|Year : 2018 | Volume
| Issue : 3 | Page : 86-92
Association of depression, anxiety, and stress with myocardial infarction: A case–control study
MT Manoj MSW, MBA (HM), PhD Scholar 1, KA Joseph MSW, PhD 2, Govindan Vijayaraghavan MD, DM (Cardio) 3
1 Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu; Department of Post Graduate Studies and Cardiology, Kerala Institute of Medical Sciences, Trivandrum, Kerala, India
2 Department of Social Work, Loyola College of Social Sciences, Trivandrum, Kerala, India
3 Department of Post Graduate Studies and Cardiology, Kerala Institute of Medical Sciences, Trivandrum, Kerala, India
|Date of Web Publication||10-Jul-2018|
Mr. M T Manoj
Kims Hospital, Anayara PO, Trivandrum - 695 029, Kerala
Source of Support: None, Conflict of Interest: None
Background: Myocardial infarction (MI), the most common cardiovascular disease, has assumed an epidemic proportion today. Higher prevalence of MI is reported from India (a low-middle income country) with the state of Kerala topping the list. Limited data exist on the impact of psychosocial factors on MI in India. Materials and Methods: A total of 100 cases (with MI) and 100 controls (without MI and matched for age and gender) were selected using consecutive sampling from a tertiary hospital in Trivandrum, Kerala, India. Data on depression, anxiety and stress were collected using the depression, anxiety and stress scales (DASS 21). Chi-square test was used to study the association of the variables under study with MI. Multivariate logistic regression was used to control for confounders. The unadjusted and adjusted odds ratios (OR) and 99% confidence intervals (CI) were estimated. Results: Depression (35% vs. 20%, P = 0.024), anxiety (41% vs. 14%, P < 0.001) and stress (36% vs. 15%, P = 0.002) had a statistically significant association with MI on comparing cases vs. controls. Higher levels of depression, anxiety and stress were associated with an increased risk of MI with OR of 2.790, 6.429, and 3.470, respectively. Conclusion: Depression, anxiety and stress were associated with MI. Prospective studies are required to confirm our findings.
Keywords: Anxiety, association, depression, myocardial infarction, stress
|How to cite this article:|
Manoj M T, Joseph K A, Vijayaraghavan G. Association of depression, anxiety, and stress with myocardial infarction: A case–control study. J Clin Prev Cardiol 2018;7:86-92
|How to cite this URL:|
Manoj M T, Joseph K A, Vijayaraghavan G. Association of depression, anxiety, and stress with myocardial infarction: A case–control study. J Clin Prev Cardiol [serial online] 2018 [cited 2021 May 16];7:86-92. Available from: https://www.jcpconline.org/text.asp?2018/7/3/86/236330
| Introduction|| |
Noncommunicable diseases (NCDs) are one of the major health challenges of the 21st century. Of the 56 million deaths worldwide in 2012, 38 million were due to NCDs, mainly cardiovascular diseases (CVDs), cancer, and chronic respiratory diseases. The majority of these NCD deaths (28 million) took place in low-and-middle income countries. An increase in the NCD deaths from 6.7 million in 2000 to 8.5 million in 2012 is reported in Southeast Asia and such deaths are further projected to reach 52 million by 2030., Among the NCD deaths, CVDs account for 17.5 million (46.2% of NCD deaths).
A rising trend in CVD-related deaths –20.6% deaths in 1990, 21.4% in 1995, 24.3% in 2000, 27.5% in 2005, and 29.0% in 2013 – has been reported in India. Ischemic heart disease and stroke account for 83% of CVD mortality and are jointly responsible for 21.1% of all deaths and one-tenth of the years of life lost in India (years of life lost has increased from 23.3 million in 1990 to 37 million in 2010).
Kerala, having a population of over 33 million, holds the highest prevalence rate of risk factors associated with coronary artery disease (CAD) in India. The age-adjusted CAD mortality rates per 100,000 are 382 for men and 128 for women. These rates are higher as compared to those seen in industrialized countries and 3–6 times higher than Japanese and rural Chinese. The overall age-adjusted prevalence of definite CAD is 3.5% (4.8% in men and 2.6% in women) (P< 0.001) among the rural and urban population. A dramatic increase of premature (before the age of 65 years) is reported in Kerala (males: ~60%, females: 40%). The significance of this rate is clear when compared with the 18% of the United States. Moreover, these rates are higher than that of rural Andhra Pradesh and similar to urban Chennai.,
Similar to NCDs, mental or behavioral disorders pose a great challenge. Around 450 million people across the world suffer from either of these disorders. Among these, neuropsychiatric disorders (depression, alcohol-use disorders, schizophrenia, and bipolar disorder) are four of the six leading causes of years lived with disability, and they affect 10% of the total world population. The number of people suffering from depressive and/or anxiety disorders has increased from 416 million to 615 million between 1990 and 2013, an increase of 50% in 13 years). The lifetime prevalence of depression among adults in developed countries is 14.6% and in low-and-middle income countries is 11.1% with India reporting 35.9%. The current prevalence rate of anxiety disorders across the world ranges between 0.9% and 28.3% whereas reported in the past 1 year ranged between 2.4% and 29.8%.
The National Mental Health Survey of India has reported that the current and life time-weighted prevalence of depression in India is 2.7% and 5.2%, respectively. Neurosis and stress-related disorders are present in 3.5% of the population. This indicates that 34/1000 population (range 0.5-53) suffer from depression and 16.5/1000 population (range: 11–70) suffer from anxiety. A similar prevalence rate is reported in another study with depression in 31.2/1000 population (range: 0.5–53) and anxiety neurosis in 18.5/1000 population (range: 11–70).
Mental health and physical health are essentially linked. People living with severe mental disorders are at higher risk of suffering from many physical disorders. Mental or psychological disorders such as depression, anxiety, and some personality types may lead to direct pathophysiological changes increasing the risk of developing CVD.
Depression is a causative factor for the incidence of coronary heart diseases (CHDs) in healthy people. Janszky et al. in a case–control study reported that people with depression are at 2.9 (95% confidence interval [CI]:1.8–4.9) times higher risk of acute myocardial infarction (MI). Another study revealed that people with the baseline depression are at increased risk of CHD (hazard ratio [HR]: 1.43; (95% CI: 1.10–1.87). This was reaffirmed in another meta-analysis which reported an overall relative risk of 1.64 (95% CI: 1.29–2.08) for the development of CHD in depressed patients.
Further, Janszky et al. also reported that people who are anxious are at higher risk of developing CHD. Their study found out that anxious people are at 2.17 (95% CI: 1.28–3.67) times increased risk of CHD and 2.51 (95% CI: 1.38–4.55) times increased risk for MI. Roest et al., in a meta-analysis, concluded that anxious people are at increased risk of CHD (HR: 1.26; 95% CI: 1.15–1.38) and cardiac death (HR: 1.48; 95% CI: 1.14–1.92).
Similarly, people who are exposed to several episodes of stress and permanent stress are at increased risk of acute MI, odds ratio (OR): 1.45 (99% CI: 1.30–1.61) and OR: 2.17 (95% CI: 1.84–2.55), respectively. The employees with higher job strain reported a relative risk of 1.43 (95% CI: 1.15–1.84) for CHD as compared with employees who had low strain.
It is important to note that the majority of research on the association between mental or psychological factors and CHD has been focused on populations of Western/developed countries even though many of these risk factors are also found in non-Western/developing nations. Moreover, the recent evidence indicates that CHD incidence and mortality are unevenly distributed within and across populations of both developed and developing countries. Overall, the current evidence indicates that the prevalence of depression, anxiety, and stress, as well as MI, is higher in India. Taking the seriousness of this issue into consideration, we decided to study the association between such psychosocial factors and MI.
To compare the level of depression, anxiety, and stress in patients with the first episode of MI with those in patients who do not have MI at a tertiary care hospital in Kerala.
| Materials and Methods|| |
Study design and setting
This was a hospital-based case–control study conducted between September 2016 and August 2017 at Kerala Institute of Medical Sciences (KIMS), a 650-beded multispecialty tertiary care hospital, located in Trivandrum district of Kerala, India.
Selection of participants
All consenting patients who presented with the first episode of MI diagnosed as per the standard protocol, with age between 25 and 65 years, and admitted to the hospital during the study period, were included in the study as incident cases. Patients with unproven MI, history of any cardiac disease, and/or current or past history of psychiatric illness, and those on antipsychotic medications and other major diseases (AIDS, cancer, chronic obstructive pulmonary disease [COPD], and physical deformations) were excluded. All consenting inpatients admitted to the General Medicine Department during the study period, with age between 25 and 65 years, and no history of MI or cardiac risk factors (e.g. diabetes) or major diseases (e.g. AIDS, cancer, COPD, and physical deformations) were selected as controls.
A standard demographic questionnaire for recording details on gender, domicile, age, religion, marital status, living status, income, educational status, and occupation along with details of consumption of alcohol, smoking, and regular physical exercise was used for the study.
The Depression Anxiety and Stress Scales (DASS) were used to assess depression, anxiety, and stress of the past 1 week. It is a self-reporting questionnaire with 21 items (seven items for each category) based on a four-point rating scale. It consists of three 7-item subscales with each item scoring on a four-point Likert scale, ranging from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time). The final result was obtained on each variable by adding up the items on each subscale and giving a score between 0 and 21. Scores above 10, 7, and 12 on the depression, anxiety, and stress subscales indicate severe levels. The scale has good convergent and discriminant validity and high internal consistency and reliability and has been previously used in the Indian population with Cronbach's alpha reported at 0.94, 0.88, and 0.93 for depression, anxiety, and stress, respectively.,
Based on the proportion of cases and controls with depression (91.5% and 65.3%, respectively) in a previous study in comparable setting, the sample size estimated for the present study was 73 in each group with 90% power and 99% CI. An additional 27 individuals, each of cases and control, were considered necessary to cover for dropouts or inability to find the correct match for cases. Therefore, a total of 100 cases and 100 controls were included in the study.
Consecutive patients (n = 100) admitted to the inpatient wards of cardiology with the first episode of MI and satisfying the inclusion criteria were enrolled into the study as “cases.” An equal number of age- and gender-matched consecutive patients, who satisfied the inclusion criteria, were selected from the inpatient wards of General Medicine Department as controls. Informed consent was obtained from both cases and controls before the start of the study. The study investigator completed the study pro forma using the hospital electronic medical records. The patients then completed the study questionnaires. The median time for administering time for the questionnaire was within 1 week of the presenting illness.
Statistical analysis was conducted using the Statistical Package for the Social Science (SPSS), Version 16.0. (Chicago, SPSS Inc). Descriptive analysis (frequencies, percentages for categorical variables) were conducted to describe the distribution of each demographic variable of cases and controls. The scoring pattern of the scale (normal, mild, moderate, severe, and extremely severe) was changed into three categories: normal, moderate (clubbing mild + moderate), and severe (severe + extremely), for facilitating the analysis. Multivariate logistic regression was used to control for confounding while assessing the association of depression, anxiety, and stress between the cases and controls. The 99% CI was used to estimate the precision of the OR.
Approval from the Institutional Human Ethics Committee of KIMS, Trivandrum, was obtained before the commencement of the study. Written informed consent was obtained from all cases and controls.
| Results|| |
The general demographic features of cases (n = 100) and controls (n = 100) are summarized in [Table 1]. There was no significant difference between cases and controls with respect to gender and age, well-matched study group. Significantly more proportion of the cases were seen to be living in urban setting (P = 0.001), and majority belonged to Hindu religion (P = 0.016) as compared to controls. The cases and controls were comparable with regards to marital status (P = 0.072), living status (P = 0.077), occupation (P = 0.137), and smoking (P = 0.128). However, statistically significant differences were noted in the income (P = 0.022), education (P = 0.010), alcohol consumption (P = 0.007), and regular exercise status (P = 0.001) between cases and controls.
Among cases, 35% were in severe depression as against the 20% in the control group, 41% had severe anxiety as against the 14% in the control group, and 36% had severe stress as against the 15% of the controls [Table 2] and [Figure 1]. Depression, anxiety, and stress were statistically significantly associated with MI; P = 0.024, 0.001, and 0.002, respectively [Table 2].
|Table 2: Association of psychosocial risk factors and myocardial infarct|
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|Figure 1: Comparison of the severity of depression, anxiety and stress (Cases vs controls)|
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The results of multivariate regression analysis including the unadjusted and adjusted ORs are shown in [Table 3] to illustrate the difference before and after adjusting the confounders. The analysis before adjusting for confounders showed that the odds of exposure to depression, anxiety, and stress among cases were higher than those among controls (OR: 2.760, 5.423, and 3.600, respectively). Further analysis after adjusting for gender, domicile, age, religion, income, education, alcohol smoking, and physical exercise revealed an increased OR of depression (2.760 vs. 2.790) and anxiety (5.423 vs. 6.429). The OR of stress decreased by a small amount (3.600 vs. 3.470) but still remained a significant factor.
|Table 3: Impact of depression, anxiety, and stress on cases versus controls|
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| Discussion|| |
The results of our study indicate that depression, anxiety, and stress have a statistically significant association with MI. Furthermore, higher levels of depression, anxiety, and stress were associated with an increased risk of MI.
Majority of the participants in our study were males within the age group of 46–55 years which is in agreement with the findings of the previous studies by Anand et al., Lerner and Kannel, and Tunstall-Pedoe et al. These investigators reported that males in the higher age group have a greater risk of MI compared with females. Alcohol consumption was found to be higher among cases in our study. A similar trend has been reported by Bagnardi et al. and Leong et al. However, smoking was not found to be a significant factor in our study contrary to the findings of other studies reporting a positive association of smoking with MI.,
Depression is considered as an independent risk factor for the development of heart diseases and it doubles the risk to individuals who are otherwise healthy. The positive association of depression with MI in our study is consistent with the findings of studies by Janszky et al. and Majed et al. Our results are also supportive of the findings by Roest et al. and Rosengren et al. that anxiety and stress increase the risk of CHD.
Our results show that people with an increased level of depression, anxiety, and stress are at increased risk of MI as compared with people without any major risk factors of MI. These findings are similar to those reported by Ford et al., Wulsin and Singal, Gullette et al., Roest et al., and Emdin et al. The results are further substantiated by studies on pathophysiological evidence linking psychosocial factors to the incidence and the progression of cardiac events. Prolonged severe depression causes inflammation  leading to atherosclerosis and CVD. Similarly, constant anxiety is known to change cardiac rhythm and increase the risk of coronary artery spasm, eventually leading to atherosclerosis and coronary artery disease. Severe stress is known to increase atherosclerosis and the risk of coronary artery occlusion. The body responds to stress by releasing an excessive amount of norepinephrine and neurotransmitters, which damages myocardial nerve endings and increases the susceptibility to MI.
The strengths and limitations of our study need to be discussed. To the best of our knowledge, this is perhaps the first study assessing the influence of depression, anxiety, and stress upon MI in a setup such as Kerala. Considering the limited data on such important public health issues in such setups, we believe that our study makes a valuable contribution. The limitations of our study include its retrospective nonrandomized design, a relatively small sample size, and selection of participants from a hospital rather than a community. Furthermore, recall bias is also an important issue in case–control studies, and our use of logistic regression analysis does not assure that influence of all confounders has been ruled out. It is important to note that DASS-21 has not been used in cardiac inpatient settings and test–retest reliability of the questionnaire is yet to be established. Finally, considering the retrospective nature of the study, the previous mental status of both cases and controls were not evaluated or not known to the authors. Therefore, the possibility of overestimating the perceived levels of depression, anxiety, and stress of cases, who had an acute coronary event, cannot be ruled out.
| Conclusion|| |
Depression, anxiety, and stress were associated with MI in our study. Prospective studies are required to confirm our findings and to assess if measures against such psychosocial factors would affect the incidence of MI in similar setups.
We are grateful to Prof. A. Joseph, Director, Academics, (KIMS), Trivandrum (Tvm), Kerala, Prof. Sanjay Patole, Clinical Professor, King Edward Memorial Hospital for Women, Centre for Neonatal Research and Education, University of Western Australia, Perth and Dr. Naveen Jain, Coordinator, Department of Neonatology, KIMS, Tvm, for their unwavering support and sharing pearls of wisdom with us during the drafting of this article. We are also thankful to Ms. Neethu Benny, Biostatistician, KIMS, Tvm, for the support in statistical matters.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. Global Health Estimates: Deaths by Cause, Age, Sex and Country, 2000-2012. Geneva: WHO; 2014.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3:e442.
World Health Organization. Global Status Report on Non-Communicable Diseases 2014. Geneva: World Health Organization; 2014.
Registrar General of India. Causes of Deaths in India, 2001-2003. New Delhi, India: Office of the Registrar General; 2009.
Thankappan KR, Shah B, Mathur P, Sarma PS, Srinivas G, Mini GK, et al.
Risk factor profile for chronic non-communicable diseases: Results of a community-based study in Kerala, India. Indian J Med Res 2010;131:53-63.
] [Full text]
Krishnan MN, Zachariah G, Venugopal K, Mohanan PP, Harikrishnan S, Sanjay G, et al.
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.
Soman CR, Kutty VR, Safraj S, Vijayakumar K, Rajamohanan K, Ajayan K, et al.
All-cause mortality and cardiovascular mortality in Kerala state of India: Results from a 5-year follow-up of 161,942 rural community dwelling adults. Asia Pac J Public Health 2011;23:896-903.
Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, et al
. Executive summary: Heart disease and stroke statistics-2010 update: A report from the american heart association. 2010;121:e46-e215. DOI: 10.1161/CIRCULATIONAHA.109.192667
Joshi R, Chow CK, Raju PK, Raju R, Reddy KS, Macmahon S, et al.
Fatal and nonfatal cardiovascular disease and the use of therapies for secondary prevention in a rural region of India. Circulation 2009;119:1950-5.
Gajalakshmi V, Peto R. Verbal autopsy of 80,000 adult deaths in Tamil Nadu, South India. BMC Public Health 2004;4:47.
World Health Organization. WHO Health Statistics, Projections of Mortality and Causes of Death, 2015 and 2030. Geneva: World Health Organization; 2013.
Murthy RS. National mental health survey of India 2015-2016. Indian J Psychiatry 2017;59:21-6.
] [Full text]
Bromet E, Andrade LH, Hwang I, Sampson NA, Alonso J, de Girolamo G, et al.
Cross-national epidemiology of DSM-IV major depressive episode. BMC Med 2011;9:90.
Baxter AJ, Scott KM, Vos T, Whiteford HA. Global prevalence of anxiety disorders: A systematic review and meta-regression. Psychol Med 2013;43:897-910.
Ganguli HC. Epidemiological findings on prevalence of mental disorders in India. Indian J Psychiatry 2000;42:14-20.
] [Full text]
Madhav M. Epidemiological study of prevalence of mental disorders in India. Indian J Community Med 2001;26:198200.
Patten SB. Long-term medical conditions and major depression in the Canadian population. Can J Psychiatry 1999;44:151-7.
Riba M, Wulsin L, Rubenfire M. Psychiatry and Heart Disease: The Mind, Brain, and Heart. Hoboken, NJ: Wiley-Blackwell; 2011.
Janszky I, Ahlbom A, Hallqvist J, Ahnve S. Hospitalization for depression is associated with an increased risk for myocardial infarction not explained by lifestyle, lipids, coagulation, and inflammation: The SHEEP study. Biol Psychiatry 2007;62:25-32.
Majed B, Arveiler D, Bingham A, Ferrieres J, Ruidavets JB, Montaye M, et al.
Depressive symptoms, a time-dependent risk factor for coronary heart disease and stroke in middle-aged men: The PRIME study. Stroke 2012;43:1761-7.
Rugulies R. Depression as a predictor for coronary heart disease. A review and meta-analysis. Am J Prev Med 2002;23:51-61.
Janszky I, Ahnve S, Lundberg I, Hemmingsson T. Early-onset depression, anxiety, and risk of subsequent coronary heart disease: 37-year follow-up of 49,321 young Swedish men. J Am Coll Cardiol 2010;56:31-7.
Roest AM, Martens EJ, de Jonge P, Denollet J. Anxiety and risk of incident coronary heart disease: A meta-analysis. J Am Coll Cardiol 2010;56:38-46.
Rosengren A, Hawken S, Ounpuu S, Sliwa K, Zubaid M, Almahmeed WA, et al.
Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): Case-control study. Lancet 2004;364:953-62.
Kivimäki M, Virtanen M, Elovainio M, Kouvonen A, Väänänen A, Vahtera J, et al.
Work stress in the etiology of coronary heart disease – A meta-analysis. Scand J Work Environ Health 2006;32:431-42.
Reddy KS, Yusuf S. Emerging epidemic of cardiovascular disease in developing countries. Circulation 1998;97:596-601.
Cannon CP, Brindis RG, Chaitman BR, Cohen DJ, Cross JT Jr., Drozda JP Jr., et al.
2013 ACCF/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes and coronary artery disease: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Acute Coronary Syndromes and Coronary Artery Disease Clinical Data Standards). Circulation 2013;127:1052-89.
Lovibond SH, Lovibond PF. Manual for the Depression Anxiety Stress Scales. 2nd
ed. Sydney: Psychology Foundation of Australia; 1995.
Chandrasekhar K, Kapoor J, Anishetty S. A prospective, randomized double-blind, placebo-controlled study of safety and efficacy of a high-concentration full-spectrum extract of ashwagandha root in reducing stress and anxiety in adults. Indian J Psychol Med 2012;34:255-62.
] [Full text]
Var FA, Rajeswaran J. Perception of illness in patients with traumatic brain injury. Indian J Psychol Med 2012;34:223-6.
] [Full text]
Sattar KA, Qidwai W, Nanji K. Psychosocial risk factors for acute myocardial infarction: Results of a case-control study in a teaching hospital at Karachi, Pakistan. Acta Psychopathol 2015;1:3.
Kumar RB, Dudala SR, Rao AR. Kuppuswamy's socioeconomic status scale – A revision of economic parameter for 2012. Int J Res Dev Health 2013;7:2-4.
Anand SS, Islam S, Rosengren A, Franzosi MG, Steyn K, Yusufali AH, et al.
Risk factors for myocardial infarction in women and men: Insights from the INTERHEART study. Eur Heart J 2008;29:932-40.
Lerner DJ, Kannel WB. Patterns of coronary heart disease morbidity and mortality in the sexes: A 26-year follow-up of the Framingham population. Am Heart J 1986;111:383-90.
Tunstall-Pedoe H, Kuulasmaa K, Amouyel P, Arveiler D, Rajakangas AM, Pajak A, et al.
Myocardial infarction and coronary deaths in the World Health Organization MONICA project. Registration procedures, event rates, and case-fatality rates in 38 populations from 21 countries in four continents. Circulation 1994;90:583-612.
Bagnardi V, Rota M, Botteri E, Tramacere I, Islami F, Fedirko V, et al.
Alcohol consumption and site-specific cancer risk: A comprehensive dose-response meta-analysis. Br J Cancer 2015;112:580-93.
Leong DP, Smyth A, Teo KK, McKee M, Rangarajan S, Pais P, et al.
Patterns of alcohol consumption and myocardial infarction risk: Observations from 52 countries in the INTERHEART case-control study. Circulation 2014;130:390-8.
Teo KK, Ounpuu S, Hawken S, Pandey MR, Valentin V, Hunt D, et al.
Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study: A case-control study. Lancet 2006;368:647-58.
Grundtvig M, Hagen TP, Amrud ES, Reikvam A. Mortality after myocardial infarction: Impact of gender and smoking status. Eur J Epidemiol 2011;26:385-93.
Srinivasan K. “Blues” ain't good for the heart. Indian J Psychiatry 2011;53:192-4.
] [Full text]
Ford DE, Mead LA, Chang PP, Cooper-Patrick L, Wang NY, Klag MJ, et al.
Depression is a risk factor for coronary artery disease in men: The precursors study. Arch Intern Med 1998;158:1422-6.
Wulsin LR, Singal BM. Do depressive symptoms increase the risk for the onset of coronary disease? A systematic quantitative review. Psychosom Med 2003;65:201-10.
Gullette EC, Blumenthal JA, Babyak M, Jiang W, Waugh RA, Frid DJ, et al.
Effects of mental stress on myocardial ischemia during daily life. JAMA 1997;277:1521-6.
Emdin CA, Odutayo A, Wong CX, Tran J, Hsiao AJ, Hunn BH, et al.
Meta-analysis of anxiety as a risk factor for cardiovascular disease. Am J Cardiol 2016;118:511-9.
Maes M, Bosmans E, De Jongh R, Kenis G, Vandoolaeghe E, Neels H, et al.
Increased serum IL-6 and IL-1 receptor antagonist concentrations in major depression and treatment resistant depression. Cytokine 1997;9:853-8.
Bot I, de Jager SC, Zernecke A, Lindstedt KA, van Berkel TJ, Weber C, et al.
Perivascular mast cells promote atherogenesis and induce plaque destabilization in apolipoprotein E-deficient mice. Circulation 2007;115:2516-25.
Esler M. The sympathetic system and hypertension. Am J Hypertens 2000;13:99S-105S.
Matthews KA, Owens JF, Kuller LH, Sutton-Tyrrell K, Lassila HC, Wolfson SK, et al.
Stress-induced pulse pressure change predicts women's carotid atherosclerosis. Stroke 1998;29:1525-30.
Cebelin MS, Hirsch CS. Human stress cardiomyopathy. Myocardial lesions in victims of homicidal assaults without internal injuries. Hum Pathol 1980;11:123-32.
Gersh BJ, Bassendine MF, Forman R, Walls RS, Beck W. Coronary artery spasm and myocardial infarction in the absence of angiographically demonstrable obstructive coronary disease. Mayo Clin Proc 1981;56:700-8.
[Table 1], [Table 2], [Table 3]
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