Next Article in Journal
Quadratus Lumborum Block Versus Transversus Abdominis Plane Block for Postoperative Analgesia After Laparoscopic Colorectal Surgery
Previous Article in Journal
Assessment of the Abnormalities in Chest Computed Tomography and Pulmonary Function Test in Convalescents Six Months After COVID-19
Previous Article in Special Issue
Relationship Between Coronary Collateral Circulation and the Neutrophil-Percentage-to-Albumin Ratio in Patients with Chronic Coronary Syndrome
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Medicina
Volume 61
Issue 5
10.3390/medicina61050824
medicina-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Exploring Factors Affecting Health-Related Quality of Life in Coronary Artery Disease Patients

by
Geetha Kandasamy
1,
Thangamani Subramani
2,*,
Mona Almanasef
1,
Khalid Orayj
1,
Eman Shorog
1,
Asma M. Alshahrani
3,
Tahani S. Alanazi
1 and
Anusha Majeed
2
1
Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha 62521, Saudi Arabia
2
Department of Pharmacy Practice, Grace College of Pharmacy, Palakkad 678004, India
3
Department of Clinical Pharmacy, College of Pharmacy, Shaqra University, Dawadimi 11911, Saudi Arabia
*
Author to whom correspondence should be addressed.
Medicina 2025, 61(5), 824; https://doi.org/10.3390/medicina61050824
Submission received: 8 March 2025 / Revised: 23 April 2025 / Accepted: 24 April 2025 / Published: 29 April 2025
(This article belongs to the Special Issue Advances in Chronic Coronary Syndrome and Coronary Heart Disease)
Versions Notes

Abstract

Background and Objectives: Coronary artery disease (CAD) significantly impacts health-related quality of life (HRQoL), with lifestyle factors and comorbidities influencing various dimensions of well-being. This study aimed to assess HRQoL and its association with sociodemographic and lifestyle factors in CAD patients. Materials and Methods: A cross-sectional study was conducted at the Rajiv Gandhi Co-operative Multispecialty Hospital, South India, from July 2022 to April 2023, where lifestyle factors were assessed, and HRQoL was measured using the EQ-5D-3L. The differences and associations of sociodemographic and lifestyle factors with HRQoL were analyzed using the chi-square test and multivariate regression. Results: A total of 212 CAD patients were included in this study. Female gender and comorbid disease were more likely to be associated with reported problems in mobility (89.7%, 78.8%) and anxiety/depression (97.4%, 92.7%) (p < 0.05). Factors such as age ≥ 50 years, family history of CAD, current smoking, comorbid disease, and a moderate- to high-risk diet significantly influenced anxiety/depression (p < 0.05). Patients with comorbid disease and moderate- to high-risk dietary intake were significantly associated with all five dimensions (p < 0.05). Gender, educational level, alcohol intake, and sleep duration did not show a significant association with all dimensions (p > 0.05). Conclusions: This study found that CAD patients undergoing treatment for secondary prevention exhibited inadequate HRQoL, particularly in terms of mental health. Factors such as comorbid disease and moderate- to high-risk dietary intake were significantly associated with reduced HRQoL. Older age, family history of CAD, current smoking habit, comorbid disease, and a moderate- to high-risk diet were significantly associated with anxiety/depression.

1. Introduction

Coronary artery disease (CAD) is the most prevalent form of cardiovascular disease (CVD) and is one of the primary causes of death, illness, and economic strain globally [1,2,3]. Recent research has shown that individuals with CAD have a significantly higher likelihood of experiencing cognitive impairment compared with healthy individuals of the same age [4,5,6]. Furthermore, the rates of anxiety and depression among heart patients are four times higher (15–20%) than those observed in the general population (5%), which negatively impacts health-related quality of life (HRQoL) and leads to increased morbidity and mortality [7,8,9]. The hallmarks of coronary heart disease (CHD) include the accumulation of cholesterol in the major coronary arteries, which can lead to angina, dyspnoea, fatigue, and myocardial infarction [10].
CHD is one of the most prevalent diseases, constituting a significant global public health concern. It is the leading cause of premature deaths from CVD, alongside stroke [11]. Despite a reduction in the CHD mortality rate over the past 20 years, low- and middle-income countries have experienced an increase in the number of life years lost to premature CHD-related deaths [12]. The World Health Organization (WHO) defines quality of life (QoL) as “an individual’s way of perceiving their life position within the cultural context and value system in which they live, and in relation to the tasks, expectations, and standards determined by environmental conditions” [13,14]. In the context of medicine, studying quality of life involves identifying issues arising from an illness and its treatment, linking these to human activity in physical, mental, and social domains and characterizing a patient’s perceptions of their subjective well-being and health [15,16].
The QoL of individuals with CAD is affected by various factors. Physical symptoms can impair functioning in familial and social contexts, often leading to social isolation [17]. A decline in physical ability can reduce independence, increasing reliance on others. Additionally, mobility limitations due to fatigue, dyspnea, muscle weakness, and poor balance can disrupt daily activities [18]. HRQoL is a multidimensional construct that encompasses an individual’s capacity to engage in daily activities (i.e., functioning), their overall life perspective (i.e., well-being), and their subjective assessment of health condition management. In recent years, HRQoL has emerged as a critical patient-reported outcome measure, providing valuable insights for patient-centered care, informing clinical decision-making, and influencing health policy and reimbursement frameworks [19]. Its integration into healthcare research and practice enhances the understanding of patient experiences and supports the development of targeted interventions to optimize health outcomes [20]. Furthermore, HRQoL has been identified as a significant predictor of mortality, recurrent coronary events, and long-term health prognosis [21]. Emerging evidence suggests that subjective well-being (SWB) should be considered when assessing overall well-being, as it encompasses a broad spectrum of psychological and evaluative dimensions, including emotional responses, domain-specific satisfaction, and global life satisfaction [22]. Given these insights, SWB may represent an additional critical indicator of HRQoL in patients with CHD, providing a more comprehensive assessment of their health status and QoL [23]. The aim of this study was to assess the HRQoL of patients with CAD and their associated lifestyle factors.

2. Materials and Methods

2.1. Study Design and Setting

A cross-sectional study was conducted at the Rajiv Gandhi Co-operative Multispecialty Hospital in Palakkad, Kerala, South India over a period of 8 months, from July 2022 to April 2023.

2.2. Sample Size and Study Criteria

Over an 8-month period, approximately 14 to 15 patients per week visited the cardiology outpatient department, resulting in a total sample of 470 patients. The sample size was determined using the Raosoft online calculator with a 5% margin of error, a 95% confidence level, and a 50% response distribution, yielding a minimum required sample size of 212, which was the total number of patients included in this study. The eligibility criteria required patients to be 18 years or older and to be diagnosed with CAD. Both male and female outpatients were considered, regardless of the presence of comorbidities. The exclusion criteria encompassed patients with severe non-cardiovascular diseases or conditions that could significantly impact life expectancy (e.g., cancer, drug abuse), those with impaired cognitive function, and individuals unwilling to provide informed consent.

2.3. Study Procedure and Data Collection

This study’s population consisted of patients diagnosed with CAD. Signed informed consent was obtained from each patient prior to this study. A predesigned patient data collection form was used to gather the required information. The data collection was divided into three sections: Section 1 included sociodemographic details, such as gender, age, education, occupation, marital status, family history of CAD, type of CAD, and comorbidities. Section 2 included lifestyle factors (exercise, smoking, alcohol consumption, sleep, and diet). The diet section comprised 10 questions assessing dietary habits, including frequency of fried food consumption; daily servings of bread, rice, potatoes, or other starchy foods; daily servings of sweet foods (e.g., cakes, biscuits, chocolate); daily teaspoons of sugar added to hot drinks or food; frequency of fish consumption; daily fruit intake; daily servings of vegetables (excluding potatoes); daily coffee consumption; average soft drink consumption; and daily water intake. These questions were adopted from a cardiovascular risk assessment questionnaire [24], with scores ranging from −10 to 10. Based on the total score, dietary habits were categorized as follows: Low risk: scores from −19 to 6; Medium risk: scores from 7 to 13; and High risk: scores of 14 and above. Section 3 included the assessment of QoL using the EQ-5D-3L questionnaire, which is a widely used tool for evaluating HRQoL. The questionnaire was translated into the local language, Malayalam, with the help of experts. To check reliability, internal consistency was measured using Cronbach’s alpha. The Cronbach’s value for EQ-5D-3L was 0.78.

2.4. Questionnaire and Scorings

The European Quality of Life 5-Dimension 3-Level (EQ-5D-3L) is a standardized instrument for measuring HRQoL [25,26]. HRQoL is measured in terms of five dimensions (5D): mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has three questions. The respondents self-rate their levels of severity for each dimension using the three levels of the EQ-5D-3L: Score 1: indicating no problem; Score 2: indicating some problems; and Score 3: indicating extreme problems.

2.5. Ethical Clearance

Ethical clearance was obtained from the institution’s ethics committee, Grace College of Pharmacy, Palakkad (Approval No: GCP/IEC/112A/2022 dated on 5 July 2022), prior to commencement of this study.

2.6. Statistical Analysis

Data were analyzed using IBM SPSS Statistics for Windows, Version 20.0. Categorical variables were expressed as numbers and percentages. The association of sociodemographic factors, types of CAD and lifestyle risk factors, sleep patterns, and dietary habits with HRQoL were analyzed by using multivariate logistic regression analysis. A p-value of <0.05 was considered statistically significant.

3. Results

This prospective hospital-based study assessed HRQoL and determinants like lifestyle, sleep, and diet in 212 patients with CAD over 9 months. Table 1 represents the sociodemographic and lifestyle factors among CAD patients. The majority of participants, 173 (81.6%), were male, and the minority, 39, were female (18.4%). A large proportion, 177, were aged ≥50 years (83.5%), while 35 (16.5%) were under 50 years. Regarding education, most, 121, had primary education (57.1%), followed by 78 with secondary education or a bachelor’s degree and above (36.8%), and a small number, 13, who were illiterate (6.1%). The majority, 142, were employed (67%), with 70 (33%) being unemployed, retired, or housewives. Most participants, 209, were married (98.6%), and 73 (34.4%) had a family history of CAD. A large number, 151 (71.2%), had comorbid diseases, while 61 (28.8%) did not. Regarding exercise, 129 (60.8%) exercised ≤1 time/week, while 83 (39.2%) exercised ≥2–3 times/week. The majority, 160, had never smoked or were ex-smokers (75.5%) while 52 (24.5%) were current smokers. Alcohol intake was reported by 87 (41.0%); 125 (59.0%) did not consume alcohol. Sleep duration of ≤6 h/night was observed in 143 (67.5%), while 69 (32.5%) slept for >6 h. A larger portion, 151, had moderate-/high-risk dietary habits (71.2%) with 61 (28.8%) having low-risk diets.
Table 2 presents the distribution of EQ-5D-3L questionnaire scores among the study population. Regarding “mobility,” 56 (26.4%) patients reported no problems, 150 (70.8%) had some problems, and 6 (2.8%) were confined to bed. For “self-care,” 156 (73.5%) had no issues, 41 (19.3%) experienced some problems, and 15 (7%) were unable to care for themselves. In terms of “usual activities,” 51 (24%) had no problems, 136 (64.1%) faced some issues, and 25 (11.8%) were unable to perform daily tasks. “Pain/discomfort” was reported by 78 (36.8%), with 134 (63.2%) experiencing no pain, 45 (21.2%) reporting moderate pain, and 33 (15.6%) experiencing extreme pain. Regarding “anxiety/depression,” 28 (13.2%) of CAD patients reported not feeling anxious or depressed, 118 (55.6%) were moderately affected, and 66 (31.1%) experienced extreme anxiety/depression.
Table 3 shows the relationships between sociodemographic and lifestyle factors with EQ-5D-3L domains among CAD patients. Women (89.7%) and patients with comorbid diseases (78.8%) were more likely to report some or extreme problems in the “mobility” dimension (p < 0.05). Men (79.2%), those with a family history of CAD (92.7%), illiterate people (92.3%), and people exercising regularly (≥2–3 times/week) were more likely to report some or extreme problems in “usual activities” (p < 0.05). Patients with primary education (79.3%), without a family history of CAD (78.4%) or comorbid diseases (77.5%) and who were exercising ≥2–3 times/week were more likely to report no problems with the “self-care” (p <0.029) dimension. Patients who exercised ≤1 time/week were more likely to report no pain in the “pain dimension” (p < 0.05). Women (97.4%), patients with comorbid diseases (92.7%), and those who exercised ≥2–3 times/week (94%) were more likely to report some or extreme problems in the “anxiety/depression” dimension (p < 0.05).
Table 4 presents the multivariate logistic regression analysis evaluating the association between sociodemographic and lifestyle factors with HRQoL among CAD patients. Participants aged ≥50 years (OR = 2.091, 95% CI: 1.042–4.192, p = 0.037) and current smokers (OR = 2.045, 95% CI: 1.112–3.978, p = 0.049) were significantly associated with “anxiety/depression.” Unemployed, retired, or housewife participants were significantly associated with usual activities (OR = 2.165, 95% CI: 1.098–4.269, p = 0.027). Participants with a family history of CAD were significantly associated with “pain/discomfort” (OR = 2.045, 95% CI: 1.034–4.051, p = 0.042) and “anxiety/depression” (OR = 2.354, 95% CI: 1.178–4.702, p = 0.019). Participants with comorbid diseases were significantly associated with “mobility” (OR = 2.658, 95% CI: 1.221–5.788, p = 0.014), “self-care” (OR = 2.743, 95% CI: 1.321–5.698, p = 0.012), “usual activities” (OR = 2.512, 95% CI: 1.189–5.312, p = 0.019), “pain/discomfort” (OR = 3.021, 95% CI: 1.578–5.932, p = 0.004) and “anxiety/depression” (OR = 2.895, 95% CI: 1.478–5.672, p = 0.006). A moderate-/high-risk diet was significantly associated with impairments across all EQ-5D-3L domains: “mobility” (OR = 2.341, 95% CI: 1.198–4.571, p = 0.012), “self-care” (OR = 2.198, 95% CI: 1.112–4.319, p = 0.019), “usual activities” (OR = 2.432, 95% CI: 1.231–4.812, p = 0.008), “pain/discomfort” (OR = 2.798, 95% CI: 1.412–5.541, p = 0.002), and “anxiety/depression” (OR = 2.978, 95% CI: 1.578–5.772, p = 0.001). Factors like gender, educational level, alcohol consumption, sleep duration, and exercise showed no significant associations with HRQoL in CAD patients.

4. Discussion

This cross-sectional study aimed to evaluate factors associated with quality of life (QoL) among 212 patients diagnosed with coronary artery disease (CAD) over an 8-month period. In India, CAD has increasingly been recognized as a significant public health concern [27]. The majority of participants in this study were male (81.69%), which aligns with findings from similar studies conducted in Saudi Arabia (79.9% vs. 20.1%) and Iran (68.5% vs. 31.5%) [28,29]. For instance, in a study by Sayad et al., 79.9% of the 498 CAD patients were men, while 20.1% were women [28]. The higher prevalence of CAD among men has been well documented, with the lifetime risk of coronary heart disease (CHD) being 49% for men and 32% for women aged over 40 [30].
This study revealed that CAD was most prevalent in individuals aged over 50, with the mean age of onset in Southeast Asians reported to be 53 [31] as compared with the European average of 63. Hypertension was the most predominant risk factor (76.53%), followed by hyperlipidemia (69.95%) and diabetes mellitus (60.56%), which is consistent with other studies [32]. The relationship between elevated blood pressure and the development of CAD is well understood, as it contributes to the formation of atherosclerotic plaques and worsens coronary perfusion [33].
Regarding lifestyle factors, this study observed low levels of physical activity among patients, with 60.8% reporting ≤1 time/week of exercise. Sedentary behavior is common among CAD patients and includes activities such as watching television, using computers, or working in an office [34,35]. Additionally, 67.4% of patients reported insufficient sleep, with a sleep duration of <6 h per night. Short sleep duration has been associated with subclinical cardiovascular disease and cardiometabolic syndrome, leading to adverse cardiovascular outcomes [36]. These findings emphasize the importance of sleep quality in managing CAD and reducing its impact on QoL [37].
Dietary factors also played a significant role, with 71.2% of participants following a moderate- or high-risk diet. A poor diet is a well-established risk factor for cardiovascular disease and obesity [38]. This study also found that 70.8% of participants reported problems with mobility, 64.1% experienced difficulties with usual activities, and 86.7% experienced moderate to extreme levels of anxiety or depression. This aligns with previous studies that show a high prevalence of mental health issues such as anxiety and depression among CAD patients [39,40], which are significant risk factors for myocardial infarction and mortality [41].
Gender differences were also observed in this study. Female patients and those with comorbid diseases were more likely to report mobility and anxiety/depression issues, suggesting a lower QoL for women compared with men. Previous studies have highlighted the fact that women with CAD report poorer physical functioning and mental health compared with their male counterparts [42,43]. A study involving 8580 patients from 22 European countries, conducted over six months following CHD hospitalization, reported a prevalence of depression ranging from 8.2% to 35.7% in men and 10.3% to 62.5% in women, while anxiety prevalence ranged from 12.0% to 41.8% in men and 21.5% to 63.7% in women [44]. Furthermore, this study found that patients who exercised regularly were more likely to report pain and anxiety/depression, which could be attributed to factors such as intensity of exercise or other lifestyle factors influencing mental health [45,46].
Several sociodemographic and lifestyle factors were found to significantly influence QoL dimensions. For instance, unemployment status, family history of CAD, comorbid diseases, and a moderate- to high-risk diet were significantly associated with physical health issues such as pain and difficulties with usual activities (p < 0.05). Similarly, age ≥ 50 years, family history of CAD, smoking, comorbid conditions, and a poor diet were significantly correlated with anxiety and depression (p < 0.05). The impact of diet on all dimensions of QoL was also observed, which is consistent with findings from studies in Brazil, Norway, and China [47,48,49] but is different from those in Turkey [50] and Indonesia [51].
Our study underscores the importance of considering both physical and mental health factors in the management of CAD patients. Depression and anxiety have been associated with increased cardiac mortality and higher cardiovascular risk [52]. Therefore, addressing mental health in CAD patients should be a priority in clinical settings to improve survival and QoL [53]. The role of diet is particularly crucial, as a healthy diet has been shown to prevent various cardiovascular risk factors, including dyslipidemia, hypertension, and diabetes, while also providing benefits for mental health [54].
Previous research has consistently demonstrated the negative impact of coronary artery disease (CAD) on health-related quality of life (HRQoL), influenced by sociodemographic, clinical, and psychosocial factors [55]. Similarly, the current study confirms that CAD negatively affects QoL. Specifically, factors such as gender, educational level, alcohol intake, and sleep duration were explored. While these factors showed a non-significant association with all dimensions of QoL (p > 0.05), they may still offer valuable insights in future research. Given the findings, it is essential for healthcare providers to evaluate QoL when treating CAD patients. By doing so, providers can tailor their support and treatment strategies to meet individual needs. This study suggests that early evaluation of lifestyle factors, including exercise, diet, and sleep, could be crucial in identifying areas where interventions may be most beneficial. Such evaluations can lead to appropriate referrals and better-targeted support for CAD patients [56].

Limitations

This study has several limitations. First, as a cross-sectional study, it could only identify variables that may impact the QoL of CAD patients but was unable to establish causal relationships. Therefore, a multi-center longitudinal study is needed to determine the long-term benefits of addressing factors associated with lower QoL. Second, data on treatments received for CAD, cardiac function, and other clinical parameters that may influence QoL were not included in this study. Third, the study sample was limited to 212 patients from a single tertiary hospital in Palakkad, which may not be representative of CAD patients across India. The small sample size has been acknowledged as a major limitation. Eating habits and exercise levels may be specific to this regional population and may differ from national averages. Fourth, selection bias may limit the generalizability of the findings to women, as this study included a greater number of men than women. Fifth, using a disease-specific QoL questionnaire, such as the Seattle Angina Questionnaire or the Hamilton Anxiety Rating Scale, would have provided more detailed insights into CAD patients’ QoL. However, due to practical constraints, we opted for the EQ-5D-3L, which provides a broad measure of health status but may not capture disease-specific nuances.

5. Conclusions

This study found that CAD patients undergoing treatment for secondary prevention exhibited inadequate HRQoL. Factors such as being older, a family history of CAD, current smoking, comorbid disease, and a moderate- to high-risk diet were significantly associated with the anxiety/depression dimension. Unemployed status, comorbid disease, family history of CAD and a moderate- to high-risk diet were significantly associated with physical health (problems in usual activities and pain). Moderate to severe anxiety or depression affected 87% of CAD patients. The relationship between anxiety/depression and CAD should be a focus for both physicians and psychiatrists. HRQoL should be regularly monitored and documented as part of treatment strategies and interventions aimed at improving outcomes for CAD patients.

Author Contributions

Conceptualization, G.K., T.S., E.S. and A.M.; Methodology, T.S., M.A. and A.M.; Software, G.K., K.O., E.S., A.M.A. and T.S.A.; Validation, M.A., K.O., E.S. and T.S.A.; Formal analysis, T.S., M.A., K.O., E.S. and A.M.A.; Investigation, T.S., E.S., A.M.A., T.S.A. and A.M.; Resources, K.O. and T.S.A.; Data curation, T.S. and A.M.; Writing—original draft, G.K., M.A., K.O., E.S. and A.M.A.; Writing—review & editing, G.K., T.S., M.A., E.S., T.S.A. and A.M.; Visualization, G.K.; Supervision, A.M.A.; Project administration, M.A., K.O. and A.M.A.; Funding acquisition, G.K. and T.S.A. All authors have read and agreed to the published version of the manuscript.

Funding

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/44/46.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Grace College of Pharmacy, Palakkad (Approval No: GCP/IEC/112A/2022 dated on 5 July 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in this study are included in the article; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. WHO. Cardiovascular Diseases (CVDs); World Health Organization: Geneva, Switzerland, 2021; Available online: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) (accessed on 15 February 2025).
  2. Tsao, C.W.; Aday, A.W.; Almarzooq, Z.I.; Anderson, C.A.; Arora, P.; Avery, C.L.; Baker-Smith, C.M.; Beaton, A.Z.; Boehme, A.K.; Buxton, A.E.; et al. Heart disease and stroke statistics—2023 update: A report from the American Heart Association. Circulation 2023, 147, E93–E621. [Google Scholar] [CrossRef] [PubMed]
  3. Timmis, A.; Vardas, P.; Townsend, N.; Torbica, A.; Katus, H.; De Smedt, D.; Gale, C.P.; Maggioni, A.P.; Petersen, S.E.; Huculeci, R.; et al. European Society of Cardiology: Cardiovascular disease statistics 2021. Eur. Heart J. 2022, 43, 716–799. [Google Scholar] [CrossRef] [PubMed]
  4. Schievink, S.H.; van Boxtel, M.P.; Deckers, K.; van Oostenbrugge, R.J.; Verhey, F.R.; Köhler, S. Cognitive changes in prevalent and incident cardiovascular disease: A 12-year follow-up in the Maastricht Aging Study (MAAS). Eur. Heart J. 2022, 43, e2–e9. [Google Scholar] [CrossRef] [PubMed]
  5. Xie, W.; Zheng, F.; Yan, L.; Zhong, B. Cognitive decline before and after incident coronary events. J. Am. Coll. Cardiol. 2019, 73, 3041–3050. [Google Scholar] [CrossRef]
  6. Saeed, A.; Lopez, O.; Cohen, A.; Reis, S.E. Cardiovascular disease and Alzheimer’s disease: The heart–brain axis. J. Am. Hear. Assoc. 2023, 12, e030780. [Google Scholar] [CrossRef]
  7. Jha, M.K.; Qamar, A.; Vaduganathan, M.; Charney, D.S.; Murrough, J.W. Screening and management of depression in patients with cardiovascular disease: JACC state-of-the-art review. J. Am. Coll. Cardiol. 2019, 73, 1827–1845. [Google Scholar] [CrossRef]
  8. Farquhar, J.M.; Stonerock, G.L.; Blumenthal, J.A. Treatment of anxiety in patients with coronary heart disease: A systematic review. Psychosomatics 2018, 59, 318–332. [Google Scholar] [CrossRef]
  9. Tusek-Bunc, K.; Petek, D. Comorbidities and characteristics of coronary heart disease patients: Their impact on health-related quality of life. Health Qual. Life Outcomes 2016, 14, 159. [Google Scholar] [CrossRef]
  10. Mozaffarian, D.; Benjamin, E.J.; Go, A.S.; Arnett, D.K.; Blaha, M.J.; Cushman, M.; de Ferranti, S.; Després, J.-P.; Fullerton, H.J.; Howard, V.J.; et al. Heart disease and stroke statistics–2015 update: A report from the American Heart Association. Circulation 2015, 131, e29–e322. [Google Scholar] [CrossRef]
  11. Cooper, R.; Cutler, J.; Desvigne-Nickens, P.; Fortmann, S.P.; Friedman, L.; Havlik, R.; Hogelin, G.; Marler, J.; McGovern, P.; Morosco, G.; et al. Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: Findings of the national conference on cardiovascular disease prevention. Circulation 2000, 102, 3137–3147. [Google Scholar] [CrossRef]
  12. Global Burden of Disease Study 2013 Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015, 2015, 743–800. [Google Scholar]
  13. Constitution of the World Health Organization. Agreement concluded by the Governments represented at the International Health Conference and Protocol relating to the International Office of Public Hygiene. J. Laws Device UE Amend. 1948, 61, 477. [Google Scholar]
  14. Definition of Quality of Life. WHOQOL: Measuring Quality of Life. Available online: https://www.who.int/tools/whoqol (accessed on 6 June 2024).
  15. Meeberg, G.A. Quality of life: A concept analysis. J. Adv. Nurs. 1993, 18, 32–38. [Google Scholar] [CrossRef] [PubMed]
  16. Sosnowski, R.; Kulpa, M.; Ziętalewicz, U.; Wolski, J.K.; Nowakowski, R.; Bakuła, R.; Demkow, T. Basic issues concerning health-related quality of life. Cent. Eur. J. Urol. 2017, 70, 206–211. [Google Scholar] [CrossRef]
  17. Valtorta, N.K.; Kanaan, M.; Gilbody, S.; Hanratty, B. Loneliness, social isolation and risk of cardiovascular disease in the English Longitudinal Study of Ageing. Eur. J. Prev. Cardiol. 2018, 25, 1387–1396. [Google Scholar] [CrossRef]
  18. Ishihara, K.; Izawa, K.P.; Kitamura, M.; Shimogai, T.; Kanejima, Y.; Morisawa, T.; Shimizu, I. Influence of mild cognitive impairment on activities of daily living in patients with cardiovascular disease. Heart Vessel. 2019, 34, 1944–1951. [Google Scholar] [CrossRef]
  19. Karimi, M.; Brazier, J. Health, health-related quality of life, and quality of life: What is the difference? Pharmacoeconomics 2016, 34, 645–649. [Google Scholar] [CrossRef] [PubMed]
  20. Calvert, M.; Blazeby, J.; Altman, D.G.; Revicki, D.A.; Brundage, M.D. Reporting of patient-reported outcomes in randomized trials: The CONSORT PRO extension. JAMA 2013, 309, 814–822. [Google Scholar] [CrossRef]
  21. Hofer, S.; Benzer, W.; Oldridge, N. Change in health-related quality of life in patients with coronary artery disease predicts 4-year mortality. Int. J. Cardiol. 2014, 174, 7–12. [Google Scholar] [CrossRef]
  22. Diener, E.; Suh, E.M.; Lucas, R.E.; Smith, H.L. Subjective well-being: Three decades of progress. Psychol. Bull. 1999, 125, 276–302. [Google Scholar] [CrossRef]
  23. Gao, L.; Moodie, M.; Chen, G. Measuring subjective wellbeing in patients with heart disease: Relationship and comparison between health-related quality of life instruments. Qual. Life Res. 2019, 28, 1017–1028. [Google Scholar] [CrossRef] [PubMed]
  24. Casson, M. Cardiovascular Risk Assessment Questionnaire. Published 2015. Available online: https://www.merridycasson.com/wp-content/uploads/2015/03/CDV-Questionnaire.pdf (accessed on 4 May 2024).
  25. EuroQol Group. EuroQol a new facility for the measurement of health-related quality of life. Health Policy 1990, 16, 199–208. [Google Scholar] [CrossRef] [PubMed]
  26. Brooks, R. EuroQol: The current state of play. Health Policy 1996, 37, 53–72. [Google Scholar] [CrossRef] [PubMed]
  27. Krishnan, M.N.; Zachariah, G.; Venugopal, K.; Mohanan, P.P.; Harikrishnan, S.; Sanjay, G.; Jeyaseelan, L.; Thankappan, K.R. Prevalence of coronary artery disease and its risk factors in Kerala, South India: A community-based cross-sectional study. BMC Cardiovasc. Disord. 2016, 16, 12. [Google Scholar] [CrossRef]
  28. Sayed, A.I. Gender Differences in Coronary Artery Disease, Clinical Characteristics, and Angiographic Features in the Jazan Region, Saudi Arabia. Cureus 2022, 14, e30239. [Google Scholar] [CrossRef]
  29. Hosseini, K.; Mortazavi, S.H.; Sadeghian, S.; Ayati, A.; Nalini, M.; Aminorroaya, A.; Tavolinejad, H.; Salarifar, M.; Pourhosseini, H.; Aein, A.; et al. Prevalence and trends of coronary artery disease risk factors and their effect on age of diagnosis in patients with established coronary artery disease: Tehran Heart Center (2005-2015). BMC Cardiovasc. Disord. 2021, 21, 477. [Google Scholar] [CrossRef]
  30. Sanchis-Gomar, F.; Perez-Quilis, C.; Leischik, R.; Lucia, A. Epidemiology of coronary heart disease and acute coronary syndrome. Ann. Transl. Med. 2016, 4, 256. [Google Scholar] [CrossRef]
  31. Aggarwal, A.; Srivastava, S.; Velmurugan, M. Newer perspectives of coronary artery disease in young. World J. Cardiol. 2016, 8, 728–734. [Google Scholar] [CrossRef]
  32. Lu, S.; Bao, M.Y.; Miao, S.M.; Zhang, X.; Jia, Q.-Q.; Jing, S.-Q.; Shan, T.; Wu, X.-H.; Liu, Y. Prevalence of hypertension, diabetes, and dyslipidemia, and their additive effects on myocardial infarction and stroke: A cross-sectional study in Nanjing, China. Ann. Transl. Med. 2019, 7, 436. [Google Scholar] [CrossRef]
  33. Weber, T.; Lang, I.; Zweiker, R.; Horn, S.; Wenzel, R.R.; Watschinger, B.; Slany, J.; Eber, B.; Roithinger, F.X.; Metzler, B. Hypertension and coronary artery disease: Epidemiology, physiology, effects of treatment, and recommendations: A joint scientific statement from the Austrian Society of Cardiology and the Austrian Society of Hypertension. Wien. Klin. Wochenschr. 2016, 128, 467–479. [Google Scholar] [CrossRef]
  34. Vasankari, V.; Halonen, J.; Vasankari, T.; Anttila, V.; Airaksinen, J.; Sievänen, H.; Hartikainen, J. Physical activity and sedentary behaviour in secondary prevention of coronary artery disease: A review. Am. J. Prev. Cardiol. 2021, 5, 100146. [Google Scholar] [CrossRef] [PubMed]
  35. Kim, S.Y. Sedentary Lifestyle and Cardiovascular Health. Korean J. Fam. Med. 2018, 39, 1. [Google Scholar] [CrossRef] [PubMed]
  36. Kim, J.H.; Hayek, S.S.; Ko, Y.-A.; Liu, C.; Tahhan, A.S.; Ali, S.; Alkhoder, A.; Gafeer, M.M.; Choudhary, F.; Bhimani, R.; et al. Sleep Duration and Mortality in Patients With Coronary Artery Disease. Am. J. Cardiol. 2019, 123, 874–881. [Google Scholar] [CrossRef] [PubMed]
  37. Madsen, M.T.; Huang, C.; Zangger, G.; Zwisler, A.D.O.; Gögenur, I. Sleep Disturbances in Patients with Coronary Heart Disease: A Systematic Review. J. Clin. Sleep Med. 2019, 15, 489–504. [Google Scholar] [CrossRef]
  38. Khatun, T.; Maqbool, D.; Ara, F.; Sarker, M.R.; Anwar, K.S.; Hoque, A. Dietary habits of patients with coronary artery disease in a tertiary-care hospital of Bangladesh: A case-controlled study. J. Health Popul. Nutr. 2021, 40, 3, Erratum in J. Health Popul. Nutr. 2021, 40, 18. https://doi.org/10.1186/s41043-021-00243-0. [Google Scholar] [CrossRef]
  39. Nakada, S.; Ward, J.; Strawbridge, R.J.; Welsh, P.; Celis-Morales, C.; Ho, F.K.; Pell, J.P. Anxiety disorder, depression and coronary artery disease: Associations and modification by genetic susceptibility. BMC Med. 2025, 23, 73. [Google Scholar] [CrossRef]
  40. Askin, L.; Uzel, K.E.; Tanrıverdi, O.; Kavalcı, V.; Yavcin, O.; Turkmen, S. The relationship between coronary artery disease and depression and anxiety scores. North. Clin. Istanb. 2020, 7, 523–526. [Google Scholar] [CrossRef]
  41. Shibeshi, W.A.; Young-Xu, Y.; Blatt, C.M. Anxiety worsens prognosis in patients with coronary artery disease. J. Am. Coll. Cardiol. 2007, 49, 2021–2027. [Google Scholar] [CrossRef]
  42. Norris, C.M.; Ghali, W.A.; Galbraith, P.D.; Graham, M.M.; Jensen, L.A.; Knudtson, M.L.; APPROACH Investigators. Women with coronary artery disease report worse health-related quality of life outcomes compared to men. Health Qual. Life Outcomes 2004, 2, 21. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  43. Shad, B.; Ashouri, A.; Hasandokht, T.; Rajati, F.; Salari, A.; Naghshbandi, M.; Mirbolouk, F. Effect of multimorbidity on quality of life in adult with cardiovascular disease: A cross-sectional study. Health Qual. Life Outcomes 2017, 15, 240. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  44. Pająk, A.; Jankowski, P.; Kotseva, K.; Heidrich, J.; de Smedt, D.; De Bacquer, D. Depression, anxiety, and risk factor control in patients after hospitalization for coronary heart disease: The EUROASPIRE III Study. Eur. J. Prev. Cardiol. 2013, 20, 331–340. [Google Scholar] [CrossRef] [PubMed]
  45. Wanjau, M.N.; Möller, H.; Haigh, F.; Milat, A.; Hayek, R.; Lucas, P.; Veerman, J.L. Physical Activity and Depression and Anxiety Disorders: A Systematic Review of Reviews and Assessment of Causality. AJPM Focus 2023, 2, 100074. [Google Scholar] [CrossRef] [PubMed]
  46. Lumley, S.; Yu, D.; Wilkie, R.; Jordan, K.P.; Peat, G. Chronic pain-mental health comorbidity and excess prevalence of health risk behaviours: A cross-sectional study. Prim. Health Care Res. Dev. 2024, 25, e15. [Google Scholar] [CrossRef] [PubMed]
  47. Dias, C.M.C.C.; Macedo, L.B.; Gomes, L.T.J.C.; De Oliveira, P.L.S.P.; Albuquerque, I.V.S.; Lemos, A.Q.; Brasil, C.A.; Prado, E.P.F.; Macedo, P.S.; De Oliveira, F.T.O.; et al. Quality of life of patients after an acute coronary event: Hospital discharge. J. Clin. Med. Res. 2014, 6, 362–368. [Google Scholar] [CrossRef]
  48. Veenstra, M.; Pettersen, K.I.; Rollag, A.; Stavem, K. Association of changes in health-related quality of life in coronary heart disease with coronary procedures and sociodemographic characteristics. Health Qual. Life Outcomes 2004, 2, 56. [Google Scholar] [CrossRef]
  49. Mei, Y.X.; Wu, H.; Zhang, H.Y.; Hou, J.; Zhang, Z.-X.; Liao, W.; Liu, X.-T.; Sang, S.-X.; Mao, Z.-X.; Yang, D.-B.; et al. Health-related quality of life and its related factors in coronary heart disease patients: Results from the Henan Rural Cohort study. Sci. Rep. 2021, 11, 5011. [Google Scholar] [CrossRef]
  50. Demir, S.; Ozer, Z. Evaluation of the quality of life of patients with acute coronary syndrome. J. Cardiovasc. Nurs. 2019, 10, 138–144. [Google Scholar]
  51. Imanuna, M.; Wardani, H.E.; Tama, T.D. Factors related to the quality of life of patients with coronary heart disease at Saifulanwar general hospital, Malang. KnE Life Sci. 2021, 2021, 278–288. [Google Scholar]
  52. Chida, Y.; Steptoe, A. The association of anger and hostility with future coronary heart disease: A meta-analytic review of prospective evidence. J. Am. Coll. Cardiol. 2009, 53, 936–946. [Google Scholar] [CrossRef]
  53. Amin, M.A.; Ahmed, M.; Nahin, S.; Kakoly, N.S. Assessment of Depression and Anxiety Among Admitted People With Heart Disease Conditions: A Cross-Sectional Hospital-Based Study in a Bangladeshi Population During the COVID-19. Front. Psychiatry 2022, 13, 895224. [Google Scholar] [CrossRef]
  54. Tourlouki, E.; Matalas, A.L.; Panagiotakos, D.B. Dietary habits and cardiovascular disease risk in middle-aged and elderly populations: A review of evidence. Clin. Interv. Aging 2009, 4, 319–330. [Google Scholar] [CrossRef] [PubMed]
  55. Muhammad, I.; He, H.; Kowitlawakul, Y.; Wang, W. Narrative review of health-related quality of life and its predictors among patients with coronary heart disease. Int. J. Nurs. Pract. 2016, 22, 4–14. [Google Scholar] [CrossRef] [PubMed]
  56. Gąsecka, A.; Rzepa, B.; Skwarek, A.; Ćwiek, A.; Pluta, K.; Szarpak, Ł.; Jaguszewski, M.J.; Mazurek, T.; Kochman, J.; Opolski, G.; et al. Health-related Quality of Life Increases After First-time Acute Myocardial Infarction: A Population-based Study. Slov. J. Public Health 2021, 61, 24–31. [Google Scholar] [CrossRef] [PubMed]
Table 1. Sociodemographic and lifestyle factors among CAD patients.
Table 1. Sociodemographic and lifestyle factors among CAD patients.
VariablesNumber of Patients
n = 212 (%)
Gender
Male173 (81.60)
Female39 (18.39)
Age group in years
<50 years35 (16.50)
≥50 years177 (83.49)
Education
Illiterate13 (6.13)
Primary Education121 (57.07)
Secondary Education/Bachelor’s Degree and Above78 (36.79)
Occupation
Unemployed/Retired/Housewife70 (33.01)
Employed142 (66.98)
Marital status
Married209 (98.58)
Unmarried4 (1.88)
Family history of CAD
Yes (Father/Mother)73 (34.43)
No139 (65.56)
Comorbid disease
Yes (HT, DM, Hyperlipidemia, hypothyroidism)151 (71.22)
No61 (28.77)
Exercise
≤1 time/week129 (60.84)
≥2–3 times/week83 (39.15)
Smoking
Never/Ex-smoker160 (28.30)
Current smoker52 (24.52)
Alcohol intake
Yes87 (41.03)
No125 (58.96)
Sleep Duration
≤6 h/night143 (67.45)
>6 h69 (32.54)
Dietary habits
Low Risk61 (28.77)
Moderate/High Risk151 (71.22)
HT: Hypertension, DM: Diabetes Mellitus.
Table 2. Distribution based on EQ-5D-3L questionnaire scores among the study population.
Table 2. Distribution based on EQ-5D-3L questionnaire scores among the study population.
DimensionsScoreNumber (%)
(n = 212)
Mobility1 (no problems)56 (26.41)
2 (some problems)150 (70.75)
3 (confined to bed)6 (2.8)
Self-care1 (no problems)156 (73.5)
2 (some problems)41 (19.3)
3 (unable)15 (7)
Usual activities1 (no problems)51 (24)
2 (some problems)136 (64.1)
3 (unable)25 (11.79)
Pain/Discomfort1 (no pain)134 (63.2)
2 (moderate pain)45 (21.22)
3 (extreme pain)33 (15.56)
Anxiety/Depression1 (not anxious depressed)28 (13.2)
2 (moderately anxious or/depressed)118 (55.6)
3 (extreme anxious/depressed)66 (31.1)
Table 3. The relationships between sociodemographic variables and lifestyle factors with EQ-5D-3L domains among CAD patients using the chi-square test.
Table 3. The relationships between sociodemographic variables and lifestyle factors with EQ-5D-3L domains among CAD patients using the chi-square test.
ParametersMobilitySelf CareUsual ActivitiesPainAnxiety/Depression
No ProblemsSome or Extreme Problemsp ValueNo ProblemsSome or
Extreme
Problems		p ValueNo ProblemsSome or
Extreme
Problems		p ValueNo
Problems		Some or
Extreme
Problems		p ValueNo ProblemsSome or Extreme Problemsp Value
Gender
Male51 (29.5)122 (70.5)0.013 *124 (71.6)49 (28.3)0.30036 (20.8)137 (79.2)0.044 *113 (65.6)60 (34.7)0.10127 (15.6)146 (84.4)0.029 *
Female4 (10.3)35 (89.7) 31 (79.4)08 (25.5) 14 (35.9)25 (64.1) 20 (51.3)19 (48.7) 01 (2.6)38 (97.4)
Age group
<50 years9 (25.7)26 (74.3)0.97329 (82.2)06 (17.1)0.17311 (31.4)24 (68.6)0.26422 (62.2)13 (37.2)0.96203 (8.8)32 (91.2)0.375
>50 years46 (26)131 (74) 127 (71.8)50 (28.2) 40 (22.6)137 (77.4) 112 (63.3)65 (36.7) 25 (14.1)152 (85.9)
Education
Illiterate6 (46.1)07 (53.8)0.14906 (46.1)07 (53.8)0.016 *01 (7.7)12 (92.3)0.005 *08 (61.5)05 (38.5)0.72703 (33.1)10 (76.9)0.496
Primary27 (22.3)94 (77.7) 96 (79.3)25 (20.6) 41 (33.9)80 (66.1) 74 (61.2)47 (38.8) 14 (11.6)107 (88.4)
Secondary/
Degree		22 (28.2)56 (71.8) 53 (67.9)25 (32.1) 09 (11.5)69 (88.5) 52 (66.7)26 (33.3) 10 (12.8)68 (87.2)
Employment
Unemployed/
Retired		14 (20)56 (80)0.13652 (74.3)18 (25.7)0.87012 (17.1)58 (82.9)0.09845 (64.3)25 (35.7)0.81907 (10)63 (90)0.332
Employed42 (29.6)100 (70.4) 104 (73.2)38 (26.8) 39 (27.5)103 (72.5) 89 (62.8)53 (37.3) 21 (14.9)121 (85.2)
F/H Of CAD
Yes22 (30.1)51 (69.9)0.37347 (64.9)26 (35.6)0.027 *11 (15.1)62 (84.9)0.026 *44 (60.3)29 (39.7)0.52014 (19.2)59 (80.8)0.062
No34 (24.5)105 (75.5) 109 (78.4) 40 (28.8)99 (71.2) 90 (64.7)49 (35.3) 14 (10.1)125 (89.9)
Comorbid disease
Yes32 (21.2)119 (78.8)0.006 *117 (77.5)34 (22.5)0.042 *41 (27)110 (72.8)0.09793 (61.6)58 (38.4)0.44211 (7.3)140 (92.7)0.0006 *
No24 (39.3)37 (60.7) 39 (63.9)22 (36) 10 (16.4)51 (83.6) 41 (67.2)20 (32.8) 17 (27.9)44 (72.1)
Exercise
≤1 times/week34 (26.4)95 (73.6)0.98088 (68.2)41 (31.8)0.027 *23 (17.8)106 (82.2)0.008 *89 (69)40 (31)0.029 *23 (17.8)106 (82.2)0.013 *
≥2–3 times/week22 (26.5)61 (73.5) 68 (82)15 (18.1) 28 (33.7)55 (66.3) 45 (54.2)38 (45.8) 05 (06)78 (94)
Smoking
Never/
Ex-smoker		44 (27.5)116 (72.5)0.529118 (73.8)42 (26.3)0.92335 (21.9)125 (78.1)0.192102 (63.8)58 (36.2)0.77322 (13.8)138 (86.2)0.682
Current12 (23.1)40 (76.9) 38 (73)14 (26.9) 16 (30.8)36 (69.2) 32 (61.5)20 (38,5) 06 (11.5)46 (88.5)
Alcohol intake
Yes38 (30.4)87 (69.6)0.11494 (75.2)31 (24.8)0.52224 (19.2)101 (80.8)0.071481 (64.8)44 (35.2)0.56418 (14.4)107 (85.6)0.538
No18 (20.7)69 (79.3) 62 (71.3)25 (28.7) 26 (29.9)61 (70.1) 53 (60.9)34 (39.1) 10 (11.5)77 (88.5)
Sleep duration
≤6 h/night40 (28)103 (72)0.459101 (70.6)42 (29.4)0.15931 (21.7)112 (78.3)0.24391 (63.6)52 (36.4)0.85221 (14.7)122 (85.3)0.360
>6 h/night16 (23.2)53 (76.8) 55 (79.7)14 (20.3) 20 (29)49 (71) 43 (62.3)26 (37.7) 07 (10.1)62 (89.9)
Diet
Low risk20 (32.8)41 (67.2)0.18143 (70.5)18 (29.5)0.51614 (23)47 (77)0.81034 (55.7)27 (44.3)0.15111 (18)50 (82)0.187
Moderate/
High risk		36 (23.8)115 (76.2) 113 (74.8)38 (25.2) 37 (24.5)114 (75.5) 100 (66.2)51 (33.8) 17 (11.3)134 (88.7)
p < 0.05 * significance.
Table 4. The multivariate logistic regression analysis of coronary artery disease patients in association with sociodemographic variables and lifestyle factors versus the EQ-5D-3L domains.
Table 4. The multivariate logistic regression analysis of coronary artery disease patients in association with sociodemographic variables and lifestyle factors versus the EQ-5D-3L domains.
ParametersMobilitySelf CareUsual ActivitiesPainAnxiety/Depression
OR RatioCIp ValueOR RatioCIp ValueOR RatioCIp ValueOR RatioCIp ValueOR RatioCIp Value
Gender
MaleReference
Female0.108(0.00065, 1.797)0.3941.102(0.541, 2.246)0.7921.432(0.712, 2.882)0.3210.876(0.432, 1.774)0.7121.654(0.843, 3.241)0.178
Age group
<50 yearsReference
≥50 years1.512(0.789, 2.897)0.2041.873(0.942, 3.721)0.0731.326(0.678, 2.592)0.4121.765(0.879, 3.512)0.0922.091(1.042, 4.192)0.037 *
Education
Illiterate0.876(0.432, 1.774)0.7121.142(0.578, 2.256)0.6931.321(0.641, 2.723)0.4150.897(0.451, 1.783)0.7821.621(0.789, 3.012)0.213
Primary0.763(0.382, 1.523)0.4440.932(0.481, 1.805)0.8321.012(0.521, 1.967)0.9731.023(0.542, 1.932)0.9511.154(0.578, 2.212)0.693
Secondary/DegreeReference
Employment
Unemployed/Retired/Housewife1.932(0.921, 4.052)0.0821.982(0.973, 4.034)0.0592.165(1.098,4.269)0.027 *1.765(0.879, 3.512)0.0921.654(0.843,
3.241)		0.178
EmployedReference
Family history of CAD
Yes 1.421(0.739, 2.731)0.2891.543(0.812, 2.932)0.2011.782(0.893, 3.456)0.0872.045(1.034, 4.051)0.042 *2.354(1.178, 4.702)0.019 *
NoReference
Comorbid disease
Yes2.658(1.221, 5.788)0.014 *2.743(1.321, 5.698)0.012 *2.512(1.189, 5.312)0.019 *3.021(1.578, 5.932)0.004 *2.895(1.478, 5.672)0.006 *
NoReference
Exercise
≤1 time/week0.743(0.389, 1.419)0.3710.821(0.412, 1.632)0.4820.765(0.389, 1.512)0.4040.892(0.431, 1.732)0.5630.698(0.321, 1.432)0.275
≥2–3 times/weekReference
Smoking
Never/Ex-smokerReference
Current1.567(0.812, 3.023)0.1821.642(0.821, 3.278)0.1931.732(0.872, 3.456)0.2211.856(0.912, 3.672)0.1742.045(1.112, 3.978)0.049 *
Alcohol intake
Yes0.984(0.513, 1.888)0.9611.021(0.542, 1.932)0.8970.978(0.498, 1.892)0.9321.145(0.598, 2.231)0.6741.298(0.678, 2.489)0.38
No Reference
Sleep duration
≤6 h/night1.276(0.649, 2.507)0.4831.398(0.721, 2.721)0.2911.321(0.678, 2.562)0.4021.523(0.789, 2.931)0.1961.674(0.843, 3.241)0.178
> 6 h/nightReference
Diet
Low RiskReference
Moderate/High Risk2.341(1.198, 4.571)0.0122.198(1.112, 4.319)0.0192.432(1.231, 4.812)0.0082.798(1.412, 5.541)0.0022.978(1.578, 5.772)0.001
p < 0.05 * significance; CI: Confidence Interval, OR-Odds ratio.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kandasamy, G.; Subramani, T.; Almanasef, M.; Orayj, K.; Shorog, E.; Alshahrani, A.M.; Alanazi, T.S.; Majeed, A. Exploring Factors Affecting Health-Related Quality of Life in Coronary Artery Disease Patients. Medicina 2025, 61, 824. https://doi.org/10.3390/medicina61050824

AMA Style

Kandasamy G, Subramani T, Almanasef M, Orayj K, Shorog E, Alshahrani AM, Alanazi TS, Majeed A. Exploring Factors Affecting Health-Related Quality of Life in Coronary Artery Disease Patients. Medicina. 2025; 61(5):824. https://doi.org/10.3390/medicina61050824

Chicago/Turabian Style

Kandasamy, Geetha, Thangamani Subramani, Mona Almanasef, Khalid Orayj, Eman Shorog, Asma M. Alshahrani, Tahani S. Alanazi, and Anusha Majeed. 2025. "Exploring Factors Affecting Health-Related Quality of Life in Coronary Artery Disease Patients" Medicina 61, no. 5: 824. https://doi.org/10.3390/medicina61050824

APA Style

Kandasamy, G., Subramani, T., Almanasef, M., Orayj, K., Shorog, E., Alshahrani, A. M., Alanazi, T. S., & Majeed, A. (2025). Exploring Factors Affecting Health-Related Quality of Life in Coronary Artery Disease Patients. Medicina, 61(5), 824. https://doi.org/10.3390/medicina61050824

Article Metrics

Back to TopTop