Health-related quality of life and associated factors among community-dwelling older adults with cardiovascular diseases in Vietnam: a nationwide cross-sectional study using EQ-5D-5L

Health-related quality of life and associated factors among community-dwelling older adults with cardiovascular diseases in Vietnam: a nationwide cross-sectional study using EQ-5D-5L | 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 Health-related quality of life and associated factors among community-dwelling older adults with cardiovascular diseases in Vietnam: a nationwide cross-sectional study using EQ-5D-5L Cuong Le Manh, Thanh Le Dinh, Suong Nguyen Thi Thao, Trung Nguyen Hoang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9092933/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives To describe health-related quality of life (HRQoL) and to examine factors associated with HRQoL among community-dwelling older adults with cardiovascular diseases (CVDs) in Vietnam. Methods We conducted a multicenter descriptive cross-sectional study with analytical components in eight provinces/cities (Ha Giang, Thai Binh, Nghe An, Dak Lak, Dong Nai, Can Tho, Hanoi, and Ho Chi Minh City) from October 2021 to September 2025. Participants were adults aged ≥ 60 years who were identified as having at least one cardiovascular disease based on self-reported medical history and verification with medical records (when available). Data were collected through face-to-face interviews using a structured questionnaire and the EQ-5D-5L. EQ-5D-5L index scores were derived using the Vietnamese value set. Descriptive statistics were presented as frequencies/proportions and mean ± SD; group comparisons used appropriate statistical tests. Independent factors associated with HRQoL were identified using a multivariable Generalized Linear Model (GLM), with 95% confidence intervals estimated via bootstrapping. Results A total of 2,330 older adults with CVDs were included in the analysis. The mean EQ-5D-5L index score was 0.7175 ± 0.1468. Across CVD subgroups, mean scores ranged from 0.6552 ± 0.1394 (peripheral/venous vascular disease) to 0.7482 ± 0.1417 (valvular heart disease). In the multivariable GLM, lower HRQoL was independently associated with poor household economic status (β = −0.028; 95% CI: −0.047 to − 0.009; p = 0.004), multimorbidity with ≥ 4 comorbid conditions (β = −0.028; 95% CI: −0.036 to − 0.019; p = 0.001), and increasing disease duration (2–5 years: β = −0.080; 95% CI: −0.082 to − 0.077; p = 0.001; 6–10 years: β = −0.221; 95% CI: −0.228 to − 0.213; p = 0.001; >10 years: β = −0.450; 95% CI: −0.459 to − 0.441; p = 0.001). Lower secondary/high school education was also associated with lower HRQoL compared with university/postgraduate education (β = −0.013; 95% CI: −0.022 to − 0.004; p = 0.001). Conclusions HRQoL among community-dwelling older adults with CVDs in Vietnam is reduced, with prominent burdens in pain/discomfort and anxiety/depression. HRQoL is strongly influenced by multimorbidity, longer disease duration, and socioeconomic disadvantage. Quality of life Cardiovascular diseases Aged Multimorbidity Vietnam Figures Figure 1 Introduction Population ageing is accelerating worldwide and has become a major public health challenge of the 21st century ( 1 , 2 ). The World Health Organization (WHO) projects that by 2030, one in six people globally will be aged 60 years or older, and emphasizes that ageing is often accompanied by an increasing burden of chronic diseases, functional decline, and greater demand for long-term care ( 3 ). In Vietnam, population ageing is also occurring rapidly, creating an urgent need for epidemiological evidence and outcome measures that fully reflect the disease burden among older adults—not only in terms of mortality, but also in function and quality of life ( 4 ). Cardiovascular diseases (CVDs) represent the most prevalent group of non-communicable diseases and have a particularly profound impact on older adults due to their chronic course, recurrent episodes, and frequent coexistence with multiple comorbidities ( 2 , 5 ). According to the WHO, CVDs remain the leading cause of death worldwide, with an estimated 17.9 million deaths in 2019, accounting for approximately 32% of all global deaths ( 6 ). In Vietnam, WHO reports also indicate that CVDs contributed to about 31% of all deaths in 2016; in addition, hypertension is a highly prevalent risk factor and its management at health-care facilities remains limited ( 7 ). These figures highlight the substantial burden of CVDs and the need to strengthen chronic disease management strategies, particularly among older adults. However, contemporary care goals for older adults with CVDs extend beyond reducing mortality or cardiovascular events, and increasingly aim to optimize mobility, self-care, participation in daily activities, pain and discomfort control, and mental well-being ( 8 ). In this context, health-related quality of life (HRQoL) measures have been increasingly emphasized in cardiovascular research because they directly capture patients’ lived experiences, facilitate communication between clinicians and patients, and have potential utility in evaluating the quality of health care ( 8 ). Among older adults, HRQoL is also strongly influenced by multimorbidity and polypharmacy; prior studies suggest that EQ-5D measures can be applied to older populations with multiple comorbid conditions and can help identify domains of functional impairment that require intervention ( 9 ). Among instruments used to assess HRQoL, the EQ-5D questionnaire is a generic measure that has been widely applied in population studies, clinical research, and health economic evaluations ( 10 ). The five-level version (EQ-5D-5L) was developed to increase sensitivity and reduce ceiling effects compared with the three-level version ( 10 ). Vietnam has established an EQ-5D-5L value set based on societal preferences from a nationally representative sample, providing an important foundation for HRQoL research ( 11 ). Nevertheless, evidence on HRQoL in Vietnam remains limited and inconsistent. Most existing studies describe HRQoL in the general Vietnamese population or focus on specific diseases or hospital-based samples, with varying sample sizes and representativeness ( 12 – 15 ). To date, large-scale studies describing HRQoL among community-dwelling older adults with CVDs are lacking. Therefore, assessing HRQoL in community-dwelling older adults with CVDs in Vietnam using a standardized instrument (EQ-5D-5L) and deriving utility scores based on the Vietnamese value set is necessary to (i) describe the burden of impaired quality of life across functional domains, (ii) identify associated factors in real-world community settings, and (iii) generate evidence to inform the design, prioritization, and evaluation of chronic CVD management programs aimed at improving quality of life among older adults. Accordingly, this study was conducted to describe HRQoL and analyze factors associated with HRQoL among older adults with CVDs in Vietnam using the EQ-5D-5L instrument. Methods Study design This study employed an analytical cross-sectional descriptive design to assess health-related quality of life (HRQoL) and associated factors among community-dwelling older adults living with cardiovascular diseases (CVDs) in Vietnam. The study was implemented as a multicenter survey across eight provinces/cities representing different geographic regions, including Ha Giang, Thai Binh, Nghe An, Dak Lak, Dong Nai, Can Tho, Hanoi, and Ho Chi Minh City. Data collection was conducted from October 2021 to September 2025. Study population The target population comprised older adults residing in the community in the selected provinces/cities. Stage 1 (assessment of CVD morbidity profile): individuals aged ≥ 60 years who were living in the study areas during the survey period, were able to participate in the interview, and provided consent were enrolled. Stage 2 (HRQoL assessment): among participants in Stage 1, those identified as having cardiovascular disease were selected to assess HRQoL using the EQ-5D-5L. In this study, CVD status was determined based on participant-reported medical history, with verification against prior medical records when available. Collected CVD categories included (but were not limited to) hypertension, valvular heart disease, heart failure, coronary artery disease/ischemic heart disease, arrhythmias, cerebrovascular disease, and peripheral vascular/venous disease. Inclusion criteria: community-dwelling adults aged ≥ 60 years who had resided in the study areas for ≥ 2 years, agreed to participate, and had complete information on age and marital status. Participants were included in the analysis if they were identified as having at least one CVD within the surveyed CVD categories (including hypertension; cerebrovascular disease; localized ischemic heart disease; heart failure; cardiac arrhythmias; valvular heart disease; and peripheral/venous vascular disease) and had available EQ-5D-5L data. Exclusion criteria: ( 1 ) refusal to participate or withdrawal during the survey; ( 2 ) inability to complete the interview due to severe illness or communication/cognitive limitations at the time of data collection; and ( 3 ) missing core information required for analyses aligned with the study objectives. Sampling and participant recruitment A multistage sampling strategy was applied across the eight provinces/cities. In each study site, administrative units (districts/communes/wards) were selected according to the local sampling plan. At the commune/ward level, the research team worked with local health facilities and authorities to compile lists of community-dwelling older adults and performed systematic random sampling to invite eligible individuals. Selected individuals were approached, provided with study information and objectives, and asked to sign informed consent prior to data collection. Participants received an explanation of the study objectives and provided consent in accordance with applicable regulations, after which they were interviewed face-to-face using a standardized questionnaire. During data collection, interviewers checked questionnaire completeness and documented non-participation or non-completion to support control of selection bias. For Stage 2, from the roster of older adults with CVD identified in Stage 1, systematic random sampling was again applied (based on sample allocation by province/city) to recruit a sufficient number of participants for HRQoL assessment. Data collection procedures and quality control Data were collected through face-to-face interviews with participants in the community following a standardized and uniform protocol across study sites. The data-collection instrument consisted of a structured questionnaire with four main components: ( 1 ) sociodemographic characteristics; ( 2 ) morbidity status, including cardiovascular diseases; ( 3 ) health behaviors and selected related factors; and ( 4 ) assessment of health-related quality of life (HRQoL) using the EQ-5D-5L ( 11 ). Prior to field implementation, the research team conducted interviewer training covering the study objectives, interviewing techniques, standardized administration of questions, questionnaire completion procedures, and principles of confidentiality and research ethics. During data collection, interviewers reviewed questionnaires immediately after each interview to minimize missing data and data-entry errors (e.g., skipped items, incorrect coding, or inconsistent recording across sections). Collected data were cleaned and verified before analysis. The research team performed range checks and consistency checks to detect out-of-range values, implausible response patterns, and incomplete records. Identified discrepancies (if any) were cross-checked against the original forms and/or verified with the field investigators responsible for the site, and then corrected according to the established quality-control procedures. In addition, to minimize measurement error, the team applied standardized supervision and site-level monitoring during data collection, particularly for HRQoL assessment items, to ensure comparability across study locations. Study variables The primary outcome was health-related quality of life (HRQoL), measured using the EQ-5D-5L descriptive system comprising five domains: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. EQ-5D-5L health states were converted into EQ-5D-5L index scores; this index served as the key outcome variable for statistical analyses and was calculated using the Vietnamese value set ( 10 , 11 ). Independent variables were collected and categorized based on the study questionnaire, including: (a) Sociodemographic characteristics: age group (60–69, 70–79, ≥ 80 years), sex (male/female), educational level (no formal schooling, primary, lower secondary/upper secondary, college/intermediate, postgraduate), personal economic status (financially dependent vs having income), household economic status (poor vs non-poor), place of residence (rural vs urban), and social participation (participation vs non-participation in social activities). (b) Morbidity and treatment-related characteristics: multimorbidity status (1 condition, 2–3 conditions, ≥ 4 conditions), duration of CVD (10 years), and number of medications used (0, 1–2, ≥ 3). The presence of additional physician-diagnosed conditions (yes/no) was also recorded, including diagnosis of coronary artery disease/ischemic heart disease and assessment of hypertension status (previously diagnosed and/or currently diagnosed). Cardiovascular diagnoses (yes/no) recorded included hypertension, cerebrovascular disease, localized ischemic heart disease, heart failure, arrhythmia, valvular heart disease, and peripheral/venous vascular disease. (c) Health behaviors and social engagement: medication adherence (adherent/non-adherent), smoking (current smoker/non-smoker), alcohol use (current drinker/non-drinker), physical activity (inactive; <150 minutes/week; ≥150 minutes/week, based on WHO recommendations for moderate-intensity physical activity among older adults) ( 16 ), and social activity participation (yes/no) ( 16 ). Statistical analysis Following data collection, completeness and internal consistency were assessed prior to data entry and analysis. Range and logic checks were performed to identify out-of-range values, missing key variables, and implausible combinations. Detected errors were cross-checked against paper questionnaires and/or verified with site investigators and corrected in accordance with the quality-control process. Analyses were conducted among community-dwelling older adults with CVDs who had HRQoL data available. Statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA). Categorical variables were summarized as frequencies and percentages. Continuous variables were described using mean ± standard deviation (SD) for approximately normally distributed data; otherwise, medians and interquartile ranges (IQRs) or ranges (minimum–maximum) were reported. HRQoL was primarily summarized using the EQ-5D-5L index score. To compare EQ-5D-5L index scores across groups defined by sociodemographic, morbidity-related, and behavioral characteristics, appropriate inferential tests were applied depending on distributional assumptions: independent-samples t-test/one-way ANOVA for normally distributed outcomes with homogeneous variances; or non-parametric tests (Mann–Whitney U for two groups and Kruskal–Wallis for three or more groups) when normality assumptions were not met. For categorical variables, between-group comparisons were conducted using the Chi-square test (or Fisher’s exact test, as appropriate). To identify independent factors associated with HRQoL, a multivariable Generalized Linear Model (GLM) was fitted with the EQ-5D-5L index score as the dependent variable and sociodemographic, morbidity-related, and behavioral variables as predictors. Results are presented as regression coefficients (β) with 95% confidence intervals estimated using bootstrapping, and two-sided p-values; statistical significance was set at p < 0.05. Results In Stage 1, the study surveyed 6,203 community-dwelling older adults, of whom 3,753 were identified as having cardiovascular disease (60.5%). In Stage 2 (HRQoL assessment), 2,330 older adults with cardiovascular disease were included in the analysis (62.1% of CVD cases; 37.6% of the overall sample). The sample was stratified by province/city to ensure adequate numbers for description and comparisons. The Stage 1 and Stage 2 sample sizes by site were as follows: Ha Giang (700; 264), Hanoi (1,001; 373), Thai Binh (700; 264), Nghe An (700; 264), Dak Lak (700; 264), Ho Chi Minh City (1,002; 373), Dong Nai (700; 264), and Can Tho (700; 264). Table 1 summarizes baseline characteristics of 2,330 community-dwelling older adults with cardiovascular diseases. Participants were predominantly aged 60–69 years (42.2%), with comparable proportions of men and women (49.7% vs. 50.3%). Nearly half had intermediate/college education (49.5%), while 26.6% had university/postgraduate education; most reported personal income (81.0%) and household economic conditions of “adequate or better” (80.1%). Clinically, multimorbidity was common (2–3 conditions: 38.8%; ≥4: 27.5%), and CVD duration was most frequently 2–5 years (47.8%). Medication use varied, with 32.3% using ≥ 4 drugs and 30.4% not using medications. Hypertension was the most prevalent diagnosis (77.2%), followed by cerebrovascular disease (16.2%) and localized ischemic heart disease (15.8%). Regarding behaviors, 43.6% were current smokers and 36.6% reported alcohol/beer use; half were physically inactive (50.0%), only 13.5% achieved ≥ 150 minutes/week, and social participation was low (20.3%). Table 1 Baseline characteristics of community-dwelling older adults with cardiovascular diseases (N = 2,330) Sociodemographic characteristics n (%) % Age group (years) 60–69 984 42.2 70–79 763 32.7 ≥ 80 583 25.0 Sex Male 1159 49.7 Female 1171 50.3 Education No schooling/Primary 274 11.8 Secondary/High school 283 12.1 Vocational/College 1153 49.5 University/Postgraduate 620 26.6 Personal income Has income 1887 81.0 No income/Not working 443 19.0 Household economic status Poor 463 19.9 Adequate or above 1867 80.1 Marital status Living with spouse 1535 65.9 Spouse living apart 239 10.3 Separated/Divorced/Widowed 556 23.9 Clinical characteristics Number of comorbidities 1 disease 787 33.9 2–3 diseases 903 38.8 ≥ 4 diseases 640 27.5 Duration of disease 10 years 294 12.6 Number of medications currently used 0 708 30.4 1 314 13.5 2–3 556 23.9 ≥ 4 752 32.3 Hypertension diagnosis and treatment status Diagnosed and treated 1798 77.2 Not diagnosed/no hypertension 532 22.8 Cardiovascular diagnoses Hypertension 1798 77.2 Cerebrovascular disease 378 16.2 Ischemic heart disease 369 15.8 Heart failure 105 4.5 Arrhythmia 89 3.8 Valvular heart disease 55 2.4 Varicose veins (lower limb) 62 2.7 Health behaviors and social participation Smoking status Current smoker 1016 43.6 Non-smoker 1314 56.4 Alcohol use Current drinking 853 36.6 No drinking 1477 63.4 Physical activity None 1165 50.0 < 150 min/week 851 36.5 ≥ 150 min/week 314 13.5 Participation in social activities Yes 473 20.3 No 1857 79.7 Figure 1 shows the distribution across the five EQ-5D-5L domains in older adults with CVDs (n = 2,330). In the domains of mobility, self-care, and usual activities, most participants reported no problems (Level 1), with proportions of 71.5%, 78.0%, and 78.2%, respectively; the proportions reporting problems (Levels 2–4) were 28.4%, 22.0%, and 21.8%. In contrast, the pain/discomfort domain showed a very high prevalence of problems (91.8%), primarily at Level 2 (57.6%) and Level 3 (29.8%), whereas Level 1 accounted for only 8.2%. For anxiety/depression, Level 1 was not observed (0.0%); most participants were classified as Level 3 (69.7%) and Level 4 (20.8%). No cases were recorded at Level 5 in any domain. The overall mean EQ-5D-5L index score for the study sample was 0.7175 ± 0.1468 (Table 2 ). Across diagnostic groups, valvular heart disease had the highest mean score (0.7482 ± 0.1417), whereas peripheral/venous vascular disease showed the lowest (0.6552 ± 0.1394). Participants with localized ischemic heart disease also had a relatively low mean score (0.6936 ± 0.1639). The remaining conditions (hypertension, cerebrovascular disease, heart failure, and arrhythmia) exhibited similar mean index scores, ranging from 0.7090 to 0.7159. Table 2 EQ-5D-5L index scores among older adults with different cardiovascular conditions (n = 2,330) Characteristics Number (n = 2,330) Percentage (%) Mean SD Hypertension 1,798 77.2 0.7107 0.1492 Cerebrovascular disease 378 16.2 0.7138 0.1374 Localized ischemic heart disease 369 15.8 0.6936 0.1639 Heart failure 105 4.5 0.7090 0.1530 Cardiac arrhythmia 89 3.8 0.7159 0.1468 Valvular heart disease 55 2.4 0.7482 0.1417 Peripheral/venous vascular disease 62 2.7 0.6552 0.1394 Overall 0.7175 0.1468 Table 3 indicates that EQ-5D-5L index scores varied across selected sociodemographic characteristics among older adults with cardiovascular diseases. No statistically significant differences in EQ-5D-5L index scores were observed by age group (p = 0.736) or sex (p = 0.442). In contrast, educational attainment was significantly associated with EQ-5D-5L index scores (p = 0.001), with higher mean scores generally observed in groups with higher education compared with those with lower education. No significant differences were found according to personal economic status, household economic status, or marital status (all p > 0.05). Table 3 EQ-5D-5L index scores by sociodemographic characteristics among older adults with cardiovascular diseases (n = 2,330) Characteristics Number (n = 2,330) Percentage (%) EQ-5D-5L index (Mean ± SD) Median (Min–Max) p Age group 60–69 984 42.2 0.7200 ± 0.1448 0.8035 (0.32–0.89) 0.736 70–79 763 32.7 0.7144 ± 0.1477 0.8035 (0.32–0.94) ≥ 80 583 25.0 0.7171 ± 0.1491 0.7448 (0.32–0.89) Sex Male 1,159 49.7 0.7198 ± 0.1445 0.8035 (0.32–0.89) 0.442 Female 1,171 50.3 0.7151 ± 0.1491 0.8035 (0.32–0.94) Educational level No schooling/primary 274 11.8 0.7003 ± 0.1486 0.7448 (0.3187–0.8875) 0.001 Lower/upper secondary 283 12.1 0.6931 ± 0.1533 0.7448 (0.3187–0.9362) Intermediate/college 1,153 49.5 0.7258 ± 0.1433 0.8035 (0.4895–0.8875) University/postgraduate 620 26.6 0.7205 ± 0.1479 0.8035 (0.3187–0.8875) Personal economic status Having income 1,887 81.0 0.7195 ± 0.1492 0.8035 (0.3186–0.8874) 0.166 No income/unemployed 443 19.0 0.7088 ± 0.1362 0.7448 (0.3777–0.9362) Household economic status Poor 463 19.9 0.7097 ± 0.1381 0.7448 (0.3778–0.9362) 0.205 Adequate or better 1,867 80.1 0.7194 ± 0.1489 0.8035 (0.3187–0.8875) Marital status Living with spouse 1,535 65.9 0.7184 ± 0.1480 0.8035 (0.3187–0.9362) 0.143 Married but not cohabiting 239 10.3 0.7310 ± 0.1364 0.8035 (0.3187–0.8875) Single/divorced/widowed 556 23.9 0.7091 ± 0.1476 0.7608 (0.3187–0.9362) Table 4 shows that EQ-5D-5L index scores differed significantly across several morbidity-related and behavioral characteristics. EQ-5D-5L index scores declined markedly as the number of comorbid conditions increased (p < 0.001): the highest mean score was observed among those with one condition (0.8103 ± 0.0666), whereas the lowest was found in those with ≥ 4 conditions (0.5797 ± 0.1408). Similarly, EQ-5D-5L index scores decreased substantially with longer disease duration (p < 0.001), from 0.8896 ± 0.0101 ( 10 years). The EQ-5D-5L index also differed by the number of medications currently used (p < 0.001), with mean scores ranging from 0.7004 ± 0.1597 (no medication) to 0.7458 ± 0.1232 (one medication). Participants with a prior diagnosis and treatment of hypertension had a lower mean EQ-5D-5L index than those without such diagnosis (0.7107 ± 0.1492 vs. 0.7404 ± 0.1363; p < 0.001). No significant differences were observed by smoking status (p = 0.533) or alcohol use (p = 0.992). In contrast, physical activity was significantly associated with EQ-5D-5L index scores (p = 0.010), with higher scores among those achieving ≥ 150 minutes/week compared with inactive individuals (0.7338 ± 0.1504 vs. 0.7088 ± 0.1444). Additionally, participants who engaged in social activities had higher EQ-5D-5L index scores than those who did not (0.7357 ± 0.1308 vs. 0.7128 ± 0.1503; p = 0.002). Table 4 EQ-5D-5L index scores among older adults with cardiovascular diseases by morbidity-related characteristics and health behaviors (n = 2,330) Characteristics Number (n = 2,330) Percentage (%) EQ-5D-5L index (Mean ± SD) Median (Min-Max) p Number of comorbid conditions 1 condition 787 33.8 0.8103 ± 0.0666 0.8035 (0.4366–0.9362) < 0.001 2–3 conditions 903 38.8 0.7342 ± 0.1283 0.8035 (0.3187–0.8875) ≥ 4 conditions 640 27.5 0.5797 ± 0.1408 0.5739 (0.187–0.8523) Duration of CVD < 2 years 181 7.8 0.8896 ± 0.0101 0.8875 (0.8875–0.9362) 10 years 294 12.6 0.4201 ± 0.0517 0.4366 (0.3187–0.4895) Number of medications currently used 0 medications 708 30.4 0.7004 ± 0.1597 0.8035 (0.3187–0.8875) < 0.001 1 medication 314 13.5 0.7458 ± 0.1232 0.8035 (0.3187–0.8875) 2–3 medications 556 23.9 0.7184 ± 0.1393 0.8035 (0.3187–0.8875) ≥ 4 medications 752 32.3 0.7210 ± 0.1468 0.8035 (0.3817–0.9362) Hypertension status Previously diagnosed with hypertension and treated 1798 77.2 0.7107 ± 0.1492 0. 8035 (0.3187–0.8875) < 0.001 Not previously diagnosed / not currently diagnosed with hypertension 532 22.8 0.7404 ± 0.1363 0.8035 (0.4243–0.9362) Smoking status Current smoker 1016 43.6 0.7196 ± 0.1419 0.8035 (0.3187–0.9263) 0.533 Non-smoker 1314 56.4 0.7158 ± 0.1505 0.8035 (0.3187–0.9263) Alcohol use Current drinker 853 36.6 0.7175 ± 0.1397 0.7841 (0.3187–0.8875) 0.992 Non-drinker 1477 63.4 0.7174 ± 0.1508 0.8035 (0.4243–0.9362) Physical activity Inactive 1165 50.0 0.7088 ± 0.1444 0.7448 (0.3187–0.9362) 0.010 < 150 minutes/week 851 36.5 0.7233 ± 0.1482 0.8035 (0.3187–0.8875) ≥ 150 minutes/week 314 13.5 0.7338 ± 0.1504 0.8035 (0.3232–0.8875) Participation in social activities Participated 473 20.3 0.7357 ± 0.1308 0.8035 (0.3232–0.8875) 0.002 Did not participate 1857 79.7 0.7128 ± 0.1503 0.8035 (0.3187–0.9362) In the multivariable GLM with bootstrap-based confidence intervals (Table 5 ), EQ-5D-5L index scores were significantly associated with educational attainment, personal and household economic status, multimorbidity, disease duration, number of medications used, and smoking status. Compared with participants with 10 years: β = −0.450; all p = 0.001). Relative to participants with one comorbid condition, those with ≥ 4 comorbidities had lower EQ-5D-5L index scores (β = −0.028; p = 0.001), whereas the 2–3 comorbidity group did not differ significantly (p = 0.823). Participants from poor households had lower EQ-5D-5L index scores than those with adequate household economic conditions (β = −0.028; p = 0.004). Regarding education, lower/upper secondary education was associated with lower EQ-5D-5L index scores compared with college/technical school or higher (β = −0.013; p = 0.001). In terms of medication use, using one medication was associated with a higher EQ-5D-5L index score compared with no medication use (β = 0.008; p = 0.013), while ≥ 4 medications showed a borderline association (p = 0.051). Current smokers had higher EQ-5D-5L index scores than non-smokers (β = 0.007; p = 0.007). No statistically significant associations were observed for age group, sex, marital status, alcohol/beer use, physical activity level, or participation in social activities (all p > 0.05). Table 5 Factors associated with EQ-5D-5L index scores in the multivariable Generalized Linear Model (GLM) (n = 2,330) Variable Comparison group Adjusted β 95% CI (Bootstrap) p (2-tailed) Age group (years) 60–69 Ref ≥ 80 0.001 -0.004, 0.007 0.710 70–79 0.004 -0.001, 0.010 0.107 Sex Male Ref Female -0.002 -0.006, 0.003 0.452 Education College/technical school / Postgraduate Ref No schooling/primary 0.001 -0.007, 0.010 0.758 Lower/upper secondary -0.013 -0.022, -0.004 0.001 Intermediate/college -0.002 -0.007, 0.003 0.473 Personal economic status Having income Ref Financially dependent 0.029 0.010, 0.048 0.003 Household economic status Adequate or better Ref Poor -0.028 -0.047, -0.009 0.004 Marital status Living with spouse Ref Single/divorced/widowed 0.004 -0.001, 0.010 0.107 Married but not cohabiting 0.0002 -0.007, 0.007 0.939 Number of comorbid conditions 1 condition Ref ≥ 4 conditions -0.028 -0.036, -0.019 0.001 2–3 conditions 0.0004 -0.003, 0.004 0.823 Duration of disease 10 years -0.450 -0.459, -0.441 0.001 6–10 years -0.221 -0.228, -0.213 0.001 2–5 years -0.080 -0.082, -0.077 0.001 Number of medications used 0 medications Ref ≥ 4 medications 0.006 0.000, 0.011 0.051 1 medication 0.008 0.002, 0.014 0.013 2–3 medications -0.002 -0.009, 0.004 0.437 Smoking Non-smoker Ref Current smoker 0.007 0.002, 0.012 0.007 Alcohol/beer use Non-drinker Ref Current drinker 0.0004 -0.005, 0.006 0.863 Physical activity < 150 minutes/week Ref Inactive 0.003 -0.002, 0.007 0.325 ≥ 150 minutes/week -0.006 -0.012, 0.001 0.100 Participation in social activities Participated Ref Did not participate -0.004 -0.009, 0.002 0.160 Discussion Our study provides large-scale, multicenter evidence on health-related quality of life (HRQoL) among community-dwelling older adults with cardiovascular diseases (CVDs) in Vietnam, assessed using the EQ-5D-5L and converted using the Vietnamese value set. The EQ-5D-5L is a five-level version developed to improve sensitivity and reduce ceiling effects compared with the EQ-5D-3L, and the use of a Vietnam-specific value set facilitates interpretation that is appropriate to the Vietnamese population context ( 10 , 11 ). The mean EQ-5D-5L index score was 0.7175 ± 0.1468, indicating that overall HRQoL among older adults with CVDs was substantially lower than reference values reported for the general Vietnamese population, where population-based studies commonly report a mean score of approximately 0.91 ( 14 ). This finding is consistent with the clinical reality that CVDs in older adults often follow a chronic course, limit activity, increase physical symptoms, and impose sustained psychological burden, collectively reflected in markedly reduced HRQoL in this group compared with the general population in Vietnam. A notable contribution of this study is the domain-specific distribution of problems on the EQ-5D-5L. While most participants reported no problems in mobility, self-care, and usual activities, the prevalence of problems was very high for pain/discomfort, and anxiety/depression was reported by nearly all participants. From both clinical and public health perspectives, these findings suggest that among community-dwelling older adults with CVDs in Vietnam, symptom burden (particularly pain/discomfort) and psychological burden may be key drivers of reduced HRQoL, potentially more prominent than functional limitations in mobility or self-care. A study in Hong Kong (China) reported a mean score of 0.85 among patients with hypertension, lower than the general population (0.92). Recent studies also suggest that hypertension alone may not markedly reduce quality of life; however, HRQoL declines substantially when cardiovascular complications occur ( 17 ). In Vietnam, studies among older adults with CVDs have similarly shown that pain/discomfort is among the most frequently affected EQ-5D domains, and that socioeconomic factors and multimorbidity play important roles in HRQoL ( 15 ). Nevertheless, the very high level of problems in the anxiety/depression domain observed in our study is distinctive. This may reflect a true burden of mental health problems among older adults with CVDs in Vietnam, particularly in the context of chronic disease, loneliness, and social isolation; however, it may also relate to how items were understood/interpreted and to the standardization of interview administration. Therefore, future studies should incorporate specific depression/anxiety instruments or qualitative approaches to triangulate and clarify the nature of this finding. Factors associated with HRQoL In the univariable analyses, HRQoL was significantly associated with multiple sociodemographic characteristics (age, sex, educational attainment, marital status), morbidity- and treatment-related characteristics (number of comorbid conditions, disease duration, number of medications used), and health behaviors (smoking, alcohol/beer use, physical activity, and participation in social activities). However, in the multivariable model (GLM), only a subset of variables remained statistically significant after adjustment. This pattern may be explained by: ( 1 ) the interrelationships among independent variables (e.g., age, education, economic status, and morbidity burden); ( 2 ) the possibility that lifestyle behaviors (particularly physical activity) may influence HRQoL through intermediary pathways such as reduced pain, improved function, and better mental well-being; and ( 3 ) collinearity among morbidity- and treatment-related variables (disease duration, number of comorbid conditions, and number of medications). Two findings are particularly noteworthy. First, HRQoL decreased markedly as disease duration increased, and second, a higher morbidity burden, especially ≥ 4 comorbid conditions, was independently associated with lower HRQoL. Relative to those with disease duration 10 years groups, respectively. These results align with the clinical trajectory of CVDs in older adults: longer disease duration typically entails a more chronic course, accumulation of complications, progressive functional decline, and increased treatment burden, all of which may adversely affect HRQoL across EQ-5D domains, particularly pain/discomfort and anxiety/depression ( 18 ). In addition, multimorbidity is a common and increasingly recognized determinant of HRQoL. The multivariable model showed progressively lower HRQoL with increasing numbers of comorbid conditions; compared with participants with one condition, those with 2–3 and ≥ 4 conditions had substantially lower scores. This is consistent with evidence that older adults with multimorbidity often experience overlapping symptoms and cumulative limitations, which together contribute to declines in physical function, pain, and mental health ( 17 , 19 ). Regarding socioeconomic factors, education remained significant after adjustment. Compared with the highest educational group (college/technical school or higher), lower educational attainment was associated with significantly lower HRQoL (e.g., lower/upper secondary school). This finding is plausible because education is closely linked to health literacy, access to health services, treatment adherence, and social resources ( 20 , 21 ). In contrast, marital status did not remain significant in the fully adjusted model. Compared with those living with a spouse, being single/divorced/widowed was associated with lower HRQoL in unadjusted analyses, which is consistent with a Hong Kong study by Xu et al. (2017) reporting higher mean EQ-5D-5L scores among older adults living with family than among those living alone or with a spouse; that study suggested that loneliness and depressive symptoms may contribute to poorer HRQoL ( 20 ). Our findings are generally consistent with Vietnamese population evidence highlighting the role of social support in adaptation to chronic illness and symptom control ( 14 ). Nevertheless, in our community-based sample in Vietnam, the effect of marital status was attenuated after controlling for household economic factors and family structure, suggesting that marital status may be a proxy for broader social and economic resources ( 21 ). The relationship between the number of medications used and HRQoL in the multivariable model suggested that the group using one medication differed significantly from the group using no medication, whereas the ≥ 4 medications group showed a non-significant trend toward lower HRQoL. Conceptually, medication use may reflect both disease severity and treatment burden, including side effects and regimen complexity; prior studies among older adults have reported that polypharmacy is associated with lower HRQoL ( 22 , 23 ). Therefore, in practice, studies should further characterize medication patterns and appropriateness, and interventions should emphasize regular medication review and optimization, particularly in older adults with multimorbidity, to support improvements in HRQoL. In our sample, physical inactivity was common, the proportion meeting ≥ 150 minutes/week was low, and social participation was limited. In univariable analyses, both physical activity and social participation were associated with HRQoL. However, after adjustment for sociodemographic and morbidity-related factors (notably disease duration and multimorbidity), these variables were no longer statistically significant, suggesting that their independent effects may be partly mediated by disease burden. This may be interpreted as physical activity and social participation influencing HRQoL through improvements in function, pain reduction, and mental well-being; when models adjust for morbidity burden, the remaining independent association may be diminished. Nonetheless, from a practical standpoint, physical activity remains a key intervention target in older adults. WHO recommends reducing sedentary time and encouraging appropriate levels of activity tailored to age and health status ( 16 ). Moreover, evidence synthesis indicates that physical activity interventions in older adults, especially those with heart failure—can improve physical function and quality of life ( 24 ). Finally, our study found that smoking was associated with higher HRQoL in the multivariable model. This contrasts with most studies reporting that smoking is associated with lower HRQoL ( 25 ). A possible explanation is the cross-sectional nature of our study and potential residual confounding: current smokers in this sample may have had lower measured morbidity severity, reflecting survival bias (healthier smokers surviving to older age), or reverse causation whereby more severe patients were more likely to quit smoking and thus were classified as non-smokers, leading to apparently higher HRQoL among current smokers. Future studies should refine smoking classification (never/former/current), capture smoking duration and intensity, and explore these hypotheses in longitudinal designs. Implications Based on the key findings, intervention priorities should focus on subgroups at higher risk of poor HRQoL, including older adults with multimorbidity, longer disease duration, lower educational attainment, and limited family support (e.g., single/divorced/widowed). Beyond optimizing cardiovascular treatment, the EQ-5D-5L domain profile suggests the need for integrated approaches that include chronic pain management, mental health screening and interventions, and rehabilitation or programs to maintain mobility and functional capacity. These directions are consistent with recommendations for physical activity in older adults, including targets of 150–300 minutes/week of moderate-intensity activity combined with muscle-strengthening and balance-enhancing exercises ( 16 ). Strengths and limitations This study has several notable strengths, including a large sample size, the use of the standardized EQ-5D-5L instrument with conversion based on the Vietnamese value set, and analyses of both the overall index score and domain-specific health dimensions, which enhance interpretability and facilitate international comparisons. However, the study also has limitations typical of cross-sectional descriptive designs, including the inability to infer causality, and potential recall bias and residual confounding. Several lifestyle variables (smoking, alcohol/beer use, physical activity, and social participation) were self-reported, which may increase the risk of misclassification. In addition, incomplete measurement of disease severity and complications (e.g., heart failure functional class, symptom control, or recent hospitalization events) could have influenced the findings. Therefore, longitudinal studies and risk stratification analyses, particularly those incorporating disease severity, are needed to validate these associations and clarify the influence of these factors. Conclusion This study indicates that HRQoL among community-dwelling older adults with cardiovascular diseases in Vietnam is reduced, with commonly affected domains including pain/discomfort, anxiety/depression, and mobility limitations. Lower HRQoL was consistently observed among individuals with a higher disease burden (multimorbidity and longer disease duration) and among socioeconomically vulnerable groups (lower education, economic hardship, and limited family support). HRQoL was also related to treatment characteristics such as the number of medications used. These findings underscore the need to implement comprehensive and integrated community-based CVD management models for older adults, prioritizing symptom control, mental health screening and support, maintenance/rehabilitation of mobility, and optimization of medication use, especially for high-risk groups. Abbreviations ANOVA Analysis of variance CI confidence interval CVDs cardiovascular diseases EQ-5D EuroQol 5-dimension questionnaire EQ-5D-3L 3-level version of the EuroQol 5-dimension questionnaire EQ-5D-5L 5-level version of the EuroQol 5-dimension questionnaire GLM Generalized Linear Model HRQoL health-related quality of life IQR interquartile range SD standard deviation WHO World Health Organization. Declarations Conflict of Interest : The authors declared no conflicts of interest with respect to the authorship and/or publication of this article. Funding: This study was funded by the Ministry of Science and Technology of Vietnam and constitutes part of the national-level project entitled “Assessment of the current status and quality of life of older adults with cardiovascular diseases and the effectiveness of selected treatment techniques in Vietnam” (Project code: ĐTĐL.CN.52/21). Author Contribution Conceived of the study: C.L.M, T.L.D, C.N.V.; Participated in its design and data analysis and statistics: T.L.D, S.N.T.T, C.L.M, T.Q.T, T.N.H; Helped to draft the manuscript: C.N.V, T.N.H, S.N.T.T, T.Q.T. All authors read and approved the final manuscript. Acknowledgement The authors would like to thank the local health authorities and staff at the study sites for their support with participant recruitment and data collection. We are also grateful to all participants for their time and valuable contributions to this research Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References Prince MJ, Wu F, Guo Y, Robledo LMG, O'Donnell M, Sullivan R, et al. The burden of disease in older people and implications for health policy and practice. lancet. 2015;385(9967):549–62. Xi J-Y, Liang B-H, Zhang W-J, Yan B, Dong H, Chen Y-Y, et al. Effects of population aging on quality of life and disease burden: a population-based study. Global Health Res Policy. 2025;10(1):2. World Health Organization. Ageing and health [Internet]. Geneva: World Health Organization. 2025 [cited 2026 Mar 11]. Available from: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health General Statistics Office of Viet Nam. The Population and Housing Census, 2019: Population Ageing and Older Persons in Viet Nam [Internet]. Hanoi: Ministry of Planning and Investment, General Statistics Office; 2021 [cited 2026 Mar 11]. Available from: https://www.nso.gov.vn/en/data-and-statistics/2021/08/population-ageing-and-older-persons-in-viet-nam/ Vakka A, Warren JS, Drosatos K. Cardiovascular aging: from cellular and molecular changes to therapeutic interventions. J Cardiovasc aging. 2023;3(3):23. World Health Organization. Cardiovascular diseases (CVDs) [Internet]. Geneva: World Health Organization. 2025 [cited 2026 Mar 11]. 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Mai VQ, Sun S, Minh HV, Luo N, Giang KB, Lindholm L, et al. An EQ-5D-5L value set for Vietnam. Qual Life Res. 2020;29(7):1923–33. Vo LNQ, Forse R, Codlin AJ, Huynh HB, Wiemers AMC, Creswell J, et al. A life that’s worth living–measuring health-related quality of life among people treated for tuberculosis in Viet Nam: a longitudinal EQ-5D-5L survey. Health Qual Life Outcomes. 2025;23(1):43. Tran BX, Ohinmaa A, Nguyen LT, Nguyen TA, Nguyen TH. Determinants of health-related quality of life in adults living with HIV in Vietnam. AIDS Care. 2011;23(10):1236–45. Nguyen LH, Tran BX, Hoang Le QN, Tran TT, Latkin CA. Quality of life profile of general Vietnamese population using EQ-5D-5L. Health Qual Life Outcomes. 2017;15(1):199. Tran BX, Moir MP, Thai TPT, Nguyen LH, Ha GH, Nguyen THT, et al. Socioeconomic inequalities in health-related quality of life among patients with cardiovascular diseases in Vietnam. Biomed Res Int. 2018;2018(1):2643814. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62. Wong ELY, Xu RH, Cheung AWL. Health-related quality of life among patients with hypertension: population-based survey using EQ-5D-5L in Hong Kong SAR, China. BMJ open. 2019;9(9):e032544. Wan L, Yang G, Dong H, Liang X, He Y. Impact of cardiovascular disease on health-related quality of life among older adults in eastern China: evidence from a national cross-sectional survey. Front Public Health. 2024;11:1300404. Makovski TT, Schmitz S, Zeegers MP, Stranges S, van den Akker M. Multimorbidity and quality of life: systematic literature review and meta-analysis. Ageing Res Rev. 2019;53:100903. Xu RH, Cheung AWL, Wong EL-Y. Examining the health-related quality of life using EQ-5D-5L in patients with four kinds of chronic diseases from specialist outpatient clinics in Hong Kong SAR, China. Patient Prefer Adherence. 2017:1565–72. Hoi LV, Chuc NT, Lindholm L. Health-related quality of life, and its determinants, among older people in rural Vietnam. BMC Public Health. 2010;10(1):549. Van Wilder L, Devleesschauwer B, Clays E, Pype P, Vandepitte S, De Smedt D. Polypharmacy and health-related quality of life/psychological distress among patients with chronic disease. Prev Chronic Dis. 2022;19:E50. Montiel-Luque A, Núñez-Montenegro AJ, Martín-Aurioles E, Canca-Sánchez JC, Toro-Toro MC, González-Correa JA, et al. Medication-related factors associated with health-related quality of life in patients older than 65 years with polypharmacy. PLoS ONE. 2017;12(2):e0171320. Racey M, Ali MU, Sherifali D, Fitzpatrick-Lewis D, Lewis R, Jovkovic M, et al. Effectiveness of physical activity interventions in older adults with frailty or prefrailty: a systematic review and meta-analysis. Can Med Association Open Access J. 2021;9(3):E728–43. Vogl M, Wenig CM, Leidl R, Pokhrel S. Smoking and health-related quality of life in English general population: implications for economic evaluations. BMC Public Health. 2012;12(1):203. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-9092933","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611701363,"identity":"b6ed895f-5a29-4f1f-b243-0f1781850897","order_by":0,"name":"Cuong Le Manh","email":"","orcid":"","institution":"Viet Nam University Of Traditional Medicine","correspondingAuthor":false,"prefix":"","firstName":"Cuong","middleName":"Le","lastName":"Manh","suffix":""},{"id":611701364,"identity":"65ce0809-2ec0-4bbd-8ba1-06c1584a92e0","order_by":1,"name":"Thanh Le Dinh","email":"","orcid":"","institution":"Thong Nhat Hospital","correspondingAuthor":false,"prefix":"","firstName":"Thanh","middleName":"Le","lastName":"Dinh","suffix":""},{"id":611701365,"identity":"3e715a80-31a0-4772-a098-382a11c0d37c","order_by":2,"name":"Suong Nguyen Thi Thao","email":"","orcid":"","institution":"Thong Nhat Hospital","correspondingAuthor":false,"prefix":"","firstName":"Suong","middleName":"Nguyen Thi","lastName":"Thao","suffix":""},{"id":611701366,"identity":"814f7a4d-b059-4f12-b0c9-9e6a16ca1d43","order_by":3,"name":"Trung Nguyen Hoang","email":"","orcid":"","institution":"Vietnam Military Medical University","correspondingAuthor":false,"prefix":"","firstName":"Trung","middleName":"Nguyen","lastName":"Hoang","suffix":""},{"id":611701367,"identity":"fde8d1dc-ccb6-4047-98eb-c1be47cf7649","order_by":4,"name":"Trang Nguyen Thi Thu","email":"","orcid":"","institution":"Vietnam Military Medical University","correspondingAuthor":false,"prefix":"","firstName":"Trang","middleName":"Nguyen Thi","lastName":"Thu","suffix":""},{"id":611701368,"identity":"59f06124-9667-4730-99d8-34b6eb2c91d2","order_by":5,"name":"Chuyen Nguyen Van","email":"","orcid":"","institution":"Vietnam Military Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chuyen","middleName":"Nguyen","lastName":"Van","suffix":""},{"id":611701369,"identity":"2aae2579-e530-4bb7-a989-593613a610ba","order_by":6,"name":"Thanh Ta Quang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYDADAwYGNgbGBgYZfhAvoQC3Sh4oLQHVYsAj2QDSYkCKFoMDUEtxAXv2w9skfu6orTNnP3vsAeOOPzzG51cnfnhgwCDPL3YAuy08aWWSvWeOS1j25KUbMJ4x4DG78XazBNBhhjNnJ+BwWI6ZBG/bMQmDA0AGYxtIy9kNIC0JBrdxaOF/Yyb5F6Tl/BuIFuMZZzf/wKtFIsdMmretRsLgBtQWA/7ebfhtufGs2Fq27YDkhhtAWxLPGPNI3ODdZpFgIIHTL+z9yRtvvm2r4zc4D7Tl4w45Of7+s5tv/qiwkeeXxq6FARIFhyFMsBoJCIlLOUxLHRKf/wA+1aNgFIyCUTACAQAaaFsg7zV40wAAAABJRU5ErkJggg==","orcid":"","institution":"Nam Thang Long Hospital","correspondingAuthor":true,"prefix":"","firstName":"Thanh","middleName":"Ta","lastName":"Quang","suffix":""}],"badges":[],"createdAt":"2026-03-11 10:10:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9092933/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9092933/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105477025,"identity":"49e933f5-7db9-4fa6-a4e7-a97a4fa21c9a","added_by":"auto","created_at":"2026-03-26 13:05:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37945,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of EQ-5D-5L domains among older adults with cardiovascular diseases (n = 2,330)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9092933/v1/1f245d824e1a631762df2003.png"},{"id":106404505,"identity":"b5cbe964-b36f-4066-89f4-378d275d218a","added_by":"auto","created_at":"2026-04-08 09:16:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1827079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9092933/v1/cf6005a0-32c9-42ab-86a1-84ff8dc5f958.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health-related quality of life and associated factors among community-dwelling older adults with cardiovascular diseases in Vietnam: a nationwide cross-sectional study using EQ-5D-5L","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePopulation ageing is accelerating worldwide and has become a major public health challenge of the 21st century (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The World Health Organization (WHO) projects that by 2030, one in six people globally will be aged 60 years or older, and emphasizes that ageing is often accompanied by an increasing burden of chronic diseases, functional decline, and greater demand for long-term care (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Vietnam, population ageing is also occurring rapidly, creating an urgent need for epidemiological evidence and outcome measures that fully reflect the disease burden among older adults\u0026mdash;not only in terms of mortality, but also in function and quality of life (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCardiovascular diseases (CVDs) represent the most prevalent group of non-communicable diseases and have a particularly profound impact on older adults due to their chronic course, recurrent episodes, and frequent coexistence with multiple comorbidities (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). According to the WHO, CVDs remain the leading cause of death worldwide, with an estimated 17.9\u0026nbsp;million deaths in 2019, accounting for approximately 32% of all global deaths (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In Vietnam, WHO reports also indicate that CVDs contributed to about 31% of all deaths in 2016; in addition, hypertension is a highly prevalent risk factor and its management at health-care facilities remains limited (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). These figures highlight the substantial burden of CVDs and the need to strengthen chronic disease management strategies, particularly among older adults. However, contemporary care goals for older adults with CVDs extend beyond reducing mortality or cardiovascular events, and increasingly aim to optimize mobility, self-care, participation in daily activities, pain and discomfort control, and mental well-being (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In this context, health-related quality of life (HRQoL) measures have been increasingly emphasized in cardiovascular research because they directly capture patients\u0026rsquo; lived experiences, facilitate communication between clinicians and patients, and have potential utility in evaluating the quality of health care (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Among older adults, HRQoL is also strongly influenced by multimorbidity and polypharmacy; prior studies suggest that EQ-5D measures can be applied to older populations with multiple comorbid conditions and can help identify domains of functional impairment that require intervention (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong instruments used to assess HRQoL, the EQ-5D questionnaire is a generic measure that has been widely applied in population studies, clinical research, and health economic evaluations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The five-level version (EQ-5D-5L) was developed to increase sensitivity and reduce ceiling effects compared with the three-level version (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Vietnam has established an EQ-5D-5L value set based on societal preferences from a nationally representative sample, providing an important foundation for HRQoL research (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Nevertheless, evidence on HRQoL in Vietnam remains limited and inconsistent. Most existing studies describe HRQoL in the general Vietnamese population or focus on specific diseases or hospital-based samples, with varying sample sizes and representativeness (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). To date, large-scale studies describing HRQoL among community-dwelling older adults with CVDs are lacking. Therefore, assessing HRQoL in community-dwelling older adults with CVDs in Vietnam using a standardized instrument (EQ-5D-5L) and deriving utility scores based on the Vietnamese value set is necessary to (i) describe the burden of impaired quality of life across functional domains, (ii) identify associated factors in real-world community settings, and (iii) generate evidence to inform the design, prioritization, and evaluation of chronic CVD management programs aimed at improving quality of life among older adults. Accordingly, this study was conducted to describe HRQoL and analyze factors associated with HRQoL among older adults with CVDs in Vietnam using the EQ-5D-5L instrument.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis study employed an analytical cross-sectional descriptive design to assess health-related quality of life (HRQoL) and associated factors among community-dwelling older adults living with cardiovascular diseases (CVDs) in Vietnam. The study was implemented as a multicenter survey across eight provinces/cities representing different geographic regions, including Ha Giang, Thai Binh, Nghe An, Dak Lak, Dong Nai, Can Tho, Hanoi, and Ho Chi Minh City. Data collection was conducted from October 2021 to September 2025.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe target population comprised older adults residing in the community in the selected provinces/cities.\u003c/p\u003e \u003cp\u003eStage 1 (assessment of CVD morbidity profile): individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years who were living in the study areas during the survey period, were able to participate in the interview, and provided consent were enrolled.\u003c/p\u003e \u003cp\u003eStage 2 (HRQoL assessment): among participants in Stage 1, those identified as having cardiovascular disease were selected to assess HRQoL using the EQ-5D-5L.\u003c/p\u003e \u003cp\u003eIn this study, CVD status was determined based on participant-reported medical history, with verification against prior medical records when available. Collected CVD categories included (but were not limited to) hypertension, valvular heart disease, heart failure, coronary artery disease/ischemic heart disease, arrhythmias, cerebrovascular disease, and peripheral vascular/venous disease.\u003c/p\u003e \u003cp\u003eInclusion criteria: community-dwelling adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years who had resided in the study areas for \u0026ge;\u0026thinsp;2 years, agreed to participate, and had complete information on age and marital status. Participants were included in the analysis if they were identified as having at least one CVD within the surveyed CVD categories (including hypertension; cerebrovascular disease; localized ischemic heart disease; heart failure; cardiac arrhythmias; valvular heart disease; and peripheral/venous vascular disease) and had available EQ-5D-5L data.\u003c/p\u003e \u003cp\u003eExclusion criteria: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) refusal to participate or withdrawal during the survey; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) inability to complete the interview due to severe illness or communication/cognitive limitations at the time of data collection; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) missing core information required for analyses aligned with the study objectives.\u003c/p\u003e\n\u003ch3\u003eSampling and participant recruitment\u003c/h3\u003e\n\u003cp\u003eA multistage sampling strategy was applied across the eight provinces/cities. In each study site, administrative units (districts/communes/wards) were selected according to the local sampling plan. At the commune/ward level, the research team worked with local health facilities and authorities to compile lists of community-dwelling older adults and performed systematic random sampling to invite eligible individuals. Selected individuals were approached, provided with study information and objectives, and asked to sign informed consent prior to data collection.\u003c/p\u003e \u003cp\u003eParticipants received an explanation of the study objectives and provided consent in accordance with applicable regulations, after which they were interviewed face-to-face using a standardized questionnaire. During data collection, interviewers checked questionnaire completeness and documented non-participation or non-completion to support control of selection bias.\u003c/p\u003e \u003cp\u003eFor Stage 2, from the roster of older adults with CVD identified in Stage 1, systematic random sampling was again applied (based on sample allocation by province/city) to recruit a sufficient number of participants for HRQoL assessment.\u003c/p\u003e\n\u003ch3\u003eData collection procedures and quality control\u003c/h3\u003e\n\u003cp\u003eData were collected through face-to-face interviews with participants in the community following a standardized and uniform protocol across study sites. The data-collection instrument consisted of a structured questionnaire with four main components: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) sociodemographic characteristics; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) morbidity status, including cardiovascular diseases; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) health behaviors and selected related factors; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) assessment of health-related quality of life (HRQoL) using the EQ-5D-5L (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrior to field implementation, the research team conducted interviewer training covering the study objectives, interviewing techniques, standardized administration of questions, questionnaire completion procedures, and principles of confidentiality and research ethics. During data collection, interviewers reviewed questionnaires immediately after each interview to minimize missing data and data-entry errors (e.g., skipped items, incorrect coding, or inconsistent recording across sections).\u003c/p\u003e \u003cp\u003eCollected data were cleaned and verified before analysis. The research team performed range checks and consistency checks to detect out-of-range values, implausible response patterns, and incomplete records. Identified discrepancies (if any) were cross-checked against the original forms and/or verified with the field investigators responsible for the site, and then corrected according to the established quality-control procedures. In addition, to minimize measurement error, the team applied standardized supervision and site-level monitoring during data collection, particularly for HRQoL assessment items, to ensure comparability across study locations.\u003c/p\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was health-related quality of life (HRQoL), measured using the EQ-5D-5L descriptive system comprising five domains: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. EQ-5D-5L health states were converted into EQ-5D-5L index scores; this index served as the key outcome variable for statistical analyses and was calculated using the Vietnamese value set (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Independent variables were collected and categorized based on the study questionnaire, including:\u003c/p\u003e \u003cp\u003e(a) Sociodemographic characteristics: age group (60\u0026ndash;69, 70\u0026ndash;79, \u0026ge;\u0026thinsp;80 years), sex (male/female), educational level (no formal schooling, primary, lower secondary/upper secondary, college/intermediate, postgraduate), personal economic status (financially dependent vs having income), household economic status (poor vs non-poor), place of residence (rural vs urban), and social participation (participation vs non-participation in social activities).\u003c/p\u003e\u003cp\u003e(b) Morbidity and treatment-related characteristics: multimorbidity status (1 condition, 2\u0026ndash;3 conditions, \u0026ge;\u0026thinsp;4 conditions), duration of CVD (\u0026lt;\u0026thinsp;2 years; 2\u0026ndash;5 years; 6\u0026ndash;10 years; \u0026gt;10 years), and number of medications used (0, 1\u0026ndash;2, \u0026ge;\u0026thinsp;3). The presence of additional physician-diagnosed conditions (yes/no) was also recorded, including diagnosis of coronary artery disease/ischemic heart disease and assessment of hypertension status (previously diagnosed and/or currently diagnosed). Cardiovascular diagnoses (yes/no) recorded included hypertension, cerebrovascular disease, localized ischemic heart disease, heart failure, arrhythmia, valvular heart disease, and peripheral/venous vascular disease.\u003c/p\u003e \u003cp\u003e(c) Health behaviors and social engagement: medication adherence (adherent/non-adherent), smoking (current smoker/non-smoker), alcohol use (current drinker/non-drinker), physical activity (inactive; \u0026lt;150 minutes/week; \u0026ge;150 minutes/week, based on WHO recommendations for moderate-intensity physical activity among older adults) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and social activity participation (yes/no) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFollowing data collection, completeness and internal consistency were assessed prior to data entry and analysis. Range and logic checks were performed to identify out-of-range values, missing key variables, and implausible combinations. Detected errors were cross-checked against paper questionnaires and/or verified with site investigators and corrected in accordance with the quality-control process.\u003c/p\u003e \u003cp\u003eAnalyses were conducted among community-dwelling older adults with CVDs who had HRQoL data available. Statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA).\u003c/p\u003e \u003cp\u003eCategorical variables were summarized as frequencies and percentages. Continuous variables were described using mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for approximately normally distributed data; otherwise, medians and interquartile ranges (IQRs) or ranges (minimum\u0026ndash;maximum) were reported. HRQoL was primarily summarized using the EQ-5D-5L index score.\u003c/p\u003e \u003cp\u003eTo compare EQ-5D-5L index scores across groups defined by sociodemographic, morbidity-related, and behavioral characteristics, appropriate inferential tests were applied depending on distributional assumptions: independent-samples t-test/one-way ANOVA for normally distributed outcomes with homogeneous variances; or non-parametric tests (Mann\u0026ndash;Whitney U for two groups and Kruskal\u0026ndash;Wallis for three or more groups) when normality assumptions were not met. For categorical variables, between-group comparisons were conducted using the Chi-square test (or Fisher\u0026rsquo;s exact test, as appropriate).\u003c/p\u003e \u003cp\u003eTo identify independent factors associated with HRQoL, a multivariable Generalized Linear Model (GLM) was fitted with the EQ-5D-5L index score as the dependent variable and sociodemographic, morbidity-related, and behavioral variables as predictors. Results are presented as regression coefficients (β) with 95% confidence intervals estimated using bootstrapping, and two-sided p-values; statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn Stage 1, the study surveyed 6,203 community-dwelling older adults, of whom 3,753 were identified as having cardiovascular disease (60.5%). In Stage 2 (HRQoL assessment), 2,330 older adults with cardiovascular disease were included in the analysis (62.1% of CVD cases; 37.6% of the overall sample). The sample was stratified by province/city to ensure adequate numbers for description and comparisons. The Stage 1 and Stage 2 sample sizes by site were as follows: Ha Giang (700; 264), Hanoi (1,001; 373), Thai Binh (700; 264), Nghe An (700; 264), Dak Lak (700; 264), Ho Chi Minh City (1,002; 373), Dong Nai (700; 264), and Can Tho (700; 264).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes baseline characteristics of 2,330 community-dwelling older adults with cardiovascular diseases. Participants were predominantly aged 60\u0026ndash;69 years (42.2%), with comparable proportions of men and women (49.7% vs. 50.3%). Nearly half had intermediate/college education (49.5%), while 26.6% had university/postgraduate education; most reported personal income (81.0%) and household economic conditions of \u0026ldquo;adequate or better\u0026rdquo; (80.1%). Clinically, multimorbidity was common (2\u0026ndash;3 conditions: 38.8%; \u0026ge;4: 27.5%), and CVD duration was most frequently 2\u0026ndash;5 years (47.8%). Medication use varied, with 32.3% using\u0026thinsp;\u0026ge;\u0026thinsp;4 drugs and 30.4% not using medications. Hypertension was the most prevalent diagnosis (77.2%), followed by cerebrovascular disease (16.2%) and localized ischemic heart disease (15.8%). Regarding behaviors, 43.6% were current smokers and 36.6% reported alcohol/beer use; half were physically inactive (50.0%), only 13.5% achieved\u0026thinsp;\u0026ge;\u0026thinsp;150 minutes/week, and social participation was low (20.3%).\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\u003eBaseline characteristics of community-dwelling older adults with cardiovascular diseases (N\u0026thinsp;=\u0026thinsp;2,330)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo schooling/Primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVocational/College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity/Postgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonal income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHas income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo income/Not working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpouse living apart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated/Divorced/Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of comorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of medications currently used\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension diagnosis and treatment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed and treated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot diagnosed/no hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiovascular diagnoses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValvular heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaricose veins (lower limb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth behaviors and social participation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;150 min/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;150 min/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParticipation in social activities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the distribution across the five EQ-5D-5L domains in older adults with CVDs (n\u0026thinsp;=\u0026thinsp;2,330). In the domains of mobility, self-care, and usual activities, most participants reported no problems (Level 1), with proportions of 71.5%, 78.0%, and 78.2%, respectively; the proportions reporting problems (Levels 2\u0026ndash;4) were 28.4%, 22.0%, and 21.8%. In contrast, the pain/discomfort domain showed a very high prevalence of problems (91.8%), primarily at Level 2 (57.6%) and Level 3 (29.8%), whereas Level 1 accounted for only 8.2%. For anxiety/depression, Level 1 was not observed (0.0%); most participants were classified as Level 3 (69.7%) and Level 4 (20.8%). No cases were recorded at Level 5 in any domain.\u003c/p\u003e \u003cp\u003eThe overall mean EQ-5D-5L index score for the study sample was 0.7175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1468 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Across diagnostic groups, valvular heart disease had the highest mean score (0.7482\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1417), whereas peripheral/venous vascular disease showed the lowest (0.6552\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1394). Participants with localized ischemic heart disease also had a relatively low mean score (0.6936\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1639). The remaining conditions (hypertension, cerebrovascular disease, heart failure, and arrhythmia) exhibited similar mean index scores, ranging from 0.7090 to 0.7159.\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\u003eEQ-5D-5L index scores among older adults with different cardiovascular conditions (n\u0026thinsp;=\u0026thinsp;2,330)\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=\"char\" char=\".\" 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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (n\u0026thinsp;=\u0026thinsp;2,330)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\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 \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1492\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalized ischemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1530\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac arrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValvular heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral/venous vascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that EQ-5D-5L index scores varied across selected sociodemographic characteristics among older adults with cardiovascular diseases. No statistically significant differences in EQ-5D-5L index scores were observed by age group (p\u0026thinsp;=\u0026thinsp;0.736) or sex (p\u0026thinsp;=\u0026thinsp;0.442). In contrast, educational attainment was significantly associated with EQ-5D-5L index scores (p\u0026thinsp;=\u0026thinsp;0.001), with higher mean scores generally observed in groups with higher education compared with those with lower education. No significant differences were found according to personal economic status, household economic status, or marital status (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\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\u003e\u003cb\u003eEQ-5D-5L index scores by sociodemographic characteristics among older adults with cardiovascular diseases (n\u0026thinsp;=\u0026thinsp;2,330)\u003c/b\u003e\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=\"char\" char=\".\" 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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (n\u0026thinsp;=\u0026thinsp;2,330)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEQ-5D-5L index\u003c/p\u003e \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(Min\u0026ndash;Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7200\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.32\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7144\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.32\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7171\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7448 (0.32\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7198\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.32\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7151\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.32\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo schooling/primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7003\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7448 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower/upper secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.6931\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7448 (0.3187\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate/college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7258\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.4895\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity/postgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7205\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonal economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaving income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7195\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.3186\u0026ndash;0.8874)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo income/unemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7088\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7448 (0.3777\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7097\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7448 (0.3778\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate or better\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7194\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7184\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried but not cohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7310\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle/divorced/widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.7091\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7608 (0.3187\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that EQ-5D-5L index scores differed significantly across several morbidity-related and behavioral characteristics. EQ-5D-5L index scores declined markedly as the number of comorbid conditions increased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001): the highest mean score was observed among those with one condition (0.8103\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0666), whereas the lowest was found in those with \u0026ge;\u0026thinsp;4 conditions (0.5797\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1408). Similarly, EQ-5D-5L index scores decreased substantially with longer disease duration (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), from 0.8896\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0101 (\u0026lt;\u0026thinsp;2 years) to 0.4201\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0517 (\u0026gt;\u0026thinsp;10 years). The EQ-5D-5L index also differed by the number of medications currently used (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with mean scores ranging from 0.7004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1597 (no medication) to 0.7458\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1232 (one medication). Participants with a prior diagnosis and treatment of hypertension had a lower mean EQ-5D-5L index than those without such diagnosis (0.7107\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1492 vs. 0.7404\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1363; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were observed by smoking status (p\u0026thinsp;=\u0026thinsp;0.533) or alcohol use (p\u0026thinsp;=\u0026thinsp;0.992). In contrast, physical activity was significantly associated with EQ-5D-5L index scores (p\u0026thinsp;=\u0026thinsp;0.010), with higher scores among those achieving\u0026thinsp;\u0026ge;\u0026thinsp;150 minutes/week compared with inactive individuals (0.7338\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1504 vs. 0.7088\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1444). Additionally, participants who engaged in social activities had higher EQ-5D-5L index scores than those who did not (0.7357\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1308 vs. 0.7128\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1503; p\u0026thinsp;=\u0026thinsp;0.002).\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\u003eEQ-5D-5L index scores among older adults with cardiovascular diseases by morbidity-related characteristics and health behaviors (n\u0026thinsp;=\u0026thinsp;2,330)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNumber (n\u0026thinsp;=\u0026thinsp;2,330)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEQ-5D-5L index (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMedian (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbid conditions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8103\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.4366\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7342\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5797\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5739 (0.187\u0026ndash;0.8523)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of CVD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8896\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8875 (0.8875\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8086\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.7571\u0026ndash;0.8523)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e31.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6563\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6766 (0.4925\u0026ndash;0.7448)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4201\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4366 (0.3187\u0026ndash;0.4895)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of medications currently used\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7458\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7184\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7210\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3817\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreviously diagnosed with hypertension and treated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7107\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0. 8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot previously diagnosed / not currently diagnosed with hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7404\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.4243\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7196\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.9263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.533\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7158\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.9263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7841 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e63.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7174\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.4243\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7088\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7448 (0.3187\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;150 minutes/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7233\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;150 minutes/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7338\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3232\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParticipation in social activities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7357\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3232\u0026ndash;0.8875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not participate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7128\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8035 (0.3187\u0026ndash;0.9362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the multivariable GLM with bootstrap-based confidence intervals (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), EQ-5D-5L index scores were significantly associated with educational attainment, personal and household economic status, multimorbidity, disease duration, number of medications used, and smoking status. Compared with participants with \u0026lt;\u0026thinsp;2 years of disease duration, those with longer duration had progressively lower EQ-5D-5L index scores (2\u0026ndash;5 years: β = \u0026minus;0.080; 6\u0026ndash;10 years: β = \u0026minus;0.221; \u0026gt;10 years: β = \u0026minus;0.450; all p\u0026thinsp;=\u0026thinsp;0.001). Relative to participants with one comorbid condition, those with \u0026ge;\u0026thinsp;4 comorbidities had lower EQ-5D-5L index scores (β = \u0026minus;0.028; p\u0026thinsp;=\u0026thinsp;0.001), whereas the 2\u0026ndash;3 comorbidity group did not differ significantly (p\u0026thinsp;=\u0026thinsp;0.823). Participants from poor households had lower EQ-5D-5L index scores than those with adequate household economic conditions (β = \u0026minus;0.028; p\u0026thinsp;=\u0026thinsp;0.004). Regarding education, lower/upper secondary education was associated with lower EQ-5D-5L index scores compared with college/technical school or higher (β = \u0026minus;0.013; p\u0026thinsp;=\u0026thinsp;0.001). In terms of medication use, using one medication was associated with a higher EQ-5D-5L index score compared with no medication use (β\u0026thinsp;=\u0026thinsp;0.008; p\u0026thinsp;=\u0026thinsp;0.013), while\u0026thinsp;\u0026ge;\u0026thinsp;4 medications showed a borderline association (p\u0026thinsp;=\u0026thinsp;0.051). Current smokers had higher EQ-5D-5L index scores than non-smokers (β\u0026thinsp;=\u0026thinsp;0.007; p\u0026thinsp;=\u0026thinsp;0.007). No statistically significant associations were observed for age group, sex, marital status, alcohol/beer use, physical activity level, or participation in social activities (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with EQ-5D-5L index scores in the multivariable Generalized Linear Model (GLM) (n\u0026thinsp;=\u0026thinsp;2,330)\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\u003eComparison group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted β\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI (Bootstrap)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep (2-tailed)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.004, 0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.710\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\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.001, 0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\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\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.006, 0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.452\u003c/p\u003e \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\u003eCollege/technical school / Postgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eNo schooling/primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.007, 0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.758\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\u003eLower/upper secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.022, -0.004\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\u003eIntermediate/college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.007, 0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePersonal economic status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHaving income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinancially dependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010, 0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHousehold economic status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate or better\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.047, -0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\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\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eSingle/divorced/widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.001, 0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\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 but not cohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.007, 0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of comorbid conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.036, -0.019\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\u003e2\u0026ndash;3 conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.003, 0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuration of disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.459, -0.441\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\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.228, -0.213\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\u003e2\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.082, -0.077\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of medications used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000, 0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\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\u003e1 medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002, 0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\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\u003e2\u0026ndash;3 medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.009, 0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.437\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\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002, 0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol/beer use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCurrent drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.005, 0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;150 minutes/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.002, 0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.325\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;150 minutes/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.012, 0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in social activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eDid not participate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.009, 0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study provides large-scale, multicenter evidence on health-related quality of life (HRQoL) among community-dwelling older adults with cardiovascular diseases (CVDs) in Vietnam, assessed using the EQ-5D-5L and converted using the Vietnamese value set. The EQ-5D-5L is a five-level version developed to improve sensitivity and reduce ceiling effects compared with the EQ-5D-3L, and the use of a Vietnam-specific value set facilitates interpretation that is appropriate to the Vietnamese population context (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mean EQ-5D-5L index score was 0.7175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1468, indicating that overall HRQoL among older adults with CVDs was substantially lower than reference values reported for the general Vietnamese population, where population-based studies commonly report a mean score of approximately 0.91 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This finding is consistent with the clinical reality that CVDs in older adults often follow a chronic course, limit activity, increase physical symptoms, and impose sustained psychological burden, collectively reflected in markedly reduced HRQoL in this group compared with the general population in Vietnam.\u003c/p\u003e \u003cp\u003eA notable contribution of this study is the domain-specific distribution of problems on the EQ-5D-5L. While most participants reported no problems in mobility, self-care, and usual activities, the prevalence of problems was very high for pain/discomfort, and anxiety/depression was reported by nearly all participants. From both clinical and public health perspectives, these findings suggest that among community-dwelling older adults with CVDs in Vietnam, symptom burden (particularly pain/discomfort) and psychological burden may be key drivers of reduced HRQoL, potentially more prominent than functional limitations in mobility or self-care. A study in Hong Kong (China) reported a mean score of 0.85 among patients with hypertension, lower than the general population (0.92). Recent studies also suggest that hypertension alone may not markedly reduce quality of life; however, HRQoL declines substantially when cardiovascular complications occur (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In Vietnam, studies among older adults with CVDs have similarly shown that pain/discomfort is among the most frequently affected EQ-5D domains, and that socioeconomic factors and multimorbidity play important roles in HRQoL (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Nevertheless, the very high level of problems in the anxiety/depression domain observed in our study is distinctive. This may reflect a true burden of mental health problems among older adults with CVDs in Vietnam, particularly in the context of chronic disease, loneliness, and social isolation; however, it may also relate to how items were understood/interpreted and to the standardization of interview administration. Therefore, future studies should incorporate specific depression/anxiety instruments or qualitative approaches to triangulate and clarify the nature of this finding.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with HRQoL\u003c/h2\u003e \u003cp\u003eIn the univariable analyses, HRQoL was significantly associated with multiple sociodemographic characteristics (age, sex, educational attainment, marital status), morbidity- and treatment-related characteristics (number of comorbid conditions, disease duration, number of medications used), and health behaviors (smoking, alcohol/beer use, physical activity, and participation in social activities). However, in the multivariable model (GLM), only a subset of variables remained statistically significant after adjustment. This pattern may be explained by: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the interrelationships among independent variables (e.g., age, education, economic status, and morbidity burden); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the possibility that lifestyle behaviors (particularly physical activity) may influence HRQoL through intermediary pathways such as reduced pain, improved function, and better mental well-being; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) collinearity among morbidity- and treatment-related variables (disease duration, number of comorbid conditions, and number of medications).\u003c/p\u003e \u003cp\u003eTwo findings are particularly noteworthy. First, HRQoL decreased markedly as disease duration increased, and second, a higher morbidity burden, especially\u0026thinsp;\u0026ge;\u0026thinsp;4 comorbid conditions, was independently associated with lower HRQoL. Relative to those with disease duration\u0026thinsp;\u0026lt;\u0026thinsp;2 years, EQ-5D-5L index scores were lower by 0.080, 0.221, and 0.450 in the 2\u0026ndash;5 years, 6\u0026ndash;10 years, and \u0026gt;\u0026thinsp;10 years groups, respectively. These results align with the clinical trajectory of CVDs in older adults: longer disease duration typically entails a more chronic course, accumulation of complications, progressive functional decline, and increased treatment burden, all of which may adversely affect HRQoL across EQ-5D domains, particularly pain/discomfort and anxiety/depression (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In addition, multimorbidity is a common and increasingly recognized determinant of HRQoL. The multivariable model showed progressively lower HRQoL with increasing numbers of comorbid conditions; compared with participants with one condition, those with 2\u0026ndash;3 and \u0026ge;\u0026thinsp;4 conditions had substantially lower scores. This is consistent with evidence that older adults with multimorbidity often experience overlapping symptoms and cumulative limitations, which together contribute to declines in physical function, pain, and mental health (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding socioeconomic factors, education remained significant after adjustment. Compared with the highest educational group (college/technical school or higher), lower educational attainment was associated with significantly lower HRQoL (e.g., lower/upper secondary school). This finding is plausible because education is closely linked to health literacy, access to health services, treatment adherence, and social resources (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In contrast, marital status did not remain significant in the fully adjusted model. Compared with those living with a spouse, being single/divorced/widowed was associated with lower HRQoL in unadjusted analyses, which is consistent with a Hong Kong study by Xu et al. (2017) reporting higher mean EQ-5D-5L scores among older adults living with family than among those living alone or with a spouse; that study suggested that loneliness and depressive symptoms may contribute to poorer HRQoL (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Our findings are generally consistent with Vietnamese population evidence highlighting the role of social support in adaptation to chronic illness and symptom control (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Nevertheless, in our community-based sample in Vietnam, the effect of marital status was attenuated after controlling for household economic factors and family structure, suggesting that marital status may be a proxy for broader social and economic resources (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relationship between the number of medications used and HRQoL in the multivariable model suggested that the group using one medication differed significantly from the group using no medication, whereas the \u0026ge;\u0026thinsp;4 medications group showed a non-significant trend toward lower HRQoL. Conceptually, medication use may reflect both disease severity and treatment burden, including side effects and regimen complexity; prior studies among older adults have reported that polypharmacy is associated with lower HRQoL (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Therefore, in practice, studies should further characterize medication patterns and appropriateness, and interventions should emphasize regular medication review and optimization, particularly in older adults with multimorbidity, to support improvements in HRQoL.\u003c/p\u003e \u003cp\u003eIn our sample, physical inactivity was common, the proportion meeting\u0026thinsp;\u0026ge;\u0026thinsp;150 minutes/week was low, and social participation was limited. In univariable analyses, both physical activity and social participation were associated with HRQoL. However, after adjustment for sociodemographic and morbidity-related factors (notably disease duration and multimorbidity), these variables were no longer statistically significant, suggesting that their independent effects may be partly mediated by disease burden. This may be interpreted as physical activity and social participation influencing HRQoL through improvements in function, pain reduction, and mental well-being; when models adjust for morbidity burden, the remaining independent association may be diminished. Nonetheless, from a practical standpoint, physical activity remains a key intervention target in older adults. WHO recommends reducing sedentary time and encouraging appropriate levels of activity tailored to age and health status (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Moreover, evidence synthesis indicates that physical activity interventions in older adults, especially those with heart failure\u0026mdash;can improve physical function and quality of life (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, our study found that smoking was associated with higher HRQoL in the multivariable model. This contrasts with most studies reporting that smoking is associated with lower HRQoL (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). A possible explanation is the cross-sectional nature of our study and potential residual confounding: current smokers in this sample may have had lower measured morbidity severity, reflecting survival bias (healthier smokers surviving to older age), or reverse causation whereby more severe patients were more likely to quit smoking and thus were classified as non-smokers, leading to apparently higher HRQoL among current smokers. Future studies should refine smoking classification (never/former/current), capture smoking duration and intensity, and explore these hypotheses in longitudinal designs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImplications\u003c/h2\u003e \u003cp\u003eBased on the key findings, intervention priorities should focus on subgroups at higher risk of poor HRQoL, including older adults with multimorbidity, longer disease duration, lower educational attainment, and limited family support (e.g., single/divorced/widowed). Beyond optimizing cardiovascular treatment, the EQ-5D-5L domain profile suggests the need for integrated approaches that include chronic pain management, mental health screening and interventions, and rehabilitation or programs to maintain mobility and functional capacity. These directions are consistent with recommendations for physical activity in older adults, including targets of 150\u0026ndash;300 minutes/week of moderate-intensity activity combined with muscle-strengthening and balance-enhancing exercises (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis study has several notable strengths, including a large sample size, the use of the standardized EQ-5D-5L instrument with conversion based on the Vietnamese value set, and analyses of both the overall index score and domain-specific health dimensions, which enhance interpretability and facilitate international comparisons.\u003c/p\u003e \u003cp\u003eHowever, the study also has limitations typical of cross-sectional descriptive designs, including the inability to infer causality, and potential recall bias and residual confounding. Several lifestyle variables (smoking, alcohol/beer use, physical activity, and social participation) were self-reported, which may increase the risk of misclassification. In addition, incomplete measurement of disease severity and complications (e.g., heart failure functional class, symptom control, or recent hospitalization events) could have influenced the findings. Therefore, longitudinal studies and risk stratification analyses, particularly those incorporating disease severity, are needed to validate these associations and clarify the influence of these factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study indicates that HRQoL among community-dwelling older adults with cardiovascular diseases in Vietnam is reduced, with commonly affected domains including pain/discomfort, anxiety/depression, and mobility limitations. Lower HRQoL was consistently observed among individuals with a higher disease burden (multimorbidity and longer disease duration) and among socioeconomically vulnerable groups (lower education, economic hardship, and limited family support). HRQoL was also related to treatment characteristics such as the number of medications used. These findings underscore the need to implement comprehensive and integrated community-based CVD management models for older adults, prioritizing symptom control, mental health screening and support, maintenance/rehabilitation of mobility, and optimization of medication use, especially for high-risk groups.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCVDs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecardiovascular diseases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEQ-5D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuroQol 5-dimension questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEQ-5D-3L\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e3-level version of the EuroQol 5-dimension questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEQ-5D-5L\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-level version of the EuroQol 5-dimension questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGLM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneralized Linear Model\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHRQoL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehealth-related quality of life\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003e \u003cem\u003eConflict of Interest\u003c/em\u003e:\u003c/h2\u003e \u003cp\u003eThe authors declared no conflicts of interest with respect to the authorship and/or publication of this article.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study was funded by the Ministry of Science and Technology of Vietnam and constitutes part of the national-level project entitled \u0026ldquo;Assessment of the current status and quality of life of older adults with cardiovascular diseases and the effectiveness of selected treatment techniques in Vietnam\u0026rdquo; (Project code: ĐTĐL.CN.52/21).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceived of the study: C.L.M, T.L.D, C.N.V.; Participated in its design and data analysis and statistics: T.L.D, S.N.T.T, C.L.M, T.Q.T, T.N.H; Helped to draft the manuscript: C.N.V, T.N.H, S.N.T.T, T.Q.T. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the local health authorities and staff at the study sites for their support with participant recruitment and data collection. We are also grateful to all participants for their time and valuable contributions to this research\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePrince MJ, Wu F, Guo Y, Robledo LMG, O'Donnell M, Sullivan R, et al. The burden of disease in older people and implications for health policy and practice. lancet. 2015;385(9967):549\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXi J-Y, Liang B-H, Zhang W-J, Yan B, Dong H, Chen Y-Y, et al. 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Examining the health-related quality of life using EQ-5D-5L in patients with four kinds of chronic diseases from specialist outpatient clinics in Hong Kong SAR, China. Patient Prefer Adherence. 2017:1565\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoi LV, Chuc NT, Lindholm L. Health-related quality of life, and its determinants, among older people in rural Vietnam. BMC Public Health. 2010;10(1):549.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Wilder L, Devleesschauwer B, Clays E, Pype P, Vandepitte S, De Smedt D. Polypharmacy and health-related quality of life/psychological distress among patients with chronic disease. Prev Chronic Dis. 2022;19:E50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontiel-Luque A, N\u0026uacute;\u0026ntilde;ez-Montenegro AJ, Mart\u0026iacute;n-Aurioles E, Canca-S\u0026aacute;nchez JC, Toro-Toro MC, Gonz\u0026aacute;lez-Correa JA, et al. Medication-related factors associated with health-related quality of life in patients older than 65 years with polypharmacy. PLoS ONE. 2017;12(2):e0171320.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRacey M, Ali MU, Sherifali D, Fitzpatrick-Lewis D, Lewis R, Jovkovic M, et al. Effectiveness of physical activity interventions in older adults with frailty or prefrailty: a systematic review and meta-analysis. Can Med Association Open Access J. 2021;9(3):E728\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVogl M, Wenig CM, Leidl R, Pokhrel S. Smoking and health-related quality of life in English general population: implications for economic evaluations. BMC Public Health. 2012;12(1):203.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Quality of life, Cardiovascular diseases, Aged, Multimorbidity, Vietnam","lastPublishedDoi":"10.21203/rs.3.rs-9092933/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9092933/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo describe health-related quality of life (HRQoL) and to examine factors associated with HRQoL among community-dwelling older adults with cardiovascular diseases (CVDs) in Vietnam.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a multicenter descriptive cross-sectional study with analytical components in eight provinces/cities (Ha Giang, Thai Binh, Nghe An, Dak Lak, Dong Nai, Can Tho, Hanoi, and Ho Chi Minh City) from October 2021 to September 2025. Participants were adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years who were identified as having at least one cardiovascular disease based on self-reported medical history and verification with medical records (when available). Data were collected through face-to-face interviews using a structured questionnaire and the EQ-5D-5L. EQ-5D-5L index scores were derived using the Vietnamese value set. Descriptive statistics were presented as frequencies/proportions and mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; group comparisons used appropriate statistical tests. Independent factors associated with HRQoL were identified using a multivariable Generalized Linear Model (GLM), with 95% confidence intervals estimated via bootstrapping.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 2,330 older adults with CVDs were included in the analysis. The mean EQ-5D-5L index score was 0.7175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1468. Across CVD subgroups, mean scores ranged from 0.6552\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1394 (peripheral/venous vascular disease) to 0.7482\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1417 (valvular heart disease). In the multivariable GLM, lower HRQoL was independently associated with poor household economic status (β = \u0026minus;0.028; 95% CI: \u0026minus;0.047 to \u0026minus;\u0026thinsp;0.009; p\u0026thinsp;=\u0026thinsp;0.004), multimorbidity with \u0026ge;\u0026thinsp;4 comorbid conditions (β = \u0026minus;0.028; 95% CI: \u0026minus;0.036 to \u0026minus;\u0026thinsp;0.019; p\u0026thinsp;=\u0026thinsp;0.001), and increasing disease duration (2\u0026ndash;5 years: β = \u0026minus;0.080; 95% CI: \u0026minus;0.082 to \u0026minus;\u0026thinsp;0.077; p\u0026thinsp;=\u0026thinsp;0.001; 6\u0026ndash;10 years: β = \u0026minus;0.221; 95% CI: \u0026minus;0.228 to \u0026minus;\u0026thinsp;0.213; p\u0026thinsp;=\u0026thinsp;0.001; \u0026gt;10 years: β = \u0026minus;0.450; 95% CI: \u0026minus;0.459 to \u0026minus;\u0026thinsp;0.441; p\u0026thinsp;=\u0026thinsp;0.001). Lower secondary/high school education was also associated with lower HRQoL compared with university/postgraduate education (β = \u0026minus;0.013; 95% CI: \u0026minus;0.022 to \u0026minus;\u0026thinsp;0.004; p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHRQoL among community-dwelling older adults with CVDs in Vietnam is reduced, with prominent burdens in pain/discomfort and anxiety/depression. HRQoL is strongly influenced by multimorbidity, longer disease duration, and socioeconomic disadvantage.\u003c/p\u003e","manuscriptTitle":"Health-related quality of life and associated factors among community-dwelling older adults with cardiovascular diseases in Vietnam: a nationwide cross-sectional study using EQ-5D-5L","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 13:05:29","doi":"10.21203/rs.3.rs-9092933/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ecb3d67d-6296-4933-a006-d0f645809472","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T04:10:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 13:05:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9092933","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9092933","identity":"rs-9092933","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}