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Cardiovascular disease (CVD)
CVD is a group of diseases that affect either the heart or the blood vessels: rheumatic heart disease, coronary heart disease (CHD), cerebrovascular disease (including stroke), peripheral arterial disease, congenital heart disease (heart disease at birth) and cardiomyopathies (World Health Organization, 2017, May 17). The most common type is coronary heart disease. It is the blockage or narrow of the heart arteries due to atherosclerosis which is an accumulation of fatty deposits (i.e. cholesterol) on the blood vessels’ inner walls causing angina pectoris (chest pain) or heart attack (myocardial infarction (MI) (World Health Organization, 2017, May 17).
CVD is a leading cause of death worldwide according to the World Health Organization (WHO) (World Health Organization, 2017, May 17). For instance, in 2016, worldwide, CVD contributed to 31% of total mortality, almost 17.9 million deaths. These deaths were mainly due to stroke and heart attack since both of them represented 85% of these deaths (World Health Organization, 2017, May 17). The number of CVD deaths is projected to reach 23.6 million by 2030 (World Health Organization). In France, CVD is the second leading cause of death with approximately 140,000 deaths per year (Ministère des Solidarités et de la Santé, 2017, November 10) and contributed to 27% of all deaths in 2011 (Tzoulaki et al., 2016).
There are multiple traditional risk factors associated with CVD and mainly with stroke and heart attacks (World Health Organization, 2017, May 17) and they can be classified as non-modifiable and modifiable risk factors. The main non-modifiable risk factors are family history of CVD, male sex, increase in age and ethnicity. The main modifiable risk factors include behavioral risk factors such as smoking, lack of physical activity and alcohol use as well as biological risk factors such as hypertension, diabetes, dyslipidemia and obesity (World Health Organization, 2017, May 17). Adults with hypertension and diabetes are estimated to reach 1.56 billion cases in 2025 (Kearney et al., 2005) and 629 million cases in 2045 (International Diabetes Federation, 2017) respectively, and hypercholesterolemia contributes to 29.7 million cases annually (World Health Organization, 2017). As well, diabetes contributed to 1.5 million deaths in 2012 (World Health Organization, 2016), hypertension and hypercholesterolemia contributed to 7.5 million (World Health Organization, 2009) and 2.6 million deaths (World Health Organization, 2017) annually respectively. In other terms, these three conditions contribute to 68% of all deaths (World Health Organization, 2014). Moreover, hypertension, diabetes, hypercholesterolemia, smoking and obesity account for 9.7 million CVD deaths annually worldwide, and they are the most prevalent in Central and Eastern Europe (Tzoulaki et al., 2016). Around 60% of the global CVD deaths were at age >70, and the rest were at age between 30-70. Most of these CVD deaths result mainly from hypertension, then followed by smoking in men and obesity in women (Tzoulaki et al., 2016). Beside these traditional risk factors, some psychological risk factors which are also modifiable could be associated with CVD such as psychological stress, anxiety, depression and others (Lane, Carroll, Ring, Beevers, & Lip, 2000; Nicholson, Kuper, & Hemingway, 2006; World Health Organization, 2017, May 17).
The modifiable traditional cardiovascular risk factors can be treated, and evidence showed that the risk of CVD decreases after treating and managing these risk factors (Tzoulaki et al., 2016). For instance, smoking cessation, changing in diet such as increase consumption of vegetables and fruits and decrease consumption of salt, increase physical activity, are associated with decrease risk of CVD (Tzoulaki et al., 2016), partly because of their favorable effects on the control for each of hypertension, diabetes and dyslipidemia. Hypertension, diabetes and dyslipidemia are also controlled and managed by established pharmacologic treatments. In this PhD thesis, they were referred as treatable cardiovascular risk factors.
Finally, in this PhD thesis, we focused on psychological risk factors and mainly on depression and we wanted to study its association with the increased risk of CVD.
Depression and CVD
Depression is a serious mental health disorder (World Health Organization, 2018, March 22) known either by clinical depression or major depressive disorder (MDD) (The National Institute of Mental Health, 2018). It is not similar to the person’s usual responses to his/her daily activities in terms of feelings, emotions and mood fluctuations (World Health Organization, 2018, March 22). In order to be diagnosed with depression, individuals must have severe symptoms at least all days for at least two weeks that affect their appetite, sleep, function at school, work and in their families. In other terms these symptoms affect the person’s ability to handle his/her daily activities.
Depression is the leading cause disability (World Health Organization, 2018, March 22) worldwide according to WHO. For instance, more than 300 million individuals are currently affected by depression (World Health Organization, 2018, March 22). In France, the prevalence of depression is estimated at 5 to 12% in the general population (Chan Chee et al., 2011). Depression causes functional impairment or disability in daily activities whether at school, in the workplace or in social relationships, leading to economic and social burden (World Health Organization, 2018, March 22). For instance, depression could lead to absenteeism and presenteeism which both result in employment cessation. It also reduces the social interactions with family members, coworkers or/and friends (interpersonal relationships), and contributes to loss of interest in maintaining household responsibilities including financial ones. In addition, if depression is not treated and severe, it can lead to suicide which was the eighteenth leading cause of death in the general population in 2016 (World Health Organization, 2018). For instance, around 800 thousand deaths per year are due to suicide which is equivalent to 1 person dies every forty seconds worldwide.
Depression and CVD are highly comorbid especially in the general population. This comorbidity could be explained to some extent by shared risk factors (e.g. tobacco consumption (An & Xiang, 2015; Dierker, Avenevoli, Stolar, & Merikangas, 2002; Yun, Shin, Kweon, Ryu, & Rhee, 2012). The association between these two conditions could also be bi-directional. According to previous epidemiological studies, there is a bidirectional association between depression and incidence of CVD: depressed patients have a higher risk of sudden cardiac death, overall cardiovascular mortality and new onset morbidity than those non-depressed (Case, Sawhney, & Stewart, 2018; Dong, Zhang, Tong, & Qin, 2012; Ford et al., 1998; Hare, Toukhsati, Johansson, & Jaarsma, 2014; Van der Kooy et al., 2007) as well patients with CVD are at a higher risk of developing depression than those with no CVD (Freak-Poli, Ikram, Franco, Hofman, & Tiemeier, 2018; Huang, Dong, Lu, Yue, & Liu, 2010; Thombs et al., 2006). Indeed, according to previous prospective studies, depressed individuals are on average 1.5 to 2 times more likely to develop CVD incident cases compared to non-depressed (Nicholson et al., 2006).
Beyond shared risk factors (e.g. genetic risk factors, environmental hazards and others) that may confound the association between depression and increased risk of CVD morbidity and mortality, there are multiple mechanisms that could explain the causality of this association (Carney, Freedland, Miller, & Jaffe, 2002). It could be explained by biological pathways where depression could lead to alteration or changes in the autonomic nervous system triggering increased risk of CVD (de Jonge, Mangano, & Whooley, 2007; Veith et al., 1994). For example, the hypothalamic-pituitary-adrenal axis (HPA) and the autonomous nervous system may display functional abnormalities in depression. In addition, the biological pathways include reduce or absence of coagulation factors such as pro-inflammatory cytokines, plasminogen activator inhibitor-1 (PAI-1) and fibrinogen (Brouwers et al., 2013) dysregulation of the platelet reactivity (Ziegelstein, Parakh, Sakhuja, & Bhat, 2007), lower heart rate variability. Furthermore, there are other mechanisms which could explain the association between depression and increase CVD risk. Among these mechanisms, we focused on two in this PhD thesis. First, a potential confounding role of hostility: Depression and hostility are highly correlated (Stewart, Fitzgerald, & Kamarck, 2010; Suls & Bunde, 2005) and hostile traits could increase the subsequent risk of depression (Nabi, Singh-Manoux, et al., 2010), as well as the risk of CVD (Chida & Steptoe, 2009). This hypothesis leads to the following prediction:
1. The prospective association between depression and incident CVD will be explained by hostile traits.
Second, a potential mediating role of non-adherence to medications targeting treatable cardiovascular risk factors (i.e. hypertension, diabetes and dyslipidemia). This second hypothesis leads to two predictions:
2. The prospective association between depression and incident CVD will be of greater magnitude among participants who present with treatable cardiovascular risk factors than among those who do not.
3. The association of depression with incident CVD will be partly explained by poor adherence to preventive measures such as medications targeting treatable cardiovascular risk factors.
Hostile traits, depression and CVD
Hostility is a multidimensional personality construct which includes different characteristics such as aggression, impatience, ambition, anger and competitiveness. Hostility is a presumably stable trait factor and it is a proneness to experience hostile thoughts or display hostile behaviors in addition to irritability and negativism. Hostile thoughts (i.e. cognitive hostility) could encompass resentment or distrust whereas hostile behaviors (i.e. behavioral hostility) could be direct such as direct aggression, either verbal or physical, or indirect (e.g., spreading rumors mocking someone’s appearance). Therefore, the main hostile traits are cognitive hostility and behavior hostility, as well as irritability and negativism. The literature suggests that hostile traits could act as a confounder in the association between depression and CVD. In other terms, hostile traits could increase the risk of both developing depression and developing CVD, thus partially explaining their association.
Hostile traits could increase the risk of developing depression. A longitudinal study on 3,399 individuals aged between 35-55 years showed that cynical hostility measured at baseline was associated with incident depressive mood (Nabi, Singh-Manoux, et al., 2010). For instance, individuals with the highest quartile of cynical hostility were 4.66 times more likely to develop depressive mood (odds ratio (OR) of 4.66 and 95% confidence interval (CI) of 3.41-6.36) compared to those with the lowest quartile. In addition, depression was found to be correlated with cynical hostility (correlation coefficient=0.26, P<0.01) in a longitudinal study (Appleton et al., 2016). A longitudinal study on 296 healthy men and women aged between 50 and 70 showed that baseline cognitive hostility predicted depressive symptoms (β=0.15, P=0.004) over 6 years of follow-up (Stewart et al., 2010). Therefore, the authors emphasized on the importance to address hostility while studying the association between depression and cardiovascular outcomes. In other terms, to improve the cardiovascular outcomes, the interventions on depression should include hostility treatments to have a better impact on the outcomes.
Moreover, hostile traits could increase the risk of CVD. For instance, the last recent meta-analysis on this topic showed that anger and hostility combined together predict incident CHD in participants free of CHD at baseline with a hazard ratio (HR) of 1.19 (95% CI of 1.05-1.35) (Chida & Steptoe, 2009). This study, however, was not in line with at least one study (Sturmer, Hasselbach, & Amelang, 2006). Focusing on hostility only, overall hostility was associated with CVD or CHD incidence in several studies (Barefoot, Larsen, von der Lieth, & Schroll, 1995; Izawa et al., 2011; Meesters & Smulders, 1994; Miller, Smith, Turner, Guijarro, & Hallet, 1996; Myrtek, 2001), but not in other studies (Everson et al., 1997; Hearn, Murray, & Luepker, 1989; Smith, Glazer, Ruiz, & Gallo, 2004). Age differences may explain these discrepancies to some extent since some studies showed that hostility was associated with myocardial infarction in individuals younger than 50 (Izawa et al., 2011; Meesters & Smulders, 1994) and others in older populations (older than 50) (Barefoot et al., 1995). Most of these studies (Barefoot et al., 1995; Everson et al., 1997; Hearn et al., 1989; Izawa et al., 2011; Meesters & Smulders, 1994) measured hostility using the Cook-Medley Hostility Scale which measures cynical hostility and not overall hostility.
In addition to cynical hostility, some other hostile traits could be associated with adverse CVD outcomes. There is an inconsistency on the topic in the literature. Several studies showed a significant association between irritability and CVD (Fava, Cosci, & Sonino, 2017; Mendes de Leon, 1992; Perlis et al., 2005; Porcelli & Guidi, 2015; Siegman, Townsend, Civelek, & Blumenthal, 2000; Sirri et al., 2012; Sonino et al., 2004). When assessed with the Diagnostic Criteria for Psychosomatic Research (DCRP), the prevalence of irritable mood may be as high as 10-15% in medical patients, including patients with myocardial infarction (Fava et al., 2017). Another study showed that the rate of DCPR irritable mood was higher in patients with vs. without cardiac disease (Sirri et al., 2012). Moreover, in a case-control study in patients free of myocardial infarction and with a low socioeconomic status, irritability was associated with cardiac events (myocardial infarction and unstable angina) (Mendes de Leon, 1992). However, in a case-control study on men, irritability was not associated with myocardial infarction adjusting for age, smoking status and hypertension (Meesters, Muris, & Backus, 1996). Moreover, the observed hostility which is known as a behavioral hostility was positively associated with incidence of CHD (Newman et al., 2011). This study examined the association between observed hostility at baseline and the incidence of CHD for a follow-up period of 10 years on 1749 adults of the ‘1995 Canadian Nova Scotia Health Survey’ and found that participants with observed hostility were at a higher risk of developing CHD compared to their counterparts (adjusted HR=2.06, 95% CI= 1.04-4.08). This finding was not observed in Hearn, Murray and Luepker’s study (Hearn et al., 1989). However, another study on personality traits including hostility and CVD mortality in 2008 (Nabi et al., 2008) showed that CVD mortality was neither associated with total hostility nor cognitive hostility but it was associated with behavioral hostility after adjusting for age, sex, marital status and education (HR= 2.32, 95% CI=1.02-5.27).
Table of contents :
REMERCIEMENTS
LIST OF SUPPLEMENTARY FIGURES
LIST OF ABBREVATIONS
LIST OF PUBLICATIONS
RESUME LONG EN FRANҪAIS
ABSTRACT
1 CHAPTER I: GENERAL INTRODUCTION
2 CHAPTER II: LITERATURE REVIEW
2.1 CARDIOVASCULAR DISEASE (CVD)
2.2 DEPRESSION AND CVD
2.3 HOSTILE TRAITS, DEPRESSION AND CVD
2.4 DEPRESSION AND CARDIOVASCULAR RISK FACTORS
2.5 DEPRESSION AND POOR OR NON-ADHERENCE TO MEDICATIONS FOR TREATABLE CARDIOVASCULAR RISK FACTORS
3 CHAPTER III: DEPRESSION, HOSTILITY AND INCIDENT CARDIAC EVENTS IN THE GAZEL COHORT
4 CHAPTER IV: DEPRESSION, TREATABLE CARDIOVASCULAR RISK FACTORS AND INCIDENT CARDIAC EVENTS IN THE GAZEL COHORT
5 CHAPTER V: DEPRESSION AND NON-ADHERENCE TO TREATABLE CARDIOVASCULAR RISK FACTORS’ MEDICATIONS IN THE CONSTANCES COHORT
6 CHAPTER VI: DISCUSSION
6.1 SUMMARY OF THE RESULTS
6.1.1 Summary results of Chapter III
6.1.2 Summary results of Chapter IV
6.1.3 Summary results of Chapter V
6.2 CONTRIBUTIONS TO THE LITERATURE
6.3 CONCLUSION
6.4 PERSPECTIVES
7 REFERENCES
