morbidity worldwide, accounting for an estimated 18\u0026nbsp;million deaths annually (Chatzinikolaou et al., 2021; Soleimani et al., 2024). This global burden is not confined to high-income nations; it is increasingly prevalent in low- and middle-income countries, including those in the Middle East and North Africa (MENA) region. The MENA region has witnessed a significant rise in CVD prevalence, with a 30% increase from 1990 to 2021, driven by demographic shifts, urbanization, and a high prevalence of risk factors such as hypertension, diabetes, and dyslipidemia (Soleimani et al., 2024; Al-Hajj et al., 2024(.\u003c/p\u003e \u003cp\u003eWhile mortality rates are a crucial metric, the profound impact of CVDs extends beyond survival, significantly impairing patients' functional status, psychological well-being, and social interactions. Consequently, the assessment of Health-Related Quality of Life (HRQoL) has emerged as a critical patient-centered outcome, essential for comprehensive healthcare evaluation and planning (Asrie et al., 2025; Komalasari et al., 2020). HRQoL is a multidimensional construct encompassing physical, psychological, and social domains of health (Alharbi et al., 2022). In patients with CVD, the disease and its treatment often lead to debilitating symptoms like angina, dyspnea, and fatigue, which directly impair physical functioning. Furthermore, the psychological burden of living with a chronic, life-threatening condition frequently results in anxiety and depression, which in turn negatively affect social functioning and overall life satisfaction (Bahall et al., 2020; Dąbek et al., 2024).\u003c/p\u003e \u003cp\u003eInternational research has consistently identified key factors influencing HRQoL in CVD patients. Advanced age is associated with poorer outcomes, particularly in physical functioning (Chatzinikolaou et al., 2021; Alharbi et al., 2022). Lower educational attainment and socioeconomic status are also significant predictors of reduced QOL, likely due to limited health literacy and higher psychosocial stress (Asrie et al., 2025). Clinical factors, including the presence of comorbidities like diabetes and hypertension, are strongly correlated with diminished QOL (Chatzinikolaou et al., 2021). The high prevalence of such comorbidities in the region, for instance among diabetic patients in Yemen, underscores the potential for a compounded negative impact on patient well-being (Al-Hajj et al., 2024(.\u003c/p\u003e \u003cp\u003eWithin the Arab world, studies from Saudi Arabia, Sudan, and Libya have begun to document the QOL challenges faced by CVD patients, consistently highlighting impairments in physical functioning and the role of comorbidities and demographic factors (Alharbi et al., 2022; Abdalla et al., 2024; Abduelkarem et al., 2012). In Yemen, a country grappling with a severe humanitarian crisis and a strained healthcare system, the burden of CVD is particularly acute. A foundational study conducted in Aden by Ba-Saddik and Obeid (2019) revealed that CVD patients in Yemen experience notably low QOL, especially in physical functioning and general health, with age, comorbidities, and educational level being significant influencing factors.\u003c/p\u003e \u003cp\u003eHowever, research in this context remains scarce, and the situation may vary significantly across different regions of the country due to local socioeconomic and healthcare disparities. To date, no published study has specifically assessed the HRQoL of CVD patients in Ibb City, a densely populated region with unique demographic and socioeconomic characteristics. Providing crucial baseline data for local healthcare planning and the development of targeted interventions Therefore, this study aims to fill this gap by evaluating the HRQoL and its associated factors among CVD patients attending outpatient clinics in Ibb City, Yemen,.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis cross-sectional study, conducted in major outpatient cardiology clinics in Ibb City, Yemen, collected data over ten months (February 1 \u0026ndash; November 29, 2025).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population and Selection criteria\u003c/h3\u003e\n\u003cp\u003eThe study population comprised patients with a confirmed diagnosis of cardiovascular disease attending follow-up appointments at the selected outpatient clinics. \u003cb\u003eInclusion Criteria\u003c/b\u003e: Patients were eligible to participate if they were: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Yemeni citizens, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) aged between 20 and 75 years, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) had a confirmed diagnosis of cardiovascular disease (e.g., hypertension, heart failure, coronary artery disease) by a consultant cardiologist for at least six months prior to data collection. \u003cb\u003eExclusion Criteria\u003c/b\u003e: Patients were excluded if they: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) had any other major chronic illness (e.g., active cancer, end-stage renal disease) not clearly related to their CVD, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) had cognitive or communication impairments that prevented them from understanding or completing the questionnaire, or (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) refused to provide informed consent.\u003c/p\u003e\n\u003ch3\u003eSampling and Sample Size\u003c/h3\u003e\n\u003cp\u003eA convenience sampling technique was employed. The sample size was calculated using a single population proportion formula, assuming a 50% proportion of poor QOL (to maximize sample size), a 95% confidence level, and a 5% margin of error, which yielded a minimum required sample of 384. Anticipating a potential non-response rate, 400 questionnaires were distributed, and 379 completed questionnaires were returned and deemed valid for analysis, giving a response rate of 94.75%.\u003c/p\u003e\n\u003ch3\u003eData Collection Tools\u003c/h3\u003e\n\u003cp\u003eData were collected using a two-part, interviewer-administered questionnaire to accommodate varying literacy levels among participants.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSocio-demographic and Clinical Questionnaire\u003c/b\u003e: This structured section collected data on participants' age, gender, marital status, educational level, employment status, residence (urban/rural), and lifestyle factors such as smoking and khat chewing. Clinical information, including the presence of hypertension and diabetes as comorbidities, was obtained from patients' medical records and verified during the interview.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHealth-Related Quality of Life Questionnaire\u003c/b\u003e: HRQoL was assessed using the validated Arabic version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF). This 26-item instrument is an abbreviated version of the WHOQOL-100 and is widely used in chronic disease populations. It comprises four domains: Physical Health (7 items), Psychological Health (6 items), Social Relationships (3 items), and Environmental Health (8 items). Two additional items measure overall QOL and general health. Each item is scored on a 5-point Likert scale. Domain scores were calculated according to the WHOQOL-BREF user manual by computing the mean score of items within each domain. These scores were subsequently linearly transformed to a 0-100 scale to facilitate interpretation and comparison, with higher scores indicating better QOL. The Arabic version of the WHOQOL-BREF has demonstrated high validity and reliability in similar Arab populations (Ba-Saddik \u0026amp; Obeid, 2019). In the current study, the instrument showed excellent internal consistency, with a Cronbach's alpha coefficient of 0.88.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Institutional Review Board (IRB) of the Faculty of Medicine and Health Sciences, Ibb University (\u003cb\u003eApproval Number: (INSERT REAL APPROVAL NUMBER HERE )\u003c/b\u003eAll participants were provided with detailed information about the study's objectives. informed consent was obtained from each participant prior to data collection. Participants were assured of the confidentiality of their information and their right to withdraw from the study .\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 27.0. Descriptive statistics, including frequencies, percentages, means, and standard deviations (SD), were used to summarize the socio-demographic, clinical, and QOL data. The normality of the QOL domain scores was checked using the Kolmogorov-Smirnov test, which indicated a non-normal distribution (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Consequently, non-parametric tests were employed for inferential analysis. The Mann-Whitney U test was used to compare QOL domain scores between two independent groups (e.g., gender, presence of hypertension). The Kruskal-Wallis H test was used to compare scores among three or more groups (e.g., different educational levels). A p-value of less than 0.05 was considered statistically significant for all tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic and Clinical Characteristics of Participants\u003c/h2\u003e \u003cp\u003eA total of 379 patients with cardiovascular disease were included in the study. The majority of patients were female (53.8%, n\u0026thinsp;=\u0026thinsp;204). Regarding age distribution, nearly half of the patients (49.9%, n\u0026thinsp;=\u0026thinsp;189) were aged 50 years or older, followed by those aged 41\u0026ndash;50 years (23.0%, n\u0026thinsp;=\u0026thinsp;87), 31\u0026ndash;40 years (15.6%, n\u0026thinsp;=\u0026thinsp;59), and 20\u0026ndash;30 years (11.6%, n\u0026thinsp;=\u0026thinsp;44). Most participants were married (72.8%, n\u0026thinsp;=\u0026thinsp;276), while 15.8% (n\u0026thinsp;=\u0026thinsp;60) were divorced or widowed, and 11.3% (n\u0026thinsp;=\u0026thinsp;43) were single. Concerning educational attainment, approximately one-third of patients (32.7%, n\u0026thinsp;=\u0026thinsp;124) were illiterate, 29.3% (n\u0026thinsp;=\u0026thinsp;111) had completed primary education, 14.2% (n\u0026thinsp;=\u0026thinsp;54) had secondary education, and 23.7% (n\u0026thinsp;=\u0026thinsp;90) held a university degree or higher. Slightly more than half of the participants (51.5%, n\u0026thinsp;=\u0026thinsp;195) resided in rural areas, while 48.5% (n\u0026thinsp;=\u0026thinsp;184) lived in urban areas. The majority of patients (68.3%, n\u0026thinsp;=\u0026thinsp;259) were unemployed, with only 31.7% (n\u0026thinsp;=\u0026thinsp;120) reporting current employment. Regarding lifestyle factors, more than two-thirds of patients (70.4%, n\u0026thinsp;=\u0026thinsp;267) reported chewing khat, and 28.8% (n\u0026thinsp;=\u0026thinsp;109) were current smokers. With respect to clinical comorbidities, over half of the patients (52.2%, n\u0026thinsp;=\u0026thinsp;198) had hypertension, and 41.2% (n\u0026thinsp;=\u0026thinsp;156) had diabetes mellitus.\u003cb\u003e(\u003c/b\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic and Clinical Characteristics of Patients with Cardiovascular Disease (N\u0026thinsp;=\u0026thinsp;379)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced / Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity or Higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhat Chewing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOverall Quality of Life and Domain-Specific Scores\u003c/h2\u003e \u003cp\u003eThe mean scores for the overall rating of quality of life, general health satisfaction, and the four WHOQOL-BREF domains are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The overall self-rating of quality of life (Q1) had a mean score of 2.69 (SD\u0026thinsp;=\u0026thinsp;0.93) out of 5, corresponding to 53.8% of the maximum score. The mean score for general health satisfaction (Q2) was 2.94 (SD\u0026thinsp;=\u0026thinsp;0.99), representing 58.8% of the maximum score.\u003c/p\u003e \u003cp\u003eAmong the four QOL domains, the Social Relations domain exhibited the highest relative score, with a transformed mean of 63.0% (raw score mean\u0026thinsp;=\u0026thinsp;9.49, SD\u0026thinsp;=\u0026thinsp;1.93). This was followed by the Psychological Health domain (59.8%; mean\u0026thinsp;=\u0026thinsp;17.95, SD\u0026thinsp;=\u0026thinsp;2.94), the Environmental domain (58.5%; mean\u0026thinsp;=\u0026thinsp;23.41, SD\u0026thinsp;=\u0026thinsp;4.16), and the Physical Health domain (57.2%; mean\u0026thinsp;=\u0026thinsp;20.02, SD\u0026thinsp;=\u0026thinsp;2.99). The overall total mean score for QOL was 70.87 (SD\u0026thinsp;=\u0026thinsp;9.06), representing 59.0% of the maximum possible score. These findings indicate generally low to moderate levels of perceived quality of life across all domains among the study participants.,.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean Scores of Overall Quality of Life and WHOQOL-BREF Domains (N\u0026thinsp;=\u0026thinsp;379)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality of Life Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% of Max Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Self-Rating of QOL (Q1) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Health Satisfaction (Q2) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Health Domain **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological Health Domain **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Relations Domain **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironmental Domain **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal QOL Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e*Note: Scores for overall QOL and health satisfaction range from 1 to 5.\u003c/p\u003e \u003cp\u003e** Domain scores are transformed to a 0\u0026ndash;100 scale. SD: Standard Deviation. %=Percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFactors Associated with Total Quality of Life Scores\u003c/h2\u003e \u003cp\u003eThe association between patients' socio-demographic and clinical characteristics and their total QOL scores was examined. The results revealed several statistically significant associations. Age demonstrated a significant inverse relationship with QOL (p\u0026thinsp;=\u0026thinsp;0.001), with younger patients (20\u0026ndash;30 years; mean rank\u0026thinsp;=\u0026thinsp;248.02) reporting higher QOL scores compared to older patients (\u0026ge;\u0026thinsp;50 years; mean rank\u0026thinsp;=\u0026thinsp;153.27). Educational level was positively associated with QOL (p\u0026thinsp;=\u0026thinsp;0.001); patients with a university education or higher had the highest mean rank (232.19), whereas illiterate patients had the lowest (150.14). Employment status also showed a significant association (p\u0026thinsp;=\u0026thinsp;0.001), with employed patients reporting higher QOL (mean rank\u0026thinsp;=\u0026thinsp;230.57) than unemployed patients (mean rank\u0026thinsp;=\u0026thinsp;171.20). Regarding residence, urban dwellers had significantly higher QOL scores (mean rank\u0026thinsp;=\u0026thinsp;214.73) compared to their rural counterparts (mean rank\u0026thinsp;=\u0026thinsp;164.72; p\u0026thinsp;=\u0026thinsp;0.001). Clinically, the presence of diabetes was associated with significantly lower QOL scores (mean rank\u0026thinsp;=\u0026thinsp;169.69) compared to non-diabetics (mean rank\u0026thinsp;=\u0026thinsp;202.48; p\u0026thinsp;=\u0026thinsp;0.002). Similarly, patients with hypertension had significantly lower QOL scores (mean rank\u0026thinsp;=\u0026thinsp;159.00) than those without hypertension (mean rank\u0026thinsp;=\u0026thinsp;220.10; p\u0026thinsp;=\u0026thinsp;0.001). In contrast, no statistically significant associations were found between total QOL scores and gender (p\u0026thinsp;=\u0026thinsp;0.744), marital status (p\u0026thinsp;=\u0026thinsp;0.150), smoking (p\u0026thinsp;=\u0026thinsp;0.247), or khat chewing (p\u0026thinsp;=\u0026thinsp;0.785), as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation Between Total Quality of Life Scores and Patient Characteristics (N\u0026thinsp;=\u0026thinsp;379)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Rank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e242.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e182.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced / Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e182.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity or Higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e232.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e164.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhat Chewing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e169.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Mann-Whitney U or Kruskal-Wallis H test).*\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFactors Associated with Quality of Life Domains\u003c/h2\u003e \u003cp\u003eA detailed analysis of the association between patient characteristics and each of the four QOL domains (physical, psychological, social, and environmental) is presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eGender showed no statistically significant association with any of the four QOL domains (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). Residence was significantly associated with the psychological domain (p\u0026thinsp;=\u0026thinsp;0.029) and the environmental domain (p\u0026thinsp;=\u0026thinsp;0.001), with urban residents consistently reporting higher mean ranks than rural residents. No significant association was found with the physical or social domains. Age demonstrated a highly significant association with all four QOL domains: physical (p\u0026thinsp;=\u0026thinsp;0.001), psychological (p\u0026thinsp;=\u0026thinsp;0.001), social (p\u0026thinsp;=\u0026thinsp;0.013), and environmental (p\u0026thinsp;=\u0026thinsp;0.001). Younger age groups (20\u0026ndash;30 and 31\u0026ndash;40 years) consistently had higher mean ranks compared to the oldest age group (\u0026ge;\u0026thinsp;50 years). Educational level exhibited a significant positive association with the physical, psychological, and social domains (p\u0026thinsp;=\u0026thinsp;0.001 for all), where patients with a university education or higher had the highest mean ranks. No significant association was found with the environmental domain (p\u0026thinsp;=\u0026thinsp;0.40). Marital status was significantly associated with the physical domain (p\u0026thinsp;=\u0026thinsp;0.014), psychological domain (p\u0026thinsp;=\u0026thinsp;0.012), and environmental domain (p\u0026thinsp;=\u0026thinsp;0.04). Single or married individuals generally reported better QOL in these domains compared to those who were divorced or widowed. No significant association was found with the social domain. Employment status was a significant factor, with unemployment being associated with lower scores in the physical (p\u0026thinsp;=\u0026thinsp;0.001), psychological (p\u0026thinsp;=\u0026thinsp;0.05), and environmental (p\u0026thinsp;=\u0026thinsp;0.001) domains. No significant association was found with the social domain. Smoking and khat chewing did not show a statistically significant association with any of the four QOL domains (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). Clinically, the presence of diabetes was significantly associated with lower scores in the physical (p\u0026thinsp;=\u0026thinsp;0.001), psychological (p\u0026thinsp;=\u0026thinsp;0.001), and environmental (p\u0026thinsp;=\u0026thinsp;0.027) domains. Similarly, hypertension showed a significant negative association with the physical, psychological, and environmental domains (p\u0026thinsp;=\u0026thinsp;0.001 for all). Neither comorbidity was significantly associated with the social relations domain.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation Between Quality of Life Domains and Patient Characteristics (N\u0026thinsp;=\u0026thinsp;379)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePhysical Health\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePsychological Health\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eSocial Relations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eEnvironmental Health\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMean Rank\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean Rank\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eMean Rank\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eMean Rank\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e194.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e191.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e190.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e189.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e202.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e196.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e221.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e178.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e183.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e159.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;30 Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e223.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e240.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40 Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e245.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e214.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e224.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;50 Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e212.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e187.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e184.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50 Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e175.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e170.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e191.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e159.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e158.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e177.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e184.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e198.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e190.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e196.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e203.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e235.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e194.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e183.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e197.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e194.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e197.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e197.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e195.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiv./Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e159.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e159.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e224.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e195.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e206.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e173.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e187.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e182.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e197.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e185.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e197.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e191.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e187.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e194.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e187.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e190.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e178.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e196.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e188.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e166.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e192.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e175.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e206.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e188.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e200.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e182.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e169.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e227.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e197.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e212.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e*Statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Mann-Whitney U or Kruskal-Wallis H test).*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current sample comprised 379 patients, with a notable majority being female (53.8%). This finding contrasts sharply with studies from Pakistan (Khan et al., 2024), Greece (Chatzinikolaou et al., 2021), and Poland (Dąbek et al., 2024), where male patients predominated (70.7%, 65%, and approximately 66%, respectively). This disparity may reflect gender-specific healthcare-seeking behaviors in Yemen, where women may be more likely to utilize outpatient services, or could indicate epidemiological differences in the types of CVD prevalent in the region. Alternatively, cultural factors influencing hospital attendance may also play a role.\u003c/p\u003e \u003cp\u003eThe age distribution, with nearly half of the participants (49.9%) aged 50 years or older, aligns with the global trend of increasing CVD prevalence with advancing age. However, a significant proportion (27.2%) were under 40 years old, indicating a substantial burden of premature CVD in this population. This finding is consistent with reports from the North Africa and Middle East (NAME) region, where years of life lost due to CVD are notably high (Soleimani et al., 2024). It also echoes concerns raised in previous Yemeni studies regarding the rising prevalence of CVD risk factors among younger adults (Al-Hajj et al., 2024).\u003c/p\u003e \u003cp\u003eFrom a socioeconomic perspective, a high rate of illiteracy (32.7%) and unemployment (68.3%) was observed. Low educational attainment and unemployment are well-established social determinants of health that negatively impact QoL and disease management (Schultz et al., 2018). Compared to a study conducted in Tabriz, Iran, where 41.5% of participants had higher education (Azami-Aghdash et al., 2020), and to the Greek study where 25% had higher education (Chatzinikolaou et al., 2021), the educational level in our sample is considerably lower. This, coupled with the high unemployment rate\u0026mdash;far exceeding the 8.8% reported in the Greek sample (Chatzinikolaou et al., 2021) and the 38.8% in the Iranian sample (Azami-Aghdash et al., 2020)\u0026mdash;suggests significant socioeconomic vulnerability among Yemeni CVD patients. Such vulnerability can limit access to medications, healthy nutrition, and regular follow-up care, thereby severely impairing QoL (Bahall et al., 2020; Asrie et al., 2025).\u003c/p\u003e \u003cp\u003eThe prevalence of hypertension (52.2%) and diabetes (41.2%) in our cohort is alarmingly high. These figures are substantially higher than those reported by Khan et al. (2024) for hypertension and diabetes combined (39.3%) and by Chatzinikolaou et al. (2021) for hypertension alone (36.3%). This indicates a severe comorbidity burden among Yemeni CVD patients, which is a strong predictor of poorer HRQoL (Asrie et al., 2025; Alharbi et al., 2022). The systemic nature of these diseases exacerbates the physical limitations imposed by CVD and increases the psychological burden of managing a complex chronic illness (Al-Hajj et al., 2024).\u003c/p\u003e \u003cp\u003eRegarding lifestyle factors, the high rate of khat chewing (70.4%) represents a distinctive regional risk factor. Khat is a known sympathomimetic substance associated with hypertension, cardiomyopathy, and acute coronary events, posing a unique challenge to CVD management in Yemen (Abduelkarem et al., 2012; Ba-Saddik \u0026amp; Obeid, 2019). Interestingly, while khat chewing was highly prevalent, it showed no statistically significant association with QoL scores in this study. This suggests that its impact on perceived QoL, as measured by the WHOQOL-BREF, may be complex and potentially mediated through other clinical variables such as hypertension, rather than exerting a direct effect. Smoking prevalence (28.8%) was similar to the Pakistani study, in which 51.7% of participants had a history of smoking (Khan et al., 2024), but higher than in the Greek sample.\u003c/p\u003e \u003cp\u003eThe findings indicate a generally low to moderate level of perceived QoL among participants, with a total mean score of 70.87 (SD\u0026thinsp;=\u0026thinsp;9.06) out of a possible 120, representing 59% of the maximum score. This overall reduction in QoL is a consistent finding in the global literature on CVD. Similar studies in Greece, Saudi Arabia, Poland, and other regions have uniformly reported that CVD significantly impairs patients' QoL across physical, psychological, and social domains (Chatzinikolaou et al., 2021; Alharbi et al., 2022; Dąbek et al., 2024).\u003c/p\u003e \u003cp\u003eThe quality of life (QOL) profile of cardiac patients in the current study, conducted in Ibb, Yemen, and assessed using the WHOQOL-BREF, reveals a distinct pattern when compared to findings from Trinidad (Bahall et al., 2020) and Aden, Yemen (Ba-Saddik \u0026amp; Obeid, 2019). The most notable finding from this study is the Social Relations Domain, which attained the highest score at 63.0% of the maximum. This contrasts markedly with Ba-Saddik and Obeid's (2019) Aden study, which reported the social relations domain as the most impaired, with a mean score of 33.5 on a transformed 0-100 scale. This discrepancy between the two Yemeni studies may be attributable to differences in sample characteristics, healthcare settings, or the timing of data collection amid the dynamic humanitarian contexts in each governorate. Nevertheless, both Yemeni studies consistently demonstrate compromised QOL among cardiac patients, with the current study's overall QOL score reaching 59.0% of the maximum, indicating moderate impairment. Although direct comparison with Bahall et al. (2020) is constrained by their use of the SF-12 instrument, the present findings of moderate physical (57.2%) and psychological (59.8%) domain scores align with the broader evidence that cardiac disease substantially diminishes both physical and mental well-being. The moderate psychological domain score observed in this study may indirectly corroborate Bahall et al.'s conclusion regarding depression as a critical comorbidity, suggesting that undetected depressive symptoms could contribute to the observed QOL reduction.\u003c/p\u003e \u003cp\u003eThe domain-specific variations, particularly the relative strength of social relations in the current study compared to Aden, warrant interpretation through socio-cultural and contextual frameworks. These findings suggest that family and community networks may function as a resilient buffer against the dual burden of chronic illness and environmental adversity, serving as an essential coping mechanism for patients in this setting. This contrasts with Bahall et al.'s (2020) Trinidadian context, where significant age-ethnicity interactions affecting QOL were identified, revealing different socio-demographic determinants. The lower General Health Satisfaction score (58.8%) relative to the overall QOL score in the present study may indicate that patients perceive their health status more negatively than their overall life quality, potentially due to adequate social support mitigating the full impact of physical limitations. The environmental domain score (58.5%) further reflects the prevailing context of instability and resource constraints in the study setting, a factor less prominent in research from more stable environments. These comparisons collectively underscore that while the physical and psychological burdens of cardiac disease exhibit universal patterns, perceived QOL is profoundly modulated by local cultural, social, and environmental determinants.\u003c/p\u003e \u003cp\u003eA key finding of this study is the significant association between several socio-demographic factors and QoL. Higher educational level was strongly associated with better QoL in the physical, psychological, and social do mains (p\u0026thinsp;=\u0026thinsp;0.001). This aligns with research from Greece and Ethiopia, which found that patients with lower education had significantly poorer QoL scores (Chatzinikolaou et al., 2021; Asrie et al., 2025). This relationship can be explained by the fact that higher education often leads to better health literacy, enabling patients to understand their illness more effectively, adhere to complex treatment regimens, and maintain healthier lifestyles (Sarkar et al., 2007).\u003c/p\u003e \u003cp\u003eFurthermore, unemployment was a major determinant of poorer QoL, particularly in the physical and environmental domains (p\u0026thinsp;=\u0026thinsp;0.001). This finding is corroborated by studies in Poland and other settings (Dąbek et al., 2024; Schultz et al., 2018). Employment provides not only financial independence to afford better care and living conditions but also a sense of purpose and social integration, all of which are crucial for overall well-being. The lack of association between unemployment and the social domain in our study may suggest that unemployed individuals in Yemen still maintain strong family and community ties, buffering some of the social isolation often associated with job loss.\u003c/p\u003e \u003cp\u003eThe significant negative impact of older age on all QoL domains (p\u0026thinsp;=\u0026thinsp;0.001) is also a common thread in existing literature (Alharbi et al., 2022; Dąbek et al., 2024; Hwang et al., 2014). Older age in CVD patients is often compounded by multimorbidity, reduced physical capacity, and social isolation, which collectively diminish QoL. The finding that the youngest age group (20\u0026ndash;30 years) had the highest QoL scores across all domains reinforces the importance of early intervention and secondary prevention to preserve QoL over the long term.\u003c/p\u003e \u003cp\u003eRegarding residence, urban dwellers reported significantly better QoL, particularly in the psychological and environmental domains (p\u0026thinsp;=\u0026thinsp;0.029 and p\u0026thinsp;=\u0026thinsp;0.001, respectively). This association highlights the disparities in resource allocation and access to services between urban and rural areas\u0026mdash;a problem exacerbated in low-income countries like Yemen with limited health infrastructure (Soleimani et al., 2024). Rural residents often face greater barriers to accessing specialized care, medications, and health information, all of which can negatively impact both psychological well-being and perceptions of the environment.\u003c/p\u003e \u003cp\u003eThe strong negative association between clinical comorbidities (hypertension and diabetes) and QoL is a critical concern. Both conditions were significantly associated with lower scores in the physical, psychological, and environmental domains. This finding is consistent with a study in Saudi Arabia, which identified comorbidities as a key predictor of low QoL (Alharbi et al., 2022). The synergistic effect of multiple chronic conditions likely amplifies symptom burden, complicates treatment regimens, and increases healthcare costs, all of which contribute to diminished QoL.\u003c/p\u003e \u003cp\u003eInterestingly, marital status showed significant associations with the physical, psychological, and environmental domains, with divorced or widowed individuals reporting the poorest QoL. This finding underscores the importance of social support in chronic disease management, consistent with research demonstrating that married individuals often have better health outcomes due to emotional support and practical assistance with disease management (Bahall et al., 2020).\u003c/p\u003e \u003cp\u003eIn contrast to expectations, gender showed no significant association with any QoL domain. This finding diverges from some studies that have reported gender differences in QoL among CVD patients (Chatzinikolaou et al., 2021). It is possible that in the Yemeni context, the shared burden of disease and socioeconomic hardship outweighs gender-based differences in perceived QoL. Similarly, khat chewing and smoking showed no significant associations with QoL domains, which may reflect the complex, multifactorial nature of QoL perception or potential under-reporting of these behaviors due to social desirability bias.\u003c/p\u003e "},{"header":"Conclusion and Recommendations","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003cp\u003eThis study reveals that cardiovascular disease patients in Ibb City, Yemen, experience a low to moderate quality of life, with the psychological domain being the most impaired. HRQoL was significantly influenced by educational level, employment status, age, residence, and the presence of hypertension and diabetes. These findings underscore the urgent need for a holistic, patient-centered approach that integrates psychological screening into routine care. Policymakers must develop multifaceted interventions addressing socioeconomic determinants, including patient education and risk factor awareness programs. Longitudinal and qualitative research is warranted to explore causal pathways and inform contextually appropriate strategies for improving patient well-being.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e(HRQoL) Health-related quality of life\u003c/p\u003e\n\u003cp\u003e(CVD) Cardiovascular disease\u003c/p\u003e\n\u003cp\u003e(WHOQOL-BREF) World Health Organization Quality of Life-BREF\u003c/p\u003e\n\u003cp\u003e(QOL ) quality of life\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(MENA) Middle East and North Africa\u003c/p\u003e\n\u003cp\u003e(SPSS) Statistical Package for the Social Sciences\u003c/p\u003e\n\u003cp\u003e(SD) Standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e \u003cp\u003e The study protocol received approval from the Institutional Review Board of Ibb University (approval number: IU-RB-2025-009, dated January 12, 2025). Given the retrospective nature of the research involving anonymized data collected during routine clinical care, the requirement for informed consent was waived by the ethics committee. Patient confidentiality was safeguarded throughout by anonymizing all data during collection and analysis, with no personal identifiers included in the research database. The study was conducted in accordance with the principles of the Declaration of Helsinki and applicable local regulations governing observational research.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eAll authors declare that they have no competing interests to disclose.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eContributors\u003c/h2\u003e \u003cp\u003eMohammed A, A Shomais : Investigation, Methodology, Project Administration, Writing \u0026ndash; Review \u0026amp; Editing\u003c/p\u003e \u003cp\u003eY Sinan, Wadee A: Conceptualization, Data Curation, Formal Analysis, Writing \u0026ndash; Original Draft\u003c/p\u003e \u003cp\u003eGhada A, Manar A, Reem A, Rehab A ,: Investigation, Methodology, Project Administration, Writing \u0026ndash; Review \u0026amp; Editing\u003c/p\u003e \u003cp\u003eSohila Q, Hanan A ,Ghadeer A : Conceptualization, Data Curation, Formal Analysis, Writing \u0026ndash; Original Draft\u003c/p\u003e \u003cp\u003eWadee A: Supervision, Validation, Visualization, Writing \u0026ndash; Review \u0026amp; Editing\u003c/p\u003e \u003cp\u003eWadee A: Writing \u0026ndash; Review \u0026amp; Editing, Corresponding Author\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCorresponding author\u003c/strong\u003e \u003cp\u003eCorrespondence to Wadee Abdullah Al-Shehari\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003enot applicable\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMohammed A , A Shomais : Investigation, Methodology, Project Administration, Writing \u0026ndash; Review \u0026amp; EditingY Sinan , Wadee A: Conceptualization, Data Curation, Formal Analysis, Writing \u0026ndash; Original DraftGhada A , Manar A , Reem A , Rehab A ,: Investigation, Methodology, Project Administration, Writing \u0026ndash; Review \u0026amp; EditingSohila Q , Hanan A ,Ghadeer A : Conceptualization, Data Curation, Formal Analysis, Writing \u0026ndash; Original DraftWadee A: Supervision, Validation, Visualization, Writing \u0026ndash; Review \u0026amp; EditingWadee A: Writing \u0026ndash; Review \u0026amp; Editing, Corresponding Author\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdalla MHA, Alkhalifamohamed HMA, Mohamed A, Abdalla RMSE, A. H. A., Eltoum HAA. Assessment of quality of life in patients with heart failure in Khartoum state in 2022. Archives Microbiol Immunol. 2024;8(4):493\u0026ndash;500. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.26502/ami.936500197\u003c/span\u003e\u003cspan address=\"10.26502/ami.936500197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbduelkarem R, Shareif E, J., Sharif I. Evaluation of risk factors in acute myocardial infarction patients admitted to the coronary care unit, Tripoli Medical Centre, Libya. East Mediterr Health J. 2012;18(4):332\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Abedi G, Naji A. Impact of physical activity program upon elderly quality of life at Al-Amara City/Iraq. Medico Legal Update. 2020;20(3):1223\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Asadi J, Habib S, Al-Naama M. Cardiovascular risk factors among college students. Bahrain Med Bull. 2006;28(3):126\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Hajj S, Khan Z, Gul A, Ahmed O, Gupta A, Mlawa G. The prevalence of cardiovascular risk factors in patients with diabetes mellitus in Yemen: A systematic review and meta-analysis. Cureus. 2024;16(11). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.72848\u003c/span\u003e\u003cspan address=\"10.7759/cureus.72848\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Article e72848.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlharbi M, Alharbi F, AlTuwayjiri A, Alharbi Y, Alhofair Y, Alanazi A, AlJlajle F, Khalil R, Al-Wutayd O. Assessment of health-related quality of life in patients with heart failure: A cross-sectional study in Saudi Arabia. Health Qual Life Outcomes. 2022;20(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 128. https://doi.org/10.1186/s12955-022-02040-7\u003c/span\u003e\u003cspan address=\"Article 128. 10.1186/s12955-022-02040-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlkafaji A, Risun H. Prevalence rate of depression among ischemic heart diseases patients in Al-Diwaneya Province/Iraq. Medico Legal Update. 2020;20(1):1030\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAltaleb F, Alshammari M, Alanazi M, Alenazi M, Alshammari B, Alshammari A, Alshammari A, Alenezi M. Pattern and factors associated with cardiovascular diseases among patients attending the cardiac center in Arar City, Northern Saudi Arabia. Electron Physician. 2017;9(10):5459\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.19082/5459\u003c/span\u003e\u003cspan address=\"10.19082/5459\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsrie AB, Dereje M, Getachew A, Genetu B. (2025). Assessment of health-related quality of life and its associated factors among cardiovascular disease patients at a teaching hospital in Northwest Ethiopia: A cross-sectional study. \u003cem\u003eBioMed Research International, 2025\u003c/em\u003e, Article 1159456. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1155/bmri/1159456\u003c/span\u003e\u003cspan address=\"10.1155/bmri/1159456\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzami-Aghdash S, Gharaee H, Aghaei MH, Derakhshani N. Cardiovascular disease patient's quality of life in Tabriz City in Iran in 2020. J Community Health Res. 2020;8(4):245\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18502/jchr.v8i4.2080\u003c/span\u003e\u003cspan address=\"10.18502/jchr.v8i4.2080\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahall M, Legall G, Khan K, Ali A. Quality of life among patients with cardiac disease: The impact of comorbid depression. Health Qual Life Outcomes. 2020;18(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 189. https://doi.org/10.1186/s12955-020-01453-4\u003c/span\u003e\u003cspan address=\"Article 189. 10.1186/s12955-020-01453-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBa-Saddik AS, Obeid FA. Assessment of quality of life among cardiovascular disease patients in Al-Gamhoria Teaching Hospital, Aden, Yemen. Yemeni J Med Health Res. 2019;8(12):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChatzinikolaou E, Daglas M, Kouzoupis A, Papathanasiou IV, Malli F. Assessment of quality of life in patients with cardiovascular disease using the SF-36, MacNew, and EQ-5D-5L questionnaires. Cureus. 2021;13(10). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.19017\u003c/span\u003e\u003cspan address=\"10.7759/cureus.19017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Article e19017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eComin-Colet J, Anguita M, Formiga F, Ruiz S, Gonz\u0026aacute;lez B, Manito N. Health-related quality of life of patients with chronic systolic heart failure in Spain: Results of the VIDA-IC study. Revista Espa\u0026ntilde;ola de Cardiolog\u0026iacute;a (English Edition). 2016;69(3):256\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.rec.2015.10.017\u003c/span\u003e\u003cspan address=\"10.1016/j.rec.2015.10.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDąbek J, Styczkiewicz M, Kamiński K, Kubica A, Kosior DA, Wolfshaut-Wolak R, Rajzer M, Szynal M, Jankowski P, Gąsior Z. Quality of life in patients with coronary artery disease\u0026mdash;Multicenter POLASPIRE II study. J Clin Med. 2024;13(13). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jcm13133630\u003c/span\u003e\u003cspan address=\"10.3390/jcm13133630\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Article 3630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFiorin BH, Moreira RSL, Lopes AB, Sipolatti WGR, Furieri LB, Fioresi M. Quality of life assessment after acute myocardial infarction. Rev Rene. 2020;21:e44265. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15253/2175-6783.20202144265\u003c/span\u003e\u003cspan address=\"10.15253/2175-6783.20202144265\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. \u0026amp; [additional authors if available]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHwang L, Liao C, Huang Y. Predictors of quality of life in patients with heart failure. Japan J Nurs Sci. 2014;11(4):290\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jjns.12033\u003c/span\u003e\u003cspan address=\"10.1111/jjns.12033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan AN, Masih S, Sial JA, Aziz T, Jaseem N. Health related quality of life and associated factors among patients treated for ischaemic heart disease in two public sector hospitals of Karachi, Pakistan. J Pak Med Assoc. 2024;74(10):1773\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.47391/JPMA.9745\u003c/span\u003e\u003cspan address=\"10.47391/JPMA.9745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKomalasari R, Nurjanah N, Yoche MM. Quality of life of people with cardiovascular disease: A descriptive study. *Asian/Pacific Island Nurs J. 2020;4(2):92\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.31372/20200402.1045\u003c/span\u003e\u003cspan address=\"10.31372/20200402.1045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoca-Cusachs A, Dalfo A, Badia X. Relation between clinical and therapeutic variables and quality of life in hypertension. J Hypertens. 2001;19(10):1913\u0026ndash;9. \u0026amp; Grupo de Estudio de la Calidad de Vida en la Hipertensi\u0026oacute;n\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eŠafař\u0026iacute;kov\u0026aacute; I, Bulava A. (2021). \u003cem\u003eAssessment of the quality of life in patients with atrial fibrillation \u0026ndash; Critical view on the current methods and insights for the future\u003c/em\u003e [Manuscript submitted for publication? / Unpublished manuscript?]. University of South Bohemia in Česk\u0026eacute; Budějovice, Faculty of Health and Social Sciences; Hospital Česk\u0026eacute; Budějovice, Department of Cardiology.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarkar U, Ali S, Whooley MA. Self-efficacy and health status in patients with coronary heart disease: Findings from the heart and soul study. Psychosom Med. 2007;69(4):306\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/PSY.0b013e31805152dc\u003c/span\u003e\u003cspan address=\"10.1097/PSY.0b013e31805152dc\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz WM, Kelli HM, Lisko JC, Varghese T, Shen J, Sandesara P, Quyyumi AA, Taylor HA, Gulati M, Harold JG, Mieres JH, Ferdinand KC, Mensah GA, Sperling LS. Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation. 2018;137(20):2166\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1161/CIRCULATIONAHA.117.029652\u003c/span\u003e\u003cspan address=\"10.1161/CIRCULATIONAHA.117.029652\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoleimani H, Nasrollahizadeh A, Razeghian I, Molaei MM, Hakim D, Nasir K, Al-Kindi S, Hossein K. Cardiovascular disease burden in the North Africa and Middle East region: An analysis of the Global Burden of Disease study 1990\u0026ndash;2021. BMC Cardiovasc Disord. 2024;24(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 712. https://doi.org/10.1186/s12872-024-04301-9\u003c/span\u003e\u003cspan address=\"Article 712. 10.1186/s12872-024-04301-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. WHOQOL: Measuring quality of life. World Health Organization; 1998.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cardiovascular Disease, Quality of Life, HRQoL, WHOQOL-BREF, Yemen","lastPublishedDoi":"10.21203/rs.3.rs-9202220/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9202220/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHealth-related quality of life (HRQoL) is a crucial patient-centered outcome in the management of chronic diseases, particularly cardiovascular disease (CVD).\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo assess the health-related quality of life and its associated socio-demographic and clinical factors among patients with cardiovascular disease attending outpatient clinics in Ibb City, Yemen.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ecross-sectional study was conducted from February 1 to November 29, 2025, in outpatient cardiology clinics in Ibb City, Yemen. A convenience sample of 379 patients with a confirmed diagnosis of CVD by a consultant cardiologist was enrolled. Data were collected using a two-part instrument: a structured questionnaire for socio-demographic and clinical information, and the validated Arabic version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire. Data were analyzed using SPSS version 27.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study included 379 CVD patients (53.8% female; nearly half aged\u0026thinsp;\u0026ge;\u0026thinsp;50 years). A majority were unemployed (68.3%), and high rates of khat chewing (70.4%), hypertension (52.2%), and diabetes (41.2%) were reported. The overall quality of life was moderately low, with a total mean score of 70.87 (SD\u0026thinsp;=\u0026thinsp;9.06), representing 59.0% of the maximum possible score. The Social Relations domain scored highest at 63.0% (mean\u0026thinsp;=\u0026thinsp;9.49, SD\u0026thinsp;=\u0026thinsp;1.93), followed by the Psychological Health domain at 59.8% (mean\u0026thinsp;=\u0026thinsp;17.95, SD\u0026thinsp;=\u0026thinsp;2.94). The Environmental and Physical Health domains scored 58.5% (mean\u0026thinsp;=\u0026thinsp;23.41, SD\u0026thinsp;=\u0026thinsp;4.16) and 57.2% (mean\u0026thinsp;=\u0026thinsp;20.02, SD\u0026thinsp;=\u0026thinsp;2.99), respectively, indicating compromised quality of life across all measured domains A statistically significant association was found between total QOL scores and age, education, employment status, residence, hypertension (p\u0026thinsp;=\u0026thinsp;0.001), and diabetes (p\u0026thinsp;=\u0026thinsp;0.002). Younger age (p\u0026thinsp;\u0026le;\u0026thinsp;0.013) and higher education (p\u0026thinsp;=\u0026thinsp;0.001) were significantly associated with better scores across all four domains. Urban residence (p\u0026thinsp;\u0026le;\u0026thinsp;0.029), employment (p\u0026thinsp;\u0026le;\u0026thinsp;0.05), and the absence of diabetes (p\u0026thinsp;\u0026le;\u0026thinsp;0.027) and hypertension (p\u0026thinsp;\u0026le;\u0026thinsp;0.001) were associated with better outcomes in the physical, psychological, and environmental domains. Gender, marital status, smoking, and khat chewing showed no significant association with total or domain-specific QOL scores.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ehis study reveals that CVD patients in Ibb, Yemen, experience a significantly impaired quality of life, particularly in the Physical Healthl domain. This low HRQoL is influenced by a complex interplay of educational, economic, and clinical factors. These findings underscore the urgent need for holistic care strategies that address not only the physical but also the psychological and social well-being of CVD patients in this settin.\u003c/p\u003e","manuscriptTitle":"Evaluation of Quality of life Among Cardiovascular Disease patients in outpatient Clinics in Ibb City, Yemen","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 20:32:17","doi":"10.21203/rs.3.rs-9202220/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"182910489566694170488838477501186593226","date":"2026-05-08T11:13:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227341201562199241379928996420369629328","date":"2026-05-03T04:58:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-21T21:45:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94671922243992465847244361526836308183","date":"2026-04-21T15:09:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T14:28:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-27T06:13:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T02:38:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-26T02:38:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-03-23T14:56:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fb41032e-1ab3-4417-9ab2-744f72fd5efd","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"182910489566694170488838477501186593226","date":"2026-05-08T11:13:13+00:00","index":61,"fulltext":""},{"type":"reviewerAgreed","content":"227341201562199241379928996420369629328","date":"2026-05-03T04:58:42+00:00","index":59,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T20:32:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 20:32:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9202220","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9202220","identity":"rs-9202220","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}