Volume 10, Issue 4 (November 2023)
Avicenna J Neuro Psycho Physiology 2023, 10(4): 145-157 |
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Lotfikhah B, Alipour A, Saffarinia M, Broumandpour M. Modeling psychosocial factors affecting the severity of coronary heart disease: the mediating role of physiological responses and health-related behaviors. Avicenna J Neuro Psycho Physiology 2023; 10 (4) :145-157
URL: http://ajnpp.umsha.ac.ir/article-1-470-en.html
URL: http://ajnpp.umsha.ac.ir/article-1-470-en.html
1- PhD candidate in health psychology, Payame Noor University, Tehran, Iran
2- Professor, Psychology Department, Payame Noor University, Tehran, Iran ,alipor@pnu.ac.ir
3- Professor, Psychology Department, Payame Noor University, Tehran, Iran
4- Assistant Professor, Department of Cardiology, Islamic Azad University, Tehran, Iran
2- Professor, Psychology Department, Payame Noor University, Tehran, Iran ,
3- Professor, Psychology Department, Payame Noor University, Tehran, Iran
4- Assistant Professor, Department of Cardiology, Islamic Azad University, Tehran, Iran
Keywords: Blood lipids, Coronary Heart disease, Psychological factors, Social Factors, Unhealthy behaviors
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Table 1. Demographic information of research participants by gender
Table 2. Descriptive indices of research variables
Table 3. Fit indices of the psychological factors measurement model
Table 4. Fit indices of social factors measurement model
Table 5. Fit indices of the physiological reactions measurement model
Table 6. Fit indices of the health-related behavior measurement model
Figure 1. Measurement model for psychological factors
Figure 2. Measurement model for social factors
Figure 3. Measurement model for physiological responses
Figure 4. Measurement model for health-related behaviors
Table 7. Standard coefficients, standard error, and significance levels for the structural model of psychological factors
Table 8. Results of the bootstrap test for the mediating effects of the social factors model
Full-Text: (231 Views)
Background
Today, cardiovascular diseases (CVDs) are major causes of death, ranking first across the globe [1]. Social, cultural, and industrial changes have modified the pattern of diseases, and as a result, chronic diseases are recognized as the most important health and psychological problems among people [2]. Therefore, chronic diseases are considered a major source of stress, imposing huge financial costs on societies. One of the main public issues identified by the World Health Organization (WHO) is the rising trend of chronic diseases at the global level, with an estimated one-third of all deaths from cardiovascular diseases.
The burden of these heart diseases is very high, especially in middle and high-income countries [1]. This high prevalence of heart disease typically has significant financial consequences, such as the cost of disease management and loss of income [3]. Coronary heart disease (CHD) is one of the rapidly growing diseases [4] and is known as a multifactorial disorder for which more than 250 risk factors have been identified so far [5]. In fact, since cardiovascular diseases are considered a group of psychosomatic diseases, a combination of social, biological, and psychological should be considered when investigating the effective factors in the occurrence of these diseases.
Since psychosocial factors and cardiovascular health are closely related to each other, the identification of psychosocial factors and this relationship is of utmost importance. In addition, cardiovascular disease is one of the most common heart complications and is known as a chronic, progressive, and debilitating disorder [6]. This disease, which may be caused by the narrowing and blockage of the coronary arteries, is the most important cardiovascular disorder and health problem in developing and developed countries.
As a result of rapid socioeconomic developments in recent years in many Eastern Mediterranean and Middle Eastern countries, including Iran, cardiovascular diseases are regarded as a major health and social problem, the dimensions of which are increasing rapidly [7]. Currently, heart disease is recognized as a major cause of hospitalization and death across the globe [8].
Understanding the integration of interactions between multiple psychological and biological factors in regulating the cardiovascular system and developing cardiovascular disorders is a daunting challenge posed to future research. Psychological and social factors significantly affect the cardiovascular system and play a major role in the pathogenesis of cardiovascular disorders. Over the past few decades, assiduous attention has been devoted to psychosocial and behavioral factors in cardiovascular diseases. In addition to patients' physical health, cardiovascular diseases affect their social relationships, lifestyle, family atmosphere, job, and income level.
Based on previous studies, psychosocial risk factors (PSRFs) have a role to play in both the risk of the onset of CHD events, cardiac events, and quality of life. the relative risk of cardiac events and mortality is affected by socioeconomic status, social isolation, lack of social support, acute and chronic stress, depression, anxiety, or other mental disorders (1.2-2.0). [9-11].
Apart from physical problems, cardiovascular diseases can cause significant mental disorders, such as anxiety and depression. These complications, along with the chronic, progressive, and irreversible nature of the disease, have numerous negative consequences for patients, affecting all aspects of their personal and social lives. They are considered one of the plausible reasons for a dramatic decline in their quality of life [12,13]. In addition, there is strong evidence that smoking, physical inactivity, obesity, unhealthy diet, and poor medication adherence increase the risk of cardiovascular disease and increase cardiovascular risk factors, such as hypertension, abnormal levels of blood lipids, insulin resistance, and diabetes [14].
Coronary heart disease is the result of the convergence of several risk factors [15]. Age, gender, family history, and race are among the risk factors that cannot be corrected. On the other hand, blood pressure, diabetes, blood lipids, such as cholesterol, low density, high-density cholesterol, triglyceride, and total cholesterol, obesity, social isolation, low social support and limited social networks, low physical activity, nutrition (food and food additives, including salt, sugar, and fatty acids), alcohol abuse, and smoking are among the risk factors that can be modified for coronary heart disease [16- 20].
Theoretical foundations and research background
Stress is one of the fundamental psychological concepts that disrupt a person's performance in social, psychological, physical, or physiological domains. This word, which entered the field of psychology from physics, has taken on a psychological meaning. Stress is commonly used to describe negative responses and emotions that uncertain changes that affect a biological system." Selye, in his latest conceptualization, considered stress an uncertain response to any environmental demand [21].
This disorder (depression) affects a person's mood with a constant feeling of sadness, restlessness, social isolation, and suicidal thoughts. In addition, it can have physical consequences in terms of disturbed sleep, energy, and appetite [22]. The American Psychological Association defines anxiety as "feelings characterized by tension, anxious thoughts, and physical changes, such as increased blood pressure" [23]. It is defined as a stable trait that is characterized by emotional, cognitive, and behavioral sub-components. Cognitive factors include pessimism, mistrust, and frequent malicious interpretations of others' behavior. The emotional components include anger, and the behavioral component encompasses aggressive verbal and non-verbal behaviors [24]. It is a set of relatively stable and unique characteristics that may change in response to different situations [25].
Background and research literature
Past research has identified several demographic predictors of unhealthy behaviors. For instance, several studies have pinpointed that men follow medical advice to a lesser extent than women [26; 27], while married patients follow the advice to a greater extent than single ones [28]. In the study by Jahangirpour et al. (2013) and in another research by Vella and Friedman (2009), hostility and were recognize as the risk factors of coronary heart disease [29,30]. Nonetheless, some studies did not link these characteristics and coronary heart disease [31]. The results of several studies actually demonstrated that psychological reaction can be defined as a state consisting of affective, cognitive, and motivational components[32-35], such as anger, which is both motivational and emotional [36] and negative cognitions
Research findings emphasize that different behavioral styles, such as unhealthy diet, lack of physical activity, and smoking, are related to the onset and spread of symptoms of coronary heart disease [37]. A peer-reviewed meta-analysis illustrated that smoking leads to increased mortality while reducing smoking after cardiac surgery increases life expectancy [38]. Smoking alone is a major risk factor for CVD [39, 40]; moreover, its combination with other risk factors aggravates cardiovascular diseases. In the study by Libin Tan et al., it has been reported that the risk of cardiovascular disease was higher in hypertensive smokers than in non-smokers [41].
Several other studies have also demonstrated that smoking is a potential risk factor for CVD, and its combined effect with hypertension increases the risk of stroke [41-43]. In addition to hypertension, smoking increases the risk of vascular diseases [44]. Considerable biological evidence suggests that cigarette smoke leads to endothelial damage, cellular dysfunction, arteriosclerosis, acute thrombosis, and a decrease in the oxygen-carrying ability of the blood.
Base on a recent study, a major part (59.0%) of the relationship between coronary heart disease and physical activity can be explained by differences in known risk factors. The findings of the study by Thomas et al. (2020) demonstrated that inactivity, along with low consumption of fruits and vegetables, is the most common behavioral combination for cardiovascular disease. In addition, most smokers (88%) reported three or four high-risk behaviors [45].
A sedentary lifestyle is also a major behavioral risk factor for ischemic heart disease. The results of this study (Jebermedin and Zeberkhrestos, 2021) pointed out that patients without regular physical activity were more susceptible to ischemic heart diseases. The odds of suffering from ischemic heart disease due to physical inactivity were 2.23 times higher than that of the control groups (AOR = 2.23, 95% CI = 1.32–3.76). This result is comparable to studies in the United States of America, Saudi Arabia, and Germany [46-48].
Physical activity elicits some endogenous and paracrine responses associated with cardiometabolic health. This has been largely attributed to exercise-induced changes in white adipose tissue and skeletal muscle phenotype and secretion. Muscle and white adipose tissue influence interorgan crosstalk throught the mediating role of adipokines, myokines, and gaseous messengers, such as nitric oxide. Physical activity, especially resistance training, affects body composition, promoting an anti-atherogenic and anti-inflammatory context [49-51].
Enhanced endothelial function is another mechanism related to cardiovascular health [52]. In this regard, we can also refer to the increased autonomic balance, reduced pathways related to nutrient sensing and growth signaling, as well as the maintenance of a stable phenotype of pre-existing atherosclerotic plaque [51]. Another mediated pathway that reduces cardiovascular disease risk is the antidepressant effect of physical activity [53- 55]. A sedentary lifestyle causes obesity, increasing insulin resistance, blood glucose levels, plasma lipids, and prothrombotic factors [56]. Among the other mechanisms associated with depression and heart disease, we can refer to platelet-endothelial interaction, inflammation, neurohumoral activation, autonomic imbalance, and serotonin transporter gene polymorphism.
Objectives
The current study aimed to determine the role of the aforementioned factors in coronary heart disease mediated by physiological responses and health-related behaviors.
Materials and Methods
This descriptive-correlational study was conducted on men and women referred to the Department of Cardiology of Taleghani, Modarres, and Farhikhtegan hospitals in Tehran, as well as the Department of Cardiology of Imam Khomeini Hospital in Ardabil from April 2022-March 2023. The participants were selected via the convenience sampling method. The sample size was selected based on "structural equation modeling" (SEM). Some researchers consider a minimum sample size of 100 in a study with structural equation modeling and regard a sample size of 200 or more as desirable [57].
The inclusion criteria were as follows: favorable clinical conditions of the subject, performing angiography or having an angiography report, and the presence of blood test results in the patient's file (specifically, blood lipids). On the other hand, the emergence of unusual medical and psychiatric conditions during the implementation of the research was considered the exclusion criterion. Five individuals (researcher and research assistant trained and educated in the field of psychology) were involved in the implementation of this study. Firstly, appropriate communication was made with the subjects; thereafter, explanations were provided about the objectives of the research, and after obtaining the subject's written consent, the questionnaire was completed.
The collection of research data consisted of several parts which were followed for all subjects. The demographic characteristics form was completed by the researcher. The purpose of this part was to establish proper communication and encourage the subject to continue cooperation. The questionnaires related to psychological and behavioral factors were completed by the patient and, in case of inability, with the help of the researcher. The level of blood lipids was extracted from the patient's file. After completing the questionnaires, the angiography report was
extracted from the information center, research center, cardiology centers, or medical records of the relevant hospitals using the patient's file number. Data analysis was performed using the structural equation modeling method. The existing causal relationships between the latent variables and the amount of variance explained in the entire model was investigated and determined after confirmatory factor analysis.
Results
Descriptive indicators
Sample description
The participants encompassed 163 (60.4%) men and 107 (39.6%)women. The mean age scores of male and female participants were reported as 59.85±10.51 and 61.90±10.53 years, respectively. Additional information related to demographic variables based on gender is reported in Table 1.
The burden of these heart diseases is very high, especially in middle and high-income countries [1]. This high prevalence of heart disease typically has significant financial consequences, such as the cost of disease management and loss of income [3]. Coronary heart disease (CHD) is one of the rapidly growing diseases [4] and is known as a multifactorial disorder for which more than 250 risk factors have been identified so far [5]. In fact, since cardiovascular diseases are considered a group of psychosomatic diseases, a combination of social, biological, and psychological should be considered when investigating the effective factors in the occurrence of these diseases.
Since psychosocial factors and cardiovascular health are closely related to each other, the identification of psychosocial factors and this relationship is of utmost importance. In addition, cardiovascular disease is one of the most common heart complications and is known as a chronic, progressive, and debilitating disorder [6]. This disease, which may be caused by the narrowing and blockage of the coronary arteries, is the most important cardiovascular disorder and health problem in developing and developed countries.
As a result of rapid socioeconomic developments in recent years in many Eastern Mediterranean and Middle Eastern countries, including Iran, cardiovascular diseases are regarded as a major health and social problem, the dimensions of which are increasing rapidly [7]. Currently, heart disease is recognized as a major cause of hospitalization and death across the globe [8].
Understanding the integration of interactions between multiple psychological and biological factors in regulating the cardiovascular system and developing cardiovascular disorders is a daunting challenge posed to future research. Psychological and social factors significantly affect the cardiovascular system and play a major role in the pathogenesis of cardiovascular disorders. Over the past few decades, assiduous attention has been devoted to psychosocial and behavioral factors in cardiovascular diseases. In addition to patients' physical health, cardiovascular diseases affect their social relationships, lifestyle, family atmosphere, job, and income level.
Based on previous studies, psychosocial risk factors (PSRFs) have a role to play in both the risk of the onset of CHD events, cardiac events, and quality of life. the relative risk of cardiac events and mortality is affected by socioeconomic status, social isolation, lack of social support, acute and chronic stress, depression, anxiety, or other mental disorders (1.2-2.0). [9-11].
Apart from physical problems, cardiovascular diseases can cause significant mental disorders, such as anxiety and depression. These complications, along with the chronic, progressive, and irreversible nature of the disease, have numerous negative consequences for patients, affecting all aspects of their personal and social lives. They are considered one of the plausible reasons for a dramatic decline in their quality of life [12,13]. In addition, there is strong evidence that smoking, physical inactivity, obesity, unhealthy diet, and poor medication adherence increase the risk of cardiovascular disease and increase cardiovascular risk factors, such as hypertension, abnormal levels of blood lipids, insulin resistance, and diabetes [14].
Coronary heart disease is the result of the convergence of several risk factors [15]. Age, gender, family history, and race are among the risk factors that cannot be corrected. On the other hand, blood pressure, diabetes, blood lipids, such as cholesterol, low density, high-density cholesterol, triglyceride, and total cholesterol, obesity, social isolation, low social support and limited social networks, low physical activity, nutrition (food and food additives, including salt, sugar, and fatty acids), alcohol abuse, and smoking are among the risk factors that can be modified for coronary heart disease [16- 20].
Theoretical foundations and research background
Stress is one of the fundamental psychological concepts that disrupt a person's performance in social, psychological, physical, or physiological domains. This word, which entered the field of psychology from physics, has taken on a psychological meaning. Stress is commonly used to describe negative responses and emotions that uncertain changes that affect a biological system." Selye, in his latest conceptualization, considered stress an uncertain response to any environmental demand [21].
This disorder (depression) affects a person's mood with a constant feeling of sadness, restlessness, social isolation, and suicidal thoughts. In addition, it can have physical consequences in terms of disturbed sleep, energy, and appetite [22]. The American Psychological Association defines anxiety as "feelings characterized by tension, anxious thoughts, and physical changes, such as increased blood pressure" [23]. It is defined as a stable trait that is characterized by emotional, cognitive, and behavioral sub-components. Cognitive factors include pessimism, mistrust, and frequent malicious interpretations of others' behavior. The emotional components include anger, and the behavioral component encompasses aggressive verbal and non-verbal behaviors [24]. It is a set of relatively stable and unique characteristics that may change in response to different situations [25].
Background and research literature
Past research has identified several demographic predictors of unhealthy behaviors. For instance, several studies have pinpointed that men follow medical advice to a lesser extent than women [26; 27], while married patients follow the advice to a greater extent than single ones [28]. In the study by Jahangirpour et al. (2013) and in another research by Vella and Friedman (2009), hostility and were recognize as the risk factors of coronary heart disease [29,30]. Nonetheless, some studies did not link these characteristics and coronary heart disease [31]. The results of several studies actually demonstrated that psychological reaction can be defined as a state consisting of affective, cognitive, and motivational components[32-35], such as anger, which is both motivational and emotional [36] and negative cognitions
Research findings emphasize that different behavioral styles, such as unhealthy diet, lack of physical activity, and smoking, are related to the onset and spread of symptoms of coronary heart disease [37]. A peer-reviewed meta-analysis illustrated that smoking leads to increased mortality while reducing smoking after cardiac surgery increases life expectancy [38]. Smoking alone is a major risk factor for CVD [39, 40]; moreover, its combination with other risk factors aggravates cardiovascular diseases. In the study by Libin Tan et al., it has been reported that the risk of cardiovascular disease was higher in hypertensive smokers than in non-smokers [41].
Several other studies have also demonstrated that smoking is a potential risk factor for CVD, and its combined effect with hypertension increases the risk of stroke [41-43]. In addition to hypertension, smoking increases the risk of vascular diseases [44]. Considerable biological evidence suggests that cigarette smoke leads to endothelial damage, cellular dysfunction, arteriosclerosis, acute thrombosis, and a decrease in the oxygen-carrying ability of the blood.
Base on a recent study, a major part (59.0%) of the relationship between coronary heart disease and physical activity can be explained by differences in known risk factors. The findings of the study by Thomas et al. (2020) demonstrated that inactivity, along with low consumption of fruits and vegetables, is the most common behavioral combination for cardiovascular disease. In addition, most smokers (88%) reported three or four high-risk behaviors [45].
A sedentary lifestyle is also a major behavioral risk factor for ischemic heart disease. The results of this study (Jebermedin and Zeberkhrestos, 2021) pointed out that patients without regular physical activity were more susceptible to ischemic heart diseases. The odds of suffering from ischemic heart disease due to physical inactivity were 2.23 times higher than that of the control groups (AOR = 2.23, 95% CI = 1.32–3.76). This result is comparable to studies in the United States of America, Saudi Arabia, and Germany [46-48].
Physical activity elicits some endogenous and paracrine responses associated with cardiometabolic health. This has been largely attributed to exercise-induced changes in white adipose tissue and skeletal muscle phenotype and secretion. Muscle and white adipose tissue influence interorgan crosstalk throught the mediating role of adipokines, myokines, and gaseous messengers, such as nitric oxide. Physical activity, especially resistance training, affects body composition, promoting an anti-atherogenic and anti-inflammatory context [49-51].
Enhanced endothelial function is another mechanism related to cardiovascular health [52]. In this regard, we can also refer to the increased autonomic balance, reduced pathways related to nutrient sensing and growth signaling, as well as the maintenance of a stable phenotype of pre-existing atherosclerotic plaque [51]. Another mediated pathway that reduces cardiovascular disease risk is the antidepressant effect of physical activity [53- 55]. A sedentary lifestyle causes obesity, increasing insulin resistance, blood glucose levels, plasma lipids, and prothrombotic factors [56]. Among the other mechanisms associated with depression and heart disease, we can refer to platelet-endothelial interaction, inflammation, neurohumoral activation, autonomic imbalance, and serotonin transporter gene polymorphism.
Objectives
The current study aimed to determine the role of the aforementioned factors in coronary heart disease mediated by physiological responses and health-related behaviors.
Materials and Methods
This descriptive-correlational study was conducted on men and women referred to the Department of Cardiology of Taleghani, Modarres, and Farhikhtegan hospitals in Tehran, as well as the Department of Cardiology of Imam Khomeini Hospital in Ardabil from April 2022-March 2023. The participants were selected via the convenience sampling method. The sample size was selected based on "structural equation modeling" (SEM). Some researchers consider a minimum sample size of 100 in a study with structural equation modeling and regard a sample size of 200 or more as desirable [57].
The inclusion criteria were as follows: favorable clinical conditions of the subject, performing angiography or having an angiography report, and the presence of blood test results in the patient's file (specifically, blood lipids). On the other hand, the emergence of unusual medical and psychiatric conditions during the implementation of the research was considered the exclusion criterion. Five individuals (researcher and research assistant trained and educated in the field of psychology) were involved in the implementation of this study. Firstly, appropriate communication was made with the subjects; thereafter, explanations were provided about the objectives of the research, and after obtaining the subject's written consent, the questionnaire was completed.
The collection of research data consisted of several parts which were followed for all subjects. The demographic characteristics form was completed by the researcher. The purpose of this part was to establish proper communication and encourage the subject to continue cooperation. The questionnaires related to psychological and behavioral factors were completed by the patient and, in case of inability, with the help of the researcher. The level of blood lipids was extracted from the patient's file. After completing the questionnaires, the angiography report was
extracted from the information center, research center, cardiology centers, or medical records of the relevant hospitals using the patient's file number. Data analysis was performed using the structural equation modeling method. The existing causal relationships between the latent variables and the amount of variance explained in the entire model was investigated and determined after confirmatory factor analysis.
Results
Descriptive indicators
Sample description
The participants encompassed 163 (60.4%) men and 107 (39.6%)women. The mean age scores of male and female participants were reported as 59.85±10.51 and 61.90±10.53 years, respectively. Additional information related to demographic variables based on gender is reported in Table 1.
Table 1. Demographic information of research participants by gender
| Variable | Variable levels | Males | Females | ||
| Frequency | Percentage | Frequency | Percentage | ||
| Education | Illiterate | 18 | 11% | 34 | 31.8% |
| reading and writing literacy | 13 | 8% | 12 | 11.2% | |
| Primary school | 23 | %14.1 | 23 | 21.5% | |
| Junior high school | 25 | 15.3% | 8 | 7.5% | |
| Senior high school | 7 | 4.3% | 1 | 0.9% | |
| Diploma | 41 | 25.2% | 12 | 11.2% | |
| Academic education | 33 | 20.2% | 13 | 12.1% | |
| Missing data | 3 | 1.8% | 4 | 3.7% | |
| Marital status | Single | 6 | 3.7% | 5 | 4.7% |
| Married | 141 | 86.5% | 57 | 53.3% | |
| Divorced | 8 | 4.9% | 0 | 0 | |
| Widowed | 4 | 2.5% | 42 | 39.3% | |
| Missing data | 4 | 2.5% | 3 | 2.8% | |
| Occupation | Employed | 88 | 54% | 17 | 15.9% |
| Student | 2 | 1.2% | 0 | 0 | |
| Housewife | 0 | 0 | 82 | 76.6% | |
| Retired | 46 | 28.2% | 2 | 1.9% | |
| Supported by charity organizations | 12 | 7.4% | 5 | 47% | |
| Decrepit | 9 | 5.5% | 1 | 0.9% | |
| Missing data | 6 | 3.7% | 0 | 0 | |
| State of residence | Private | 133 | 81.6% | 80 | 74.8% |
| Rental | 18 | 11% | 16 | 15% | |
| Homeless | 0 | 0 | 2 | 1.9% | |
| Missing data | 12 |
7.4% | 9 | 8.4% | |
Table 2. Descriptive indices of research variables
| Minimum | Maximum | Mean | Standard deviation | Skewness | kurtosis | |||||
| Depression | 0 | 40 | 17.22 | 7.14 | 0.08 | 0.30 | ||||
| Anxiety | 2 | 40 | 20.22 | 6.32 | -0.29 | 0.55 | ||||
| Stress | 0 | 42 | 24.99 | 8.03 | -0.62 | 0.47 | ||||
| Hostility | 1 | 20 | 6.62 | 3.21 | 0.34 | 0.51 | ||||
| type D personality | 5 | 42 | 29.54 | 5.46 | -0.35 | 1.47 | ||||
| Negative affect subscale | 0 | 28 | 15.63 | 5.20 | -0.21 | -0.37 | ||||
| Social inhibition subscale | 5 | 21 | 14.03 | 2.34 | 0.07 | 0.66 | ||||
| social support | 4 | 60 | 38.40 | 7.19 | -0.49 | 2.57 | ||||
| Adherence to treatment | 0 | 10 | 5.51 | 1.79 | -0.05 | 0.26 | ||||
| Quality of Life | 15 | 43 | 30.54 | 3.71 | -0.773 | 4.01 | ||||
| Psychological reaction | 7 | 63 | 41.21 | 9.23 | -0.52 | 0.60 | ||||
| Responsiveness subscale | 1 | 19 | 11.34 | 3.25 | -0.32 | 0.18 | ||||
| Resistance to social influence | 0 | 18 | 11.50 | 3.14 | -0.36 | 0.60 | ||||
| Reaction to advice | 0 | 10 | 4.85 | 1.72 | 0.15 | 0.95 | ||||
| Emotional response to choice constraints subscale | 6 | 19 | 13.54 | 2.74 | -0.73 | 0.28 | ||||
| Social comparison | 13 | 49 | 32.79 | 7.80 | -0.127 | -1.27 | ||||
| TC | 124 | 370 | 203.24 | 37.14 | 0.707 | 0.922 | ||||
| TG | 40 | 359 | 204.36 | 50.81 | 0.614 | 0.145 | ||||
| Table 2 Continue | ||||||||||
| HDL | 20 | 89 | 37.51 | 8.33 | 1.42 | 5.17 | ||||
| LDL | 70 | 205 | 123.13 | 26.11 | 0.45 | -0.170 | ||||
| unhealthy diet | 1 | 36 | 14.77 | 4.67 | 0.72 | 2.10 | ||||
| Unhealthy additives | 9 | 24 | 17.05 | 2.78 | -0.66 | 0.47 | ||||
| Socio-Economic Status (SES) | 5 | 20 | 10.81 | 2.21 | 1.00 | 3.13 | ||||
| smoking (number of cigarettes) | 0 | 60 | 4.59 | 8.40 | 2.31 | 7.39 | ||||
| Physical activity (doing and not doing) | 0 | 1 | 0.43 | 0.50 | 0.30 | -1.92 | ||||
| Coronary heart disease | 0 | 90 | 61.23 | 16.14 | -0.150 | 0.612 | ||||
Descriptive indicators of research variables
Table 2 displays the descriptive indices of research variables.
Table 2, in addition to the mean and standard deviation of research variables, illustrates their skewness and kurtosis.
inferential findings
Examination of research questions
Main question
1. Do psychological factors have an effect on coronary heart disease through the mediating role of physiological responses and health-related behaviors?
In this project, the structural equation modeling method was used to answer the research questions. This method consists of two important parts:
A) Measurement model
b) Structural model
For this reason, SEM analysis includes two main steps: structural model analysis through path analysis and examining the measurement model through confirmatory factor analysis. Considering that most researchers suggest that the measurement model should be evaluated before the structural modeling, the researcher carried out these steps in order.
Research measurement model
The measurement model defines the measurement of latent variables through observed variables. In the measurement model of the research (figures 1, 2, 3, and 4), 19 indicators are considered to reflect four latent structures. According to Figure 1, it is assumed that indicators of depression, stress, anxiety, hostility, type D personality, and compliance with treatment measure the latent variable of psychological factors. According to Figure 2, it is assumed that indicators of social support, socioeconomic status, social comparison, psychological reaction, and quality of life measure the latent variable of social factors.
According to Figure 3, it is assumed that the indicators of smoking, unhealthy diet, inactivity, and unhealthy additives measure the latent variable of unhealthy behaviors. Finally, according to Figure 4, it is assumed that the indicators of HDL, LDL, triglycerides, and total cholesterol measure the latent variable of physiological responses. Now the question is, to what extent does the measurement model of the current research "fit" the collected data? The goodness of fit of this model is very important since it encompasses all the latent variables of the structural equation modeling.
The measurement model was performed by path analysis using Lisrel software. Chi-square examination illustrated that the latent variable of psychological factors was measured with indicators of depression, stress, anxiety, hostility, type D personality, and adherence to treatment (non-adherence to treatment). Figure 1 illustrates the factor loadings related to the measurement model of psychological factors. All coefficients are significant at P>0.01. The fit indices of this model are also reported in Table 3. All indicators point to the appropriate fit of the measurement model.
Therefore, based on the fit indices obtained from the path analysis in the evaluation of the research measurement model, it can be stated that the observed variables are able to measure their respective latent variables. The latent variable of social factors was measured with indicators of social
Table 2 displays the descriptive indices of research variables.
Table 2, in addition to the mean and standard deviation of research variables, illustrates their skewness and kurtosis.
inferential findings
Examination of research questions
Main question
1. Do psychological factors have an effect on coronary heart disease through the mediating role of physiological responses and health-related behaviors?
In this project, the structural equation modeling method was used to answer the research questions. This method consists of two important parts:
A) Measurement model
b) Structural model
For this reason, SEM analysis includes two main steps: structural model analysis through path analysis and examining the measurement model through confirmatory factor analysis. Considering that most researchers suggest that the measurement model should be evaluated before the structural modeling, the researcher carried out these steps in order.
Research measurement model
The measurement model defines the measurement of latent variables through observed variables. In the measurement model of the research (figures 1, 2, 3, and 4), 19 indicators are considered to reflect four latent structures. According to Figure 1, it is assumed that indicators of depression, stress, anxiety, hostility, type D personality, and compliance with treatment measure the latent variable of psychological factors. According to Figure 2, it is assumed that indicators of social support, socioeconomic status, social comparison, psychological reaction, and quality of life measure the latent variable of social factors.
According to Figure 3, it is assumed that the indicators of smoking, unhealthy diet, inactivity, and unhealthy additives measure the latent variable of unhealthy behaviors. Finally, according to Figure 4, it is assumed that the indicators of HDL, LDL, triglycerides, and total cholesterol measure the latent variable of physiological responses. Now the question is, to what extent does the measurement model of the current research "fit" the collected data? The goodness of fit of this model is very important since it encompasses all the latent variables of the structural equation modeling.
The measurement model was performed by path analysis using Lisrel software. Chi-square examination illustrated that the latent variable of psychological factors was measured with indicators of depression, stress, anxiety, hostility, type D personality, and adherence to treatment (non-adherence to treatment). Figure 1 illustrates the factor loadings related to the measurement model of psychological factors. All coefficients are significant at P>0.01. The fit indices of this model are also reported in Table 3. All indicators point to the appropriate fit of the measurement model.
Therefore, based on the fit indices obtained from the path analysis in the evaluation of the research measurement model, it can be stated that the observed variables are able to measure their respective latent variables. The latent variable of social factors was measured with indicators of social
Table 3. Fit indices of the psychological factors measurement model
| Fit index | Acceptable domain | Value |
| Chi-2 (χ2) | - | 20.08 |
| chi-square divided by the degrees of freedom (χ2/df) | 5> | 2.23 |
| Normalized Fit Index (NFI) | >0.90 | 0.072 |
| Non-Normalized Fit Index (NNFI) | >0.90 | 0.974 |
| Comparative Fit Index (CFI) | >0.90 | 0.984 |
| Incremental Fit Index (IFI) | >0.90 | 0.984 |
| Goodness of fit index (GFI) | >0.90 | 0.977 |
| Root mean square error of approximation (RMSEA) | <0.08 | 0.068 |
| Standardized Root Mean Squared Residual (SRMR) | <0.1 | 0.028 |
support, socioeconomic status, social comparison, psychological response, and quality of life. Figure 2 displays the factor loadings of the measurement model of social factors, and Table 4 presents the fit indices of this model. The heterogeneous factor loadings and the non-acceptance of most fit indices indicate that these indicators cannot measure a single latent variable. Therefore, social factors are entered into the hypothesized model separately and independently.
In Figure 3, factor loadings (standard coefficients) for physiological responses illustrate that the standard coefficient equal to 1.14 for the TC variable indicates a high correlation (Multi-collinearity) between the indicators. The assessment of the correlation between indicators demonstrates that the correlation between TC and LDL is equal to 0.83; therefore, to overcome the problem of multicollinearity, the TC variable is excluded from the analysis. Table 5 depicts the relatively good fit of the measurement model for physiological responses.
Moreover, Figure 4, the measurement model for health-related behaviors, and Table 6, the fit indices for this measurement model, demonstrate that in this measurement model, to align with other variables, the variable of lack of physical activity (instead of physical activity) was analyzed. The non-significance of the factor loading of this indicator caused this variable to be excluded from the analysis.
In Figure 3, factor loadings (standard coefficients) for physiological responses illustrate that the standard coefficient equal to 1.14 for the TC variable indicates a high correlation (Multi-collinearity) between the indicators. The assessment of the correlation between indicators demonstrates that the correlation between TC and LDL is equal to 0.83; therefore, to overcome the problem of multicollinearity, the TC variable is excluded from the analysis. Table 5 depicts the relatively good fit of the measurement model for physiological responses.
Moreover, Figure 4, the measurement model for health-related behaviors, and Table 6, the fit indices for this measurement model, demonstrate that in this measurement model, to align with other variables, the variable of lack of physical activity (instead of physical activity) was analyzed. The non-significance of the factor loading of this indicator caused this variable to be excluded from the analysis.
Table 4. Fit indices of social factors measurement model
| Fit index | Accepted domain | Value |
| Chi-2 (χ2) | - | 13.46 |
| Chi-square divided by the degrees of freedom (χ2/df) | 5> | 2.69 |
| Normalized Fit Index (NFI) | >0.90 | 0.849 |
| Non-Normalized Fit Index (NNFI) | >0.90 | 0.786 |
| Comparative Fit Index (CFI) | >0.90 | 0.893 |
| Incremental Fit Index (IFI) | >0.90 | 0.899 |
| Goodness of fit index (GFI) | >0.90 | 0.981 |
| Root mean square error of approximation (RMSEA) | <0.08 | 0.079 |
| Standardized Root Mean Squared Residual (SRMR) | <0.1 | 0.053 |
Table 5. Fit indices of the physiological reactions measurement model
| Fit index | Accepted domain | Value |
| Chi-2 (χ2) | - | 36.33 |
| Chi-square divided by the degrees of freedom (χ2/df) | 5> | 18.16 |
| Normalized Fit Index (NFI) | >0.90 | 0.939 |
| Non-Normalized Fit Index (NNFI) | >0.90 | 0.904 |
| Comparative Fit Index (CFI) | >0.90 | 0.941 |
| Incremental Fit Index (IFI) | >0.90 | 0.942 |
| Goodness of fit index (GFI) | >0.90 | 0.935 |
| Root mean square error of approximation (RMSEA) | <0.08 | 0.083 |
| Standardized Root Mean Squared Residual (SRMR) | <0.1 | 0.097 |
Table 6. Fit indices of the health-related behavior measurement model
| Fit index | Accepted domain | Value |
| Chi-2 (χ2) | - | 18.62 |
| Chi-square divided by the degrees of freedom (χ2/df) | 5> | 9.31 |
| Normalized Fit Index (NFI) | >0.90 | 0.857 |
| Non-normalized fit Index (NNFI) | >0.90 | 0.905 |
| Comparative Fit Index (CFI) | >0.90 | 0.919 |
| Incremental Fit Index (IFI) | >0.90 | 0.920 |
| Goodness of fit index (GFI) | >0.90 | 0.897 |
| Root mean square error of approximation (RMSEA) | <0.08 | 0.064 |
| Standardized Root Mean Squared Residual (SRMR) | <0.1 | 0.023 |
Figure 1. Measurement model for psychological factors
Figure 2. Measurement model for social factors
Figure 3. Measurement model for physiological responses
Figure 4. Measurement model for health-related behaviors
Structural modeling test
The structural model of the research was examined after ensuring the power of indicators in measuring psychological factors, social factors, physiological responses, and health-related behaviors (unhealthy behaviors). In this model (Figures 4, 5), it is assumed that the latent variable of psychological factors, social factors with the mediation of the latent variables of physiological responses, and unhealthy behaviors predict the severity of coronary heart disease. It can also be inferred that the researcher's assumption is that physiological factors predict the relationship between unhealthy behaviors and the severity of coronary heart disease.
Accordingly, it can be concluded that, in general, the structural model of the present research "fits" the collected data and the conceptual model of the research, in which the latent variables of psychological factors, social factors, physiological responses, and unhealthy behaviors in the form of a model predict the severity of coronary heart disease "fits" the collected data. The squared multiple correlations in the structural model of psychological factors explain 25.33% of the variance of coronary heart disease, signifying that the three variables of psychological factors, physiological responses, and unhealthy behaviors explain 25.33% of the variance of coronary heart disease.
In this model, psychological factors explain 41.8% of the variance of physiological responses and 18.49% of the variance of health-related behaviors (unhealthy behaviors). Moreover, physiological responses explain 10.89% of the variance of coronary heart disease, and health-related behaviors explain 14.14% of its variance. In addition, the squared multiple correlations in the structural model of social factors demonstrated that predictor variables explain 21.86% of the variance of coronary heart disease. In this model, social factors explain a total of 32.42% of the variance of physiological responses and 32.72% of the variance of health-related behaviors. Physiological responses explain 9.61% of the variance of coronary heart disease, and health-related behaviors explain 12.25% of its variance. In general, psychological and social factors explain 47.19% of the variance of coronary heart disease.
Special questions
The structural model of the research was examined after ensuring the power of indicators in measuring psychological factors, social factors, physiological responses, and health-related behaviors (unhealthy behaviors). In this model (Figures 4, 5), it is assumed that the latent variable of psychological factors, social factors with the mediation of the latent variables of physiological responses, and unhealthy behaviors predict the severity of coronary heart disease. It can also be inferred that the researcher's assumption is that physiological factors predict the relationship between unhealthy behaviors and the severity of coronary heart disease.
Accordingly, it can be concluded that, in general, the structural model of the present research "fits" the collected data and the conceptual model of the research, in which the latent variables of psychological factors, social factors, physiological responses, and unhealthy behaviors in the form of a model predict the severity of coronary heart disease "fits" the collected data. The squared multiple correlations in the structural model of psychological factors explain 25.33% of the variance of coronary heart disease, signifying that the three variables of psychological factors, physiological responses, and unhealthy behaviors explain 25.33% of the variance of coronary heart disease.
In this model, psychological factors explain 41.8% of the variance of physiological responses and 18.49% of the variance of health-related behaviors (unhealthy behaviors). Moreover, physiological responses explain 10.89% of the variance of coronary heart disease, and health-related behaviors explain 14.14% of its variance. In addition, the squared multiple correlations in the structural model of social factors demonstrated that predictor variables explain 21.86% of the variance of coronary heart disease. In this model, social factors explain a total of 32.42% of the variance of physiological responses and 32.72% of the variance of health-related behaviors. Physiological responses explain 9.61% of the variance of coronary heart disease, and health-related behaviors explain 12.25% of its variance. In general, psychological and social factors explain 47.19% of the variance of coronary heart disease.
Special questions
- Do physiological responses predict the severity of coronary heart disease?
According to Table 4-9, the path coefficient between physiological responses and coronary heart disease is significant at 1% (P<1%, B=0.33). Accordingly, it can be argued that one standard deviation increase in physiological responses leads to a 0.33 standard deviation increase in the severity of coronary heart disease.
2. Do unhealthy behaviors predict the severity of coronary heart disease?
As illustrated in Table 4-9, the path coefficient between unhealthy behaviors and the severity of coronary heart disease is significant at 1% (P<1%, B=0.38). In other words, the findings of the present study demonstrated that physiological factors mediated the relationship between unhealthy behaviors and the severity of coronary heart disease (at 1%).
Do psychosocial factors predict the severity of coronary heart disease?
A) Psychological factors
Based on Table 7, the bootstrap test was used to evaluate the prediction of the severity of coronary heart disease by psychological factors. The results pointed to the indirect relationship between psychological factors and the severity of coronary heart disease through the mediation of physiological responses and health-related behaviors. Moreover, the relationship is significant in both mediating paths. This means that the effect of psychological factors on coronary heart disease through the mediation of physiological responses is significant, with a standard coefficient of 0.096 at P<0.05. Furthermore, the effect of this variable through the mediation of health-related behaviors is significant, with a standard coefficient of 0.163 at P< 0.01.
2. Do unhealthy behaviors predict the severity of coronary heart disease?
As illustrated in Table 4-9, the path coefficient between unhealthy behaviors and the severity of coronary heart disease is significant at 1% (P<1%, B=0.38). In other words, the findings of the present study demonstrated that physiological factors mediated the relationship between unhealthy behaviors and the severity of coronary heart disease (at 1%).
Do psychosocial factors predict the severity of coronary heart disease?
A) Psychological factors
Based on Table 7, the bootstrap test was used to evaluate the prediction of the severity of coronary heart disease by psychological factors. The results pointed to the indirect relationship between psychological factors and the severity of coronary heart disease through the mediation of physiological responses and health-related behaviors. Moreover, the relationship is significant in both mediating paths. This means that the effect of psychological factors on coronary heart disease through the mediation of physiological responses is significant, with a standard coefficient of 0.096 at P<0.05. Furthermore, the effect of this variable through the mediation of health-related behaviors is significant, with a standard coefficient of 0.163 at P< 0.01.
Table 7. Standard coefficients, standard error, and significance levels for the structural model of psychological factors
| Path | Standard coefficient | Standard error | Significance level |
| 0.29 | 0.081 | 0.01> P | |
| 0.083 | 0.01> P | ||
| 0.33 | .0650 | 0.01> P | |
| 0.38 | 0.042 | 0.01> P |
Table 8. Results of the bootstrap test for the mediating effects of the social factors model
| independent variable | Mediating variable | Dependent variable | Standard coefficient | Standard error | Significance level | >95% | 95%> |
| social support | Physiological responses | Coronary heart disease | -0.056 | 0.077 | P>0.05 | 0.008 | -0.098 |
| Psychological response | Physiological responses | Coronary heart disease | 0.130 | 0.101 | 0.01 > P | 0.163 | 0.089 |
| Social comparison | Health-related behaviors | Coronary heart disease | 0.091 | 0.026 | P<0.05 | 0.131 | 0.034 |
| Quality of Life | Health-related behaviors | Coronary heart disease | -0.179 | 0.064 | P<0.01 | -0.088 | -0.235 |
| Quality of Life | Physiological responses | Coronary heart disease | -0.105 | 0.058 | 0.01> P | -0.53 | -0.147 |
b) Social factors
As illustrated in Table 8, the bootstrap test was used to evaluate the prediction of the severity of coronary heart disease by social factors. It measures the indirect relationship between social factors and the severity of coronary heart disease through the mediation of physiological responses and health-related behaviors. As displayed in this table, all four mediating paths are significant. Moreover, except for the mediating effect of social support on heart disease through the mediation of physiological responses, which is not significant, the remaining mediating effects are significant.
Discussion
The present study aimed to assess the effect of psychosocial factors on coronary heart disease medicated by physiological responses and health-related behaviors. To this end, structural equation modeling was used according to the research conducted in the fourth chapter. This method consists of two parts: the "measurement model" and the "structural model." Examining the fit indices of the model demonstrated that the smoothed chi-square is less than five, and the optimal values of the comparative fit index (CFI), model fit index (GFI), and Adjusted Goodness of Fit Index (AGFI) are greater than 90%. Moreover, the root mean square error of approximation (RMSEA) is less than 8%.
The comparison of the collected data with the approved criteria demonstrated that, in general, the structural model of the current research "fits" the collected data well. In other words, based on the conceptual model of the research, psychosocial factors have an effect on coronary heart disease, and part of this effect is exerted through the mediation of health-related behaviors and physiological responses. Coronary heart disease is the narrowing of the coronary arteries that supply blood and oxygen to the heart. Due to the accumulation of atheroma and plaque in the arteries, the process is called atherosclerosis.
Physiological mechanisms include the buildup of atherosclerotic plaques in the walls of arteries as a result of inflammatory processes, lipid abnormalities, such as increased low-density lipoprotein cholesterol (LDLc), decreased high-density lipoprotein (HDL), and high triglycerides (TAG), decreased vasodilation and increased risk of thrombosis, endothelial dysfunction and changes in the endothelial lining of blood vessels of the cardiovascular system, high levels of homocysteine (Hcy), which is associated with increased LDLc, and a decrease in nitric oxide produced in endothelial cells, which causes vasodilation [58].
In explaining this finding, several studies have pinpointed that apart from its known role in promoting atherosclerosis in blood vessels, hyperlipidemia may directly affect the heart, leading to increased ischemia/reperfusion injury and poor response to cardiac protective interventions, such as ischemic preconditioning [59]. Further investigation suggested that the correlation between high cholesterol and increased risk of cardiovascular events is mainly related to low-density lipoprotein (LDL)-cholesterol (LDL-C). On the contrary, HDL-C is inversely correlated with mortality from coronary heart disease [60,61]. Accordingly, the "cholesterol hypothesis" was developed, which proposes that LDL-C is the cause of atherosclerosis, and as a result, reduced LDL-C lowers the risk of myocardial infarction and other cardiovascular events.
*The path coefficient between unhealthy behaviors and the severity of coronary heart disease is significant at 1% (P<1%, B=0.38).
In this research, from health-related behaviors, only unhealthy behaviors were evaluated. Unhealthy behavior consists of smoking, unhealthy diet, unhealthy additives (fat, sugar, and salt), and physical inactivity. According to Table [4-12], the test results show that unhealthy behaviors have a positive and significant relationship with coronary heart disease. In order to discuss and analyze this research finding, unhealthy behavior is considered in the form of smoking, nutrition, and physical activity. In explaining these findings, it can be stated that significant biological evidence shows that the components of cigarette smoke lead to endothelial dysfunction, cell dysfunction, arteriosclerosis, acute thrombosis, and impaired oxygen-carrying capacity of the blood [39]. Scientific findings indicated that improper nutrition is one of the most important risk factors in cardiovascular disease [60-63]. A high intake of trans-fatty acids is associated with an increased risk of cardiovascular diseases [64]. The relationship between nutrition and coronary heart disease can be explained by cholesterol being the main nutritional factor in coronary heart disease. The body makes most of it in the blood, and only about 20% of the cholesterol in the bloodstream comes from our food. Getting too much dietary cholesterol increases LDL. Nonetheless, its negative impact is less than saturated fatty acids. Most foods containing saturated fats, especially animal and solid fats, are a rich source of cholesterol, and their limited consumption leads to a decrease in cholesterol [65].
Moreover, in explaining the relationship between physical inactivity and coronary heart disease, it can be stated that a sedentary lifestyle causes obesity, increasing insulin resistance, blood glucose levels, plasma lipids, and prothrombotic factors [56]. Diet plays a critical role in creating the background for the risk factors of cardiovascular diseases. Recent studies have also provided evidence on the relationship of dietary patterns with chronic diseases and the risk of death. Furthermore, the results of research in recent decades demonstrated that drug abuse, smoking, unhealthy diet, physical inactivity, obesity, high blood pressure, and lipid abnormalities are considered risk factors for cardiovascular disease, especially coronary heart disease [66-72].
Psychological factors and coronary heart disease
The presented studies are only a part of the findings related to the role of psychosocial factors in coronary heart disease, and now, some meta-analyses and systematic reviews are being conducted on psychosocial variables. In order to explain these findings, it can be stated that psychosocial factors are one of the risk factors for coronary heart disease [73, 74], and this relationship is illustrated in two physiological and behavioral ways [75, 76]. In order to physiologically explain the relationship between psychosocial factors and coronary heart disease, the following can be mentioned:
Although the underlying mechanisms are unclear, depression has been linked to physiological and psychosocial changes that are detrimental to the cardiovascular system [77]. A meta-analysis conducted in 2017 associated major depressive disorder with a 72% increased risk of CVD and elevation in specific categories of coronary heart disease (CHD), cerebrovascular disease, congestive heart failure, and CVD death [78]. Meta-analyses have also pointed to the relationship of anxiety with a higher risk of CHD, cardiac death, CVD events, and stroke [79; 74].
Indirect pathway between psychological factors and coronary heart disease
A wide array of studies has indicated that part of the relationship between psychological factors and coronary heart disease is "indirect." In order to explain this finding, it should be stated that psychological factors form part of the significant relationship with coronary heart disease through physiological and behavioral factors, and the two variables of unhealthy behaviors and physiological factors can play a mediating role in this relationship.
Indirect pathway between social factors and coronary heart disease
The findings of this research pinpointed that social factors, taking into account the role of mediators (physiological responses and health-related behaviors), can indirectly affect coronary heart disease, and a significant part of the relationship between these factors and the severity of coronary heart disease is "indirect." In other words, psychological factors affect behavior, which in turn exert their effect on the severity of coronary heart disease through physiological responses. This research finding suggests that the mind can affect the body. Nonetheless, another point in the explanation of the comparison of the two methods of answering questions 4 and 5 is that entering any latent or observed variable into each analysis affects the behavior of other variables. Therefore, each model with its variables must be analyzed and explained.
Conclusions
Psychological components can be considered as underlying factors as well as consequences of cardiovascular diseases. It was also found that psychological processes are related to this category of diseases both directly (influence on physiological processes) and indirectly (influence on behavior and lifestyle)
The results of structural equation modeling have shown that psycho-social variables and other factors related to unhealthy behaviors such as smoking, physical activity and blood lipid. play a significant role in predicting coronary heart disease
The management of these psychological processes can be effective in reducing the causes of cardiovascular diseases as well as reducing their consequences and negative prognosis. In the end, it can be said that the mentioned cases and the results of various researches show the role of psychosocial factors in preventing, treating and reducing the effects of cardiovascular problems as the biggest health problem in the world.
Acknowledgments
This research is the result of a doctorate thesis submitted to Payam Noor University. The author's most profound appreciation goes to the Vice-Chancellor of Research and Technology of Shahid Beheshti University of Medical Sciences in Tehran and Iran, as well as the respected personnel of the Cardiology Department of Shahid Modares, Taleghani, and Farhikhtegan hospitals in Tehran, and Imam Khomeini Hospital in Ardabil for their cooperation, and Mrs. Niloofar Valizadeh, our colleague.
Authorsʼ contributions
All authors contributed equally to the preparation of all parts of the research.
Funding/Support
This article was extracted from a PhD dissertation on health psychology submitted by the first author, Ahmad Alipour. Moreover, this study was approved by the Ethics Committee of Payam Noor University (IR. PNU. REC. 1401. 055).
Conflicts of Interest
The authors declare no conflict of interest in this study.
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As illustrated in Table 8, the bootstrap test was used to evaluate the prediction of the severity of coronary heart disease by social factors. It measures the indirect relationship between social factors and the severity of coronary heart disease through the mediation of physiological responses and health-related behaviors. As displayed in this table, all four mediating paths are significant. Moreover, except for the mediating effect of social support on heart disease through the mediation of physiological responses, which is not significant, the remaining mediating effects are significant.
Discussion
The present study aimed to assess the effect of psychosocial factors on coronary heart disease medicated by physiological responses and health-related behaviors. To this end, structural equation modeling was used according to the research conducted in the fourth chapter. This method consists of two parts: the "measurement model" and the "structural model." Examining the fit indices of the model demonstrated that the smoothed chi-square is less than five, and the optimal values of the comparative fit index (CFI), model fit index (GFI), and Adjusted Goodness of Fit Index (AGFI) are greater than 90%. Moreover, the root mean square error of approximation (RMSEA) is less than 8%.
The comparison of the collected data with the approved criteria demonstrated that, in general, the structural model of the current research "fits" the collected data well. In other words, based on the conceptual model of the research, psychosocial factors have an effect on coronary heart disease, and part of this effect is exerted through the mediation of health-related behaviors and physiological responses. Coronary heart disease is the narrowing of the coronary arteries that supply blood and oxygen to the heart. Due to the accumulation of atheroma and plaque in the arteries, the process is called atherosclerosis.
Physiological mechanisms include the buildup of atherosclerotic plaques in the walls of arteries as a result of inflammatory processes, lipid abnormalities, such as increased low-density lipoprotein cholesterol (LDLc), decreased high-density lipoprotein (HDL), and high triglycerides (TAG), decreased vasodilation and increased risk of thrombosis, endothelial dysfunction and changes in the endothelial lining of blood vessels of the cardiovascular system, high levels of homocysteine (Hcy), which is associated with increased LDLc, and a decrease in nitric oxide produced in endothelial cells, which causes vasodilation [58].
In explaining this finding, several studies have pinpointed that apart from its known role in promoting atherosclerosis in blood vessels, hyperlipidemia may directly affect the heart, leading to increased ischemia/reperfusion injury and poor response to cardiac protective interventions, such as ischemic preconditioning [59]. Further investigation suggested that the correlation between high cholesterol and increased risk of cardiovascular events is mainly related to low-density lipoprotein (LDL)-cholesterol (LDL-C). On the contrary, HDL-C is inversely correlated with mortality from coronary heart disease [60,61]. Accordingly, the "cholesterol hypothesis" was developed, which proposes that LDL-C is the cause of atherosclerosis, and as a result, reduced LDL-C lowers the risk of myocardial infarction and other cardiovascular events.
*The path coefficient between unhealthy behaviors and the severity of coronary heart disease is significant at 1% (P<1%, B=0.38).
In this research, from health-related behaviors, only unhealthy behaviors were evaluated. Unhealthy behavior consists of smoking, unhealthy diet, unhealthy additives (fat, sugar, and salt), and physical inactivity. According to Table [4-12], the test results show that unhealthy behaviors have a positive and significant relationship with coronary heart disease. In order to discuss and analyze this research finding, unhealthy behavior is considered in the form of smoking, nutrition, and physical activity. In explaining these findings, it can be stated that significant biological evidence shows that the components of cigarette smoke lead to endothelial dysfunction, cell dysfunction, arteriosclerosis, acute thrombosis, and impaired oxygen-carrying capacity of the blood [39]. Scientific findings indicated that improper nutrition is one of the most important risk factors in cardiovascular disease [60-63]. A high intake of trans-fatty acids is associated with an increased risk of cardiovascular diseases [64]. The relationship between nutrition and coronary heart disease can be explained by cholesterol being the main nutritional factor in coronary heart disease. The body makes most of it in the blood, and only about 20% of the cholesterol in the bloodstream comes from our food. Getting too much dietary cholesterol increases LDL. Nonetheless, its negative impact is less than saturated fatty acids. Most foods containing saturated fats, especially animal and solid fats, are a rich source of cholesterol, and their limited consumption leads to a decrease in cholesterol [65].
Moreover, in explaining the relationship between physical inactivity and coronary heart disease, it can be stated that a sedentary lifestyle causes obesity, increasing insulin resistance, blood glucose levels, plasma lipids, and prothrombotic factors [56]. Diet plays a critical role in creating the background for the risk factors of cardiovascular diseases. Recent studies have also provided evidence on the relationship of dietary patterns with chronic diseases and the risk of death. Furthermore, the results of research in recent decades demonstrated that drug abuse, smoking, unhealthy diet, physical inactivity, obesity, high blood pressure, and lipid abnormalities are considered risk factors for cardiovascular disease, especially coronary heart disease [66-72].
Psychological factors and coronary heart disease
The presented studies are only a part of the findings related to the role of psychosocial factors in coronary heart disease, and now, some meta-analyses and systematic reviews are being conducted on psychosocial variables. In order to explain these findings, it can be stated that psychosocial factors are one of the risk factors for coronary heart disease [73, 74], and this relationship is illustrated in two physiological and behavioral ways [75, 76]. In order to physiologically explain the relationship between psychosocial factors and coronary heart disease, the following can be mentioned:
Although the underlying mechanisms are unclear, depression has been linked to physiological and psychosocial changes that are detrimental to the cardiovascular system [77]. A meta-analysis conducted in 2017 associated major depressive disorder with a 72% increased risk of CVD and elevation in specific categories of coronary heart disease (CHD), cerebrovascular disease, congestive heart failure, and CVD death [78]. Meta-analyses have also pointed to the relationship of anxiety with a higher risk of CHD, cardiac death, CVD events, and stroke [79; 74].
Indirect pathway between psychological factors and coronary heart disease
A wide array of studies has indicated that part of the relationship between psychological factors and coronary heart disease is "indirect." In order to explain this finding, it should be stated that psychological factors form part of the significant relationship with coronary heart disease through physiological and behavioral factors, and the two variables of unhealthy behaviors and physiological factors can play a mediating role in this relationship.
Indirect pathway between social factors and coronary heart disease
The findings of this research pinpointed that social factors, taking into account the role of mediators (physiological responses and health-related behaviors), can indirectly affect coronary heart disease, and a significant part of the relationship between these factors and the severity of coronary heart disease is "indirect." In other words, psychological factors affect behavior, which in turn exert their effect on the severity of coronary heart disease through physiological responses. This research finding suggests that the mind can affect the body. Nonetheless, another point in the explanation of the comparison of the two methods of answering questions 4 and 5 is that entering any latent or observed variable into each analysis affects the behavior of other variables. Therefore, each model with its variables must be analyzed and explained.
Conclusions
Psychological components can be considered as underlying factors as well as consequences of cardiovascular diseases. It was also found that psychological processes are related to this category of diseases both directly (influence on physiological processes) and indirectly (influence on behavior and lifestyle)
The results of structural equation modeling have shown that psycho-social variables and other factors related to unhealthy behaviors such as smoking, physical activity and blood lipid. play a significant role in predicting coronary heart disease
The management of these psychological processes can be effective in reducing the causes of cardiovascular diseases as well as reducing their consequences and negative prognosis. In the end, it can be said that the mentioned cases and the results of various researches show the role of psychosocial factors in preventing, treating and reducing the effects of cardiovascular problems as the biggest health problem in the world.
Acknowledgments
This research is the result of a doctorate thesis submitted to Payam Noor University. The author's most profound appreciation goes to the Vice-Chancellor of Research and Technology of Shahid Beheshti University of Medical Sciences in Tehran and Iran, as well as the respected personnel of the Cardiology Department of Shahid Modares, Taleghani, and Farhikhtegan hospitals in Tehran, and Imam Khomeini Hospital in Ardabil for their cooperation, and Mrs. Niloofar Valizadeh, our colleague.
Authorsʼ contributions
All authors contributed equally to the preparation of all parts of the research.
Funding/Support
This article was extracted from a PhD dissertation on health psychology submitted by the first author, Ahmad Alipour. Moreover, this study was approved by the Ethics Committee of Payam Noor University (IR. PNU. REC. 1401. 055).
Conflicts of Interest
The authors declare no conflict of interest in this study.
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Article Type: Research Article |
Subject:
Physiology
Received: 2023/11/2 | Accepted: 2024/01/4 | Published: 2024/05/13
Received: 2023/11/2 | Accepted: 2024/01/4 | Published: 2024/05/13
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