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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES MEDICAL ACADEMY Jūratė Pečeliūnienė MOOD, ANXIETY DISORDERS AND SUICIDAL IDEATION IN PRIMARY CARE PATIENTS Doctoral Dissertation Biomedical Sciences, Medicine (06 B) Kaunas, 2011 The doctoral dissertation was prepared during 2006–2010 at the Institute of Psychophysiology and Rehabilitation, Academy of Medicine, Lithuanian University of Health Sciences. . Scientific Supervisor: Dr. Habil. Robertas Bunevičius (Medical Academy, Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06 B) Scientific consultant Prof. Dr. Leonas Valius (Medical Academy, Lithuanian University of Health Sciences, Biomedical Sciences, Public Health – 09 B) CONTENT LIST OF ABBREVIATIONS ........................................................................ 5 INTRODUCTION ......................................................................................... 7 1. REVIEW OF LITERATURE .................................................................. 13 1.1. The prevalence of mental disorders in a primary care population ... 13 1.2. Mood, anxiety disorders and suicide ideation in primary care patients ................................................................................................................. 16 1.3. Screening for depression and anxiety disorders in primary care ..... 20 1.4. Mental disorders and general medical conditions in primary care ... 24 1.4.1. The association of depression and anxiety disorders with general medical conditions ............................................................................... 26 1.4.2. Suicide ideation, mental disorders and general medical conditions ............................................................................................. 37 1.4.3. Thyroid immunity, blood pressure and body mass index in primary care patients ............................................................................ 42 1.4.4. Mental disorders and thyroid immunity in primary care ........... 43 2. MATERIALS AND METHODS ............................................................. 45 2.1. Subjects ............................................................................................ 45 2.2. Methods ............................................................................................ 47 3. RESULTS ................................................................................................ 53 3.1. Screening for depression and anxiety disorders in primary care patients .................................................................................................... 53 3.2. The prevalence of mental disorders in an adult primary care population ................................................................................................ 55 3.3. Suicidality and mental disorders in primary care ............................. 63 3.4. Mental disorders and general medical conditions in primary care ... 66 3.4.1. The association of depression and anxiety symptoms, with general medical conditions in primary care patients ............................ 66 3.4.2. The association of thyroid immunity with blood pressure and body mass index in primary care patients ............................................ 75 3.4.3. Mood and thyroid immunity assessed by ultrasonographic imaging in primary care ....................................................................... 79 4. DISCUSSION .......................................................................................... 83 4.1. Screening for depression and anxiety disorders in primary care patients .................................................................................................... 83 4.2. The prevalence of mood and anxiety disorders in primary care ...... 85 4.3. The prevalence of suicidal ideation in primary care ........................ 89 4.4. Mental disorders and general medical conditions in primary care ... 90 3 4.4.1. The association of depression, anxiety symptoms and suicidal ideation with general medical conditions in primary care patients ...... 97 4.4.2. The association of thyroid immunity with blood pressure and body mass index in primary care patients .......................................... 100 4.4.3. Mood and thyroid immunity assessed by ultrasonographic imaging in primary care ..................................................................... 103 CONCLUSIONS ........................................................................................ 105 PRACTICAL RECOMMENDATIONS .................................................... 106 REFERENCE LIST ................................................................................... 107 APPENDIXES ........................................................................................... 135 PUBLICATIONS ON THE DISSERTATION THEME ........................... 144 4 LIST OF ABBREVIATIONS ACE – angiotensin-converting enzyme AITD - autoimmune thyroid disease AUC- the area under the receiver operating characteristics curve BMI - body mass index BP – blood pressure CAD – coronary artery disease CHD – coronary heart disease CI(s) – confidence interval(s) CREATE - Тhe Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy CVD – cardiovascular disease DALYs - disability-adjusted life years DM – diabetes mellitus DSM–IV - the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition DSM-IV-TR - the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition text revision ECA - the Epidemiologic Catchment Area Study ECNP - European College of Neuropsychopharmacology Efficacy trial ESEMeD – the European Study of the Epidemiology of Mental Disorders EU – European Union EUGLOREH - Eropean Union Public Health Project Global Report on the Health Status in the European Union FP – family physician GAD – Generalized Anxiety Disorder GAD-7 – the Generalized Anxiety Disorder -7 scale GP – general practitioner HAD – Hospital Anxiety and Depression (Scale) HADS – Hospital Anxiety and Depression Scale HADS-A – Hospital Anxiety and Depression Scale Anxiety subscale HADS-D – Hospital Anxiety and Depression Scale Depression subscale HIV – Human immunodeficiency virus HR – heart rate INSERM - the Institut National de la Santé et de la Recherche Médicale study IPT – interpersonal psychotherapy 5 MD – Major Depression MDD – Major depressive disorder MDE – major depressive episode MI – myocardial infarction MINI – the Mini International Neuropsychiatric Interview MJA – Medical Journal of Australia N (n) – number NICE – the National Institute on Clinical Excellence OCD - obsessive-compulsive disorder OMH – the Office of Mental Health OR(s) – odds ratio(s) PC - primary care post-ACS HRV – post acute coronary syndrome heart rate variability PRIME-MD – Primary Care Evaluation of Mental Disorders PTSD - post-traumatic stress disorder ROC – the receiver operating characteristics RR - relative risk SADHART - Sertaline AntiDepressant Heart Attack Randomized Trial SCAN - Structured Clinical Assessment for Neuropsychiatric disorders SCID - the Structured Clinical Interview for DSM screening questionnaire for depressive symptoms SD – standard deviation SI – suicidal ideation SPSS 12.0 - Statistical Package for the Social Sciences 12.0 version SSRI – selective seratonin reabsorbtion inhibitor SUI – suicidal ideation TSH - thyroid stimulating hormone UK – United Kingdom USA – the United States of America WHO – the World Health Organization ZARADEMP – the Zaragoza Dementia and Depression Project 6 INTRODUCTION Mood and anxiety disorders as well as suicidal ideation are highly prevalent, unrecognized and untreated in general population as well as in primary care settings [4; 5; 7; 8; 23; 35; 51;112; 132, 134; 137; 138; 145; 158; 160; 161; 200; 202; 204; 208; 230; 245; 272]. Different studies consistently demonstrated that individuals with depression and anxiety disorders experience impaired physical and role functioning, more days in bed due to illness, more work days lost, increased impairment at work, and high use of health services [8; 159; 233; 261]. Disorders must be carefully monitored and treated because it is well known that depression as well as anxiety disorders has a negative but significant effect on the course, outcomes, longterm survival, and treatment efficacy of patients affected by physical disease [17; 78; 163; 271]. Common mental health disorders, such as depression, generalised anxiety disorder, panic disorder, obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD) and social anxiety disorder, may affect up to 15% of the population at any one time [(11i)]. Psychiatric comorbidity, or the concurrent clinical presentation of two or more diagnosable behavioural disorders, is the rule rather than the exception [29; 70]. The comorbidity of major depressive and anxiety disorders is associated with barriers to treatment and worse psychiatric outcomes, including treatment resistance, increased risk for suicide, greater chance for recurrence, and greater utilization of medical resources [1]. Epidemiological research has found that 45% of those who warrant at least one diagnosis also meet the criteria for one or more additional disorders [132]. Suicide, depression and addiction is recognised as a major public health issue [112; 124; 158; 159; 188; 202; 244; 266; 273; (7i); (11i)]. Nevertheless there is an evidence that the prevalence of common mental disorders and suicide varies across Europe and all over the world, the prevalence of mental illness continuing to increase internationally [112; 202; (7i); (8i)]. Suicide is a major public health problem and should be given high priority with regard to prevention and research. Mood and substance use disorders, in particular, have been found to frequently co-occur. Authors address that significant number of completed suicides is associated with mental disorders, especially with mood disorders and substance misuse [176; 183; 242; 243] and conclude that the link between common psychiatric comorbidities, alcohol misuse and suicidal behaviour is robust and the very complex issue [29]. 7 Primary care providers can perform a central role in bridging mental health and public health and have a unique opportunity to reduce the risk for onset of mental disorders [60] as primary care is usually the first point of contact for people with mental health and/or addiction issues. The vast majority (up to 90%) of depressive and anxiety disorders that are diagnosed are treated in primary care [(11i)]. In community samples, fewer than 25% of patients with psychiatric disorders see specialty mental health providers and the majority of patients are seen in primary care settings [5; 138; 139]. The literature clearly supports the view that primary care services have a key role in the provision of mental health services for those with mild to moderate mental health and/or addiction issues. Primary mental health care also has a role to play in supporting people with severe mental health issue. Luoma and colleagues found that over 50% of people who committed suicide had had health care contact within the month prior to their death [176], however most primary care clinicians do not routinely screen for suicide risk [111]. Anxiety and depression are the two most common mental health problems seen in primary care and are a major cause of distress and disability [7; 204; 208], but recognition of those mental conditions in primary care is poor [35; 230]. Effective recognition and treatment of anxiety and mood disorders in primary care may also positively impact on the economic burden of these disorders, may assist primary care physicians better understand the comorbidity issues and to prevent from severe mental health issues like suicide. Epidemiological surveys in primary care typically show that only 10% - 15% of primary care patients have well-defined anxiety or depressive disorders [63; 160; 298]. The disability caused by depression and anxiety is just as great as that caused by other common medical condition, such as hypertension, ischaemic heart disease, diabetes, and arthritis [159; 271; (7i)]. Primary care physicians need proper instruments for screening mental disorders. Several screening tools have been established to diagnose depressive and anxiety disorders in different populations [3; 28; 38; 47; 71; 79; 106; 120; 130; 153; 209; 255; 268; 282; (4i)], but not all of them are appropriate to use in a primary care setting. Useful instruments must be easily administered, inexpensive, and highly sensitive. Instruments used for screening emotional disorders in a busy primary care setting should avoid questions about somatic distress because this population is expected to have complaints concerning their physical health and these questions could bias the results of a screening [64; 152; 153; 232; 287]. Despite the prevalence, morbidity, and cost, psychiatric disorders continue to be underdiagnosed and treated incompletely in primary care settings, even though it was stated 8 that the prevalence of such disorders, including PTSD in primary care may indeed be higher than expected [157; 158; 298]. Routine mental health screening in primary care can detect possible symptoms of depression and other mental illness, much like a blood pressure test can identify possible cardiovascular risk factors. Making mental health checkups routine is key to early identification and critical to prognosis for those who suffer from mental illness [311; (6i)] Primary care clinicians who maintain a high index of suspicion for symptoms of depression or anxiety, or other signs of psychological distress, PTSD in their patients with positive histories of trauma plus suicidal thoughts or actions, alcohol or substance abuse, or excessive health care service utilization may increase the recognition rate of these disorders in their practices [157; 158; 160; (8i)]. There is still limited information that accounts for comorbidity on the impact of role disability associated with a wide range of mental and general medical conditions in primary care (PC) samples, as most research has been completed in the community and only rarely in PC samples [193]. Physicalmental comorbidity is very common in the general population and leads to a greater absenteeism from work than pure disorders that also cause personal and social problems [32; 290], further increases the disability experienced by sufferers, but there is a lack of research in primary health care [4; 159; (11i)]. As up to one third of patients presenting to primary care clinics with somatic complaints have a mood or anxiety disorder, they often remains hidden under the guise of somatic physical complaints so that the underlying mental condition is essentially untreated [230]. Many factors may conspire against the diagnosis of a mental health condition, particularly when patients present with a complicated somatic history [147; 159; 271; 289]. The early recognition of psychotic symptoms in patients with somatic illnesses, as well as somatic illness in patients primarily treated because of psychotic disorder concluded to be crucial by investigators [102; 143; 193]. The disability caused by depression and anxiety is just as great as that caused by other common medical condition, such as hypertension, ischaemic heart disease, diabetes, and arthritis [159; 271; (7i)]. Long-standing chronic medical conditions such as obesity, cardiovascular disease and diabetes mellitus, known to have major public health effects, are frequently found coexisting with mood and anxiety disorders [13; 20; 81; 118; 135; 159; 193; 236; 253; 271; 293]. On another hand, people with mental disorders have a higher prevalence of physical illnesses and reduced life expectancy [290], depression has long had a popular link to cardiovascular disease and death. However, only during the last 15 years scientific evidence supporting this common wisdom has been 9 available [89]. Obesity and common mental disorders, such as anxiety and depression, independently account for a substantial proportion of the global burden of disease and its associated economic costs, so it is important to determine the interaction between these conditions [12; 58; 199]. Depression occurs in up to one-quarter of patients with cardiovascular disease and diabetes. Depressed patients with heart disease have poorer medical outcomes including increased risk of reinfarction and all-cause mortality. Patients with diabetes and depression have poorer glycemic control, more diabetes symptoms, and greater all-cause mortality. Depression is associated with both biological (hypothalamic-pituitaryadrenal axis dysregulation) and psychosocial processes (adherence, poorer diet, and exercise) that may mediate adverse medical outcomes [68]. An association between mood disorders and thyroid immunity has been demonstrated in different studies [34; 40; 74; 100; 151; 216; 285], however, this has never been studied in an unselected medical population, such as in primary care patients. These studies suggest that an autoimmune thyroid disease (AITD), even without clinical or subclinical thyroid dysfunction, is related to mood and anxiety disorders. It has been demonstrated that thyroid autoimmunity is related to changes in general medical conditions such as body mass index (BMI) [256], to increased cardiovascular morbidity in general [180], or to specific cardiovascular dysfunction such as pulmonary arterial hypertension [46]. These findings indicate that autoimmune thyroid disease (AITD) may have significant impact on mental and physical health. The high prevalence and clinical consequences of mental as well as physical disorders, attention to their comorbidity, demonstrates the enormous significance of mental conditions to overall illness-related disability and should remain a clinical and research priority, especially in a primary care [147; 193; 247]. The aim of the study was to evaluate the prevalence and management of depressive disorders and anxiety disorders in primary care patients in association with suicidal ideation, thyroid autoimmunity and cardiovascular factors. The objectives of the study In detail, the objectives were: 1. To evaluate the Hospital Anxiety and Depression Scale (HADS) as screening instrument for depressive disorders and anxiety disorders in an adult primary care population. 2. To evaluate the prevalence and management of mental disorders in primary care population. 10 3. To evaluate factors affecting suicidal ideation (SI) in primary care patients. 4. To evaluate an association between mental disorders and general medical conditions in an adult primary care patients. 5. To evaluate an association of thyroid immunity with symptoms of depression, with symptoms of anxiety and with cardiovascular risk factors in primary care patients. Defended statements: 1. Mental disorders are prevalent in primary care patients, unfortunately most of them are undiagnosed and untreated 2. There is no adequate management and attention for suicide ideation in primary care 3. Psychiatric disorders are associated with cardiovascular and endocrine disorders in primary care population Scientific novelty and significance of the study 1. New information of scientific value is contained in this study. To our knowledge this is the first study to dissertate how prevalent are mood, anxiety disorders and suicidal ideation in primary care, evaluated by standard method, in Lithuania. The evaluation on how precise the HAD Scale is in screening for current MINI diagnoses of depressive disorders and anxiety disorders in an unselected population of primary care patients has the real purpose and significant issue of the present study. 2. Suicide is not only personal tragedy, it represents a serious public health problem in Lithuania. And it has been never studied in the primary care, using standard method. New information was collected in the present study, regarding the prevalence and the factors, affecting suicidal ideation, in primary care patients. 3. To-date there is limited information on the subject of co-morbidity of general medical conditions known to have major public health effects and general psychiatric disorders in primary care; and new studies on the evaluation of anxiety disorder and medical conditions are highly needed, since most research has been completed in the community, and only rarely in PC samples. To our knowledge this is the first study to evaluate the prevalence of mental disorders using standard method in association with general medical conditions in primary care in Lithuania. 4. Autoimmune thyroid disease has significant impact on mental and physical health, cardiovascular risk factors such as increased blood pressure 11 (BP) or increased BMI, however, this has never been studied in an unselected medical population, such as in primary care patients. The present study covered the autoimmune thyroid evaluation by ultrasonografic imaging in association with mental status and general medical conditions, and new data and evidences were given. 5. Based on the results new practical recommendations and new training issues could be comprised in general primary care level, from the perspective of the successful integrity of primary care and public mental health sector in the preventive and everyday practice. 12 1. REVIEW OF LITERATURE 1.1. The prevalence of mental disorders in a primary care population Mood and anxiety disorders as well as suicidal ideation are highly prevalent, unrecognized and untreated in general population as well as in the primary care settings [5; 7; 8; 23; 35; 52; 112;132, 134, 137; 138; 145; 158; 160; 161; 200; 202; 204; 208; 230; 245; 272]. The World Health Organization (WHO) Global Burden of Disease Survey estimates that by the year 2020, major depression will be second only to ischemic heart disease in the amount of disability experienced by suffers. [159; 174; 293]. Different studies consistently demonstrated that individuals with depression and anxiety disorders experience impaired physical and role functioning, more days in bed due to illness, more work days lost, increased impairment at work, and high use of health services [8; 159; 261]. The prevalence of mental disorders in primary care in Europe has been estimated to range approximately between 20 and 55% [7; 8; 10; 14]. Recognition of anxiety and depression in primary care is poor, with only 23% of pure anxiety cases being recognized [230]. Common mental health disorders, such as depression, generalised anxiety disorder, panic disorder, obsessive-compulsive disorder, post-traumatic stress disorder and social anxiety disorder, may affect up to 15% of the population at any one time. The prevalence of major depression in people seen in primary care is between 5% and 10%, and two to three times as many people have depressive symptoms but do not meet the criteria for major depression. It is the third most common reason for a consultation in primary care. About two thirds of adults will at some time experience depressed mood of sufficient severity to influence their activities. Annually, 6% of adults have an episode of depression, and more than 15% of the population will experience an episode during their lifetime [(11i)]. Most depressive states are at the mildto-moderate end of the spectrum and it is these that are mainly seen in primary care. Chronic physical illness increases the risk of depression: 23% people with two or more chronic physical problems were rated as depressed versus 3.2% of healthy controls. [310] NICE recently issued specific guidance regarding depression in adults with a chronic physical health problem [(11i)]. 13 Numerous studies have shown that only approximately 50% of depressed patients are recognized as such in primary care [126; 158]. Data from the World Health Organization Collaborative Study on Psychological Problems in General Health Care, which was conducted in 26,422 primary care attendees in 14 countries worldwide, and from the Institut National de la Santé et de la Recherche Médicale (INSERM) study, which was conducted in over 2400 consecutive primary care patients in France, demonstrate the high prevalence of major depression in general practice (13.7% and 14.0% in each study, respectively). These 2 studies are supported by the more recent European Study of the Epidemiology of Mental Disorders (ESEMeD), which was conducted in over 21,400 adults from the general populations of 6 European countries and which revealed lifetime prevalence for major depression of 13.4%. Despite this high prevalence, both the WHO and INSERM studies revealed that only 54% to 58% of depressed patients were recognized as "psychiatric cases" by their general practitioner and only 15% to 26% were given a specific diagnosis of depression [160]. Comorbidity is the rule with anxiety and depressive disorders with the high levels of it in primary care [5; 204]. Comorbidity of depression with anxiety or medical illness further increases the disability experienced by sufferers [4; 159; (11i)]. There is evidence that the prevalence of common mental disorders varies across Europe [138; 290]. Unselected attendees to general practices in the UK, Spain, Portugal, Slovenia, Estonia and The Netherlands were assessed for major depression, panic syndrome and other anxiety syndrome [138]. Prevalence of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM–IV) major depression, other anxiety syndrome and panic syndrome was compared between the UK and other countries after taking account of differences in demographic factors and practice consultation rates (Table 1.1.1). Common mental health disorders, such as depression, generalised anxiety disorder, panic disorder, obsessive-compulsive disorder, post-traumatic stress disorder and social anxiety disorder, may affect up to 15% of the population at any one time. Epidemiological research has found that 45% of those who warrant at least one diagnosis also meet the criteria for one or more additional disorders [91; 132]. The highest prevalence for all disorders occurred in the UK and Spain, and lowest in Slovenia and The Netherlands. Men aged 30–50 and women aged 18–30 had the highest prevalence of major depression; men aged 40– 60 had the highest prevalence of anxiety, and men and women aged 40–50 had the highest prevalence of panic syndrome. Demographic factors 14 accounted for the variance between the UK and Spain but otherwise had little impact on the significance of observed country differences [138]. Table 1.1.1. Prevalence of depression and other psychiatric syndromes across Europe [138] UK Spain Slovenia Estonia Netherlands Portugal p Major depression Women 13.2 18.4 6.5 14.8 11.4 17.8 <0.001 Men 12.7 11.2 4.4 9.3 7.0 6.5 <0.001 Other anxiety syndromes Women 11.3 20.1 3.0 10.2 4.8 8.2 <0.001 Men 8.4 9.9 2.2 5.5 2.0 2.4 <0.001 Panic syndrome Women 10.3 11.6 7.6 8.0 3.4 13.3 <0.001 Men 8.8 5.9 4.7 5.5 3.1 5.8 <0.001 Epidemiological research has found that 45% of those who warrant at least one diagnosis also meet the criteria for one or more additional disorders [132]. The high prevalence and clinical consequences of the cooccurrence of mental and physical disorders, attention to their comorbidity should remain a clinical and research priority [247]. Still further research is needed on the evaluation of the prevalence and management of mental disorders in primary care patients in association with suicidal ideation and general medical conditions [55]. The institution of family physician practice is very vernal in Lithuania. When family health care reform was started in 1995, the physician workforce in Lithuania was dominated by specialists, the inherited soviet health system was grounded on the biomedical model, emphasizing technical facilities, underestimating the patient's role [121] and the specialty of family physician (FP) did not exist at all [260]. The very first data showed that the prevalence of mood disorders in outpatient clinic of internal medicine in Lithuania twenty years ago was 23% [35] and it remained in the same high level in the past decade with the very high numbers of suicide [83]. In 2004 Puras and colleagues discussed that the real prevalence of mental disorders in Lithuania was unknown [221]. The public mental health in Lithuania became a prioritized issue with the aim to develop new mental health Strategy for 2006-2010 in 2005. The then minister of Health of the Respublic of Lithuania emphasized the importance 15 of primary care practice from the perspective of the successful integrity of primary care and public mental health sector in the preventive and everyday practice [(10i); (16i)] The lack of the researches on mental health in primary care still meets the challenges. New studies could have plausible impact on the developmental teaching of primary care physicians, forward planning of practical recommendations for primary care givers and could have a significant influence to the primary mental health care policy in Lithuania. 1.2. Mood, anxiety disorders and suicide ideation in primary care patients Anxiety and depression are the two most common mental health problems seen in the general medical setting [7; 160; 208]. Mood or anxiety disorders often remain hidden under the guise of somatic physical complaints so that the underlying mental condition is essentially untreated [230]. Although increasing attention has been paid to anxiety, it still lags far behind depression in terms of research as well as clinical and public health efforts in screening, diagnosis, and treating affected individuals. This is unfortunate given the prevalence of anxiety and its substantial impact on patient functioning, work productivity, and health care costs [5; 261]. Recognition of anxiety and depression in primary care is poor, with only 23% of pure anxiety cases being recognized compared with 56% of depression cases [230]. Studies confirm the high prevalence of generalized anxiety disorder (GAD) and major depression (MD) in primary care and the role of several socioeconomic and regional factors in the illnesses [8]. The comorbidity of major depressive and anxiety disorders is associated with barriers to treatment and worse psychiatric outcomes, including treatment resistance, increased risk for suicide, greater chance for recurrence, and greater utilization of medical resources. Paying careful attention to the development of anxiety and depression may also positively impact the economic burden of these disorders [1; 155]. Common mental health disorders, such as depression, generalised anxiety disorder, panic disorder, OCD, post-traumatic stress disorder and social anxiety disorder, may affect up to 15% of the population at any one time. Psychiatric comorbidity, or the concurrent clinical presentation of two or more diagnosable behavioural disorders, is the rule rather than the exception [29; 70]. The comorbidity of major depressive and anxiety disorders is associated with barriers to treatment and worse psychiatric outcomes, 16 including treatment resistance, increased risk for suicide, greater chance for recurrence, and greater utilization of medical resources [1]. Epidemiological research has found that 45% of those who warrant at least one diagnosis also meet the criteria for one or more additional disorders [132]. The 4 most common anxiety disorders (excluding simple phobias that seldom present clinically) are generalized anxiety disorder, panic disorder, social anxiety disorder, and posttraumatic stress disorder [84; 97; 115; 178; 229; 230; 299]. Generalized anxiety disorder is chronic, disabling, and associated with other health problems [52]. However, despite the substantial disability associated with each anxiety disorder and the availability of effective treatments, only a minority of patients (15% to 36%) with anxiety are recognized in primary care [131; 160; 175]. Anxiety disorders are the most common psychiatric disorders in the elderlies [225]. Despite the prevalence, morbidity, and cost, psychiatric disorders continue to be underdiagnosed and treated incompletely in primary care settings, even though it was stated that the prevalence of such disorders, including PTSD in primary care may indeed be higher than expected [157; 158; 298]. Anxiety and major depressive disorders are commonly associated with other psychiatric disorders, e.g., psychiatric comorbidity, or the concurrent clinical presentation of two or more diagnosable behavioural disorders, is the rule rather than the exception [70]. Mood and substance use disorders, in particular, have been found to frequently co-occur. According to the Epidemiologic Catchment Area (ECA) Study, the lifetime prevalence for any mood disorder and any alcohol use disorder is 21.8%. For major depression and dysthymic disorder, the comparable comorbidity rates with any alcohol use disorders are 16.5% and 20.9%, respectively [224]. Among those with an existing alcohol-related disorder, as many as 30-48% of women and 9-24% of men will also meet the diagnostic criteria for major depressive disorder at some point during their lifetime [136; 224]. Depressive disorders and anxiety disorders often coexist in general population as well as primary care settings and are often secondary to other psychiatric disorders. The comorbidity between depression and anxiety is so high that debate continues as to whether they are categorically separate disorders or part of a continuum. For example, studies suggest that 30%– 40% of patients with panic disorder or obsessive compulsive disorders also have depression. Comorbidity between anxiety disorders is common (e.g., 30% of patients with OCD report simple or social phobias, and 15% report panic disorder). Comorbidity with other psychiatric disorders is also common. Depression can be a feature of virtually any psychiatric disorder. Particularly high rates of depression are found in alcohol-related disorders, eating disorders, 17 schizophrenia and somatoform disorders [(12i)] and the disabilities caused by depression and anxiety are just as great as that caused by other common medical condition [159; 271; (1i)]. The literature clearly supports the view that primary care services have a key role in the provision of mental health services for those with mild to moderate mental health and/or addiction issues. Primary mental health care also has a role to play in supporting people with severe mental health issue as suicide. Suicide, depression and addiction is recognised as a major public health issue [112; 124; 159, 158; 188; 202; 244; 266; 273; (7i); (11i)]. Most primary care clinicians do not routinely screen for suicide risk [111]. Mood and substance use disorders, in particular, have been found to frequently cooccur. Authors address that significant number of completed suicides are associated with mental disorders, especially with mood disorders and substance misuse [176; 183; 242; 243] and conclude that the link between common psychiatric comorbidities, alcohol misuse and suicidal behaviour is robust and the very complex issue [29]. There is an evidence that the prevalence of common mental disorders and suicide varies across Europe and all over the world and the rates of mental illness continuing to increase internationally [112; 202; (7i) (8i), (9i)] (Fig 1.2.1; Fig 1.2.2.). Fig. 1.2.1. Suicide rates in selected regions and countries [112] 18 Fig 1.2.2. Numbers of suicide deaths in numerous nations, for the most recent year available. Data were obtained from the World Health Organization [202]. The Projections of Global Mortality and Burden of Disease from 2002 to 2030 represented that self-inflicted injuries, rated as the 14th rank place on the rankings for 15 leading causes of death all over the world in 2002 would be on the position No.12 in the year 2030 [188]. Measured in terms of disability-adjusted life years (DALYs), mental and neurological disorders globally account for more than 15% of the total burden of all diseases and 17% in low and middle income countries [293]. For developing countries, the treatment gap for mental and neurological disorders has been estimated to be 3.6 times higher than in developed countries [99]. In 2004, more people died in Europe from suicide than from road accidents [158]. The very first data showed that the prevalence of mood disorders in outpatient clinic of internal medicine in Lithuania twenty years ago was 23% [35] and it remained in the same high level in the past decade with the very high numbers of suicide [83] in the period between 1990 and 1996 when suicide mortality in Lithuania rose 82.4%, with the rate peaking at more than 47 per 100,000 persons in 1996. After a slight decrease in 1997 (to 45.6) and in 1998 (to 43.8), suicide rates stabilized at a very high level (in 1998–2002 the average rate was 44.6) [83; 304]. In 2004 Puras and colleagues discussed that the real prevalence of mental disorders in Lithuania was unknown [221]. Throughout the last decade of the twentieth 19 century, Lithuania had the highest suicide rates in Europe among both men and women, aged 25-64 years [269]. The data from EU Public Health Project Global Report on the Health Status in the European Union [(11i)] conclude that Lithuania has the highest rate for males at 50-54 years of age (121.1) and at 15-19 (25.9). The suicidality among both men and women in Lithuania still remains standing as one of the highest suicide rates all over the World [112; 202; (8i)]. There is lack of research on primary care recognition and management of suicide in Lithuania [221] Although there has been significant interest in whether anxiety disorders are risk factors for suicidal behaviour, this remains a controversial area as anxiety disorders are highly comorbid with other anxiety disorders and tend to cluster together, not only amplify the risk of suicide attempts in persons with mood disorders [133; 244; (11i)]. Authors address that significant number of completed suicides are associated with mental disorders, especially with mood disorders and substance misuse [176; 183; 242; 244] and conclude that the link between common psychiatric comorbidities, alcohol misuse and suicidal behaviour is robust and the very complex issue [29]. The primary care plays a critical role on recognition and management of suicide - Luoma and colleagues found that over 50% of people who committed suicide had had health care contact within the month prior to their death [176]. The high prevalence and clinical consequences of the co-occurrence of mental and physical disorders, attention to their comorbidity should remain a clinical and research priority [247]. Still further research is needed on the evaluation of the prevalence and management of mental disorders in primary care patients in association with suicidal ideation and general medical conditions [55]. 1.3. Screening for depression and anxiety disorders in primary care Recognition and treatment of anxiety and depression in primary care as well as in general population is poor [5; 7; 8; 23; 35; 112; 132; 134; 137; 138; 145; 158; 160; 161; 200; 202; 208; 230; 245; 272]. Many factors may conspire against the diagnosis of a mental health condition, particularly when patients present with a complicated somatic history [147; 159; 271; 289]. Improved recognition and diagnosis of psychiatric disorders is the first step toward an enhanced management of mental health disorders in the primary care setting [15]. The ability to diagnose mental disorders by primary care givers is found to be problematic all over the world. A number of diagnostic instruments have been proposed for use in primary care but the 20 final estimation on the best diagnostic instrument was not stated [45]. In 2001, the International Consensus Group on Depression and Anxiety Spectrum proposed an algorithm for improved recognition and treatment of the depression and anxiety spectrum in primary care. The International Consensus Group went on to discuss diagnostic scales and consider the most appropriate approach for the recognition and diagnosis of spectrum disorders in primary care, and ended by developing management guidelines that can be applied across the spectrum of depressive and anxiety disorders. The characteristics of the Primary Care Evaluation of Mental Disorders (PRIME –MD) [257], the Symptom – Driven Diagnostic System for Primary Care (SDDS – PC) [207], the General Healthcare Questionaire (GHQ) [90; 92], the Center for Epidemiologic Studies Depressed Mood Scale (CES–D) [306] and Mini International Neuropsychiatric Interview (MINI) [156; 250; 251] were discussed [15]. Emotional disorders are common diagnoses among primary care patients [8; 245; 272] which must be carefully monitored and treated because it is well known that depression as well as anxiety disorders have a negative but significant effect on the course, outcomes, longterm survival, and treatment efficacy of patients affected by physical disease [17; 78; 163]. Primary care physicians need proper instruments for screening emotional disorders. Several screening tools have been established to diagnose depressive and anxiety disorders in different populations these include PRIME-MD [258], the General Health Questionnaire [90], the Beck Depression Inventory [21], the Zung Self-Rated Depression Scale [309], etc. but not all of them are appropriate to use in a primary care setting [3; 28; 38; 47; 71; 79; 92; 106; 120; 130; 153; 209; 255; 268; 282, (4i)]. Doctor-rated screening tests are a more structured way of interviewing and rating the severity of the illness. Patient-rated screening tests have the advantage of being completed in the patient’s own time, and hence allowing more widespread and time-efficient screening. [(12i)] Useful instruments must be easily administered, inexpensive, and highly sensitive. Instruments used for screening emotional disorders in a busy primary care setting should avoid questions about somatic distress because this population is expected to have complaints concerning their physical health and these questions could bias the results of a screening [64; 152; 153; 232; 287]. Instruments used for screening emotional disorders in a busy primary care setting should avoid questions about somatic distress because this population is expected to have complaints concerning their physical health and these questions could bias the results of a screening [64; 152; 153; 232; 287]. Identification of mood and anxiety disorders is of course key to treatment: the size of treatment gaps relates in part to how well these mental disorders are identified, the 21 availability of treatment resources, stigmatization of illnesses, and the policies and frameworks that are in place to deliver effective interventions for these disorders [273]. The PRIME-MD questionnaire consists of 2 parts: a screening questionnaire that is completed by the patient and a categorical diagnostic checklist that is completed by the physician. Diagnostic categories are checked according to the orientation indicated by the patient's answers. PRIME-MD explores only a limited spectrum of disorders: major depression, anxiety, somatoform disorders, eating disorders, and alcohol abuse. It is a self-assessment form, and symptoms need to have been present for 1 month. A degree of validation of this questionnaire has taken place by both primary care physicians and health care professionals who have shown it to be an acceptable instrument for the diagnosis of mood disorders but unacceptable for the diagnosis of other psychological disorders by a primary care physician [15; 257]. The SDDS-PC is also a patient-administered questionnaire, which explores 16 symptoms covering 6 diagnostic areas; this instrument has been developed from a more extensive (62 symptom) version. If the patient has a positive response in 1 area, a specific physician-administered module is then used. The criteria in the SDDS-PC are more precise than those in the PRIME-MD and include symptom duration and impairments caused by the symptoms. The possible existence of physical illness must be ruled out. The SDDS-PC is a longitudinal tracking form that explores the diagnosis of a limited number of disorders-major depression, GAD, OCD, panic disorder, alcohol abuse, and suicidal behaviour. Validation of this instrument has again raised questions regarding its suitability for use in primary care due to the difficulties in collecting the correct information [15; 207]. The General Healthcare Questionnaire (GHQ) [90; 92] assesses symptoms and the general distress caused by depression and/or anxiety disorders. It is not a diagnostic tool but a list of either 12 (GHQ-12) or 28 (GHQ-28) questions. As part of the World Health Organization (WHO) Collaborative Study on Psychological Problems in General Health Care (PPGHC), the GHQ was administered to 5269 consecutive primary care patients [274]. The data showed a linear relationship between GHQ-12 score and percentage recognition by general practitioners; however, the GHQ appears to be most useful in identifying those patients most severely affected, and a disadvantage of the questionnaire is that it is not diagnosisspecific [15]. Many other diagnostic instruments have limitations that make them unsuitable for use in primary care; for example, either they are time consuming to complete and to score, not all disorders are covered, 22 sensitivity and validity have not been fully explored, or only limited language translations are available [15]. This was the background to the development of the MINI, which was developed jointly by psychiatrists and clinicians in the United States and Europe, for DSM-IV and ICD-IO psychiatric disorders. In a validation study versus the Composite International Diagnostic Interview (CIDI) [295] which was considered the gold standard, the MINI had high specificity, sensitivity, and positive predictive values for all the depressive and anxiety disorders tested with the exception of GAD. However, following amendments to the questions asked, results equivalent to those seen with the other disorders can now be achieved for GAD [54;55] Similar results were observed against the Structured Clinical Interview for DSM-III-R in the United States [156]. The diagnoses made by primary care physicians using the MINI have been compared with the diagnoses made by a specialist. When the MINI was used, diagnostic concordance with the specialist was high for almost all disorders (positive predictive values of approximately 70%), a finding that was all the more notable given that in the absence of a structured interview an accurate diagnosis is achieved in only 15% of cases [274]. The results of this study suggest that with the use of this short structured diagnostic interview there is an increased rate of recognition of depressive and anxiety disorders in primary care [15]. A further investigation in primary care patients in France has examined the positive predictive value of using only the screening questions that are contained at the beginning of each diagnostic module in the MINI. Consecutive primary care patients completed a questionnaire containing the 17 screening questions, and the "selfreport" diagnosis was compared with that reached by a specialist following a telephone interview; the positive predictive value of the screening questions was found to be 68.5%. This shortened screening form of the MINI takes only 5 to 10 minutes to complete [15]. The Hospital Anxiety and Depression Scale [307] was developed as a screening instrument for anxiety disorders and depression in a nonpsychiatric medical population [311]. It is widely used all around the world in patients with both somatic and mental problems, including primary care patients [16; 287], and shows good psychometric properties [24]. But little is known about how well the HADS can identify depression and anxiety disorders diagnosed using standard structured diagnostic psychiatric interviews, such as the Mini International Neuropsychiatric Interview [251], in a population of primary care patients. Some organizational activities were suggested to be included for a better chance of achieving good mental health outcomes when teams work within collaborative care models that include mental health specialists who perform 23 consultation/liaison activities and provide specialized care in primary care facilities [72; 293]. The new charts were developed by the Dartmouth Primary Care Cooperative Research Network (COOP) and the World Organization of National Colleges, Academies, and Academic Associations of General Practitioners/Family Physicians (WONCA) recently and concluded to be valid and feasible option for screening for mental disorders by primary care teams trained community health workers and nurse assistants working in a collaborative mental health care model [189]. Despite the prevalence, morbidity, and cost, psychiatric disorders continue to be underdiagnosed and treated incompletely in primary care settings, even though it was stated that the prevalence of such disorders in primary care may indeed be higher than expected [157; 158; 298]. Studies of primary care screening programs have indicated that approximately 12%14% of those receiving a mental health checkup receive a positive score, and require an interview with a physician or other health professional to determine whether there is evidence of a possible mental illness, and if necessary a referral to a mental health professional. Primary care settings are ideal for implementing mental health checkups, given the regularity with which patients see their PCPs and the existing screening practices already in place there for other health issues [311; (6i)] Routine mental health screening in primary care can detect possible symptoms of depression and other mental illness, much like a blood pressure test can identify possible cardiovascular risk factors. Making mental health checkups routine is key to early identification and critical to prognosis for those who suffer from mental illness [113; 311; (6i)]. Primary care clinicians who maintain a high index of suspicion for symptoms of depression or anxiety, or other signs of psychological distress, PTSD in their patients with positive histories of trauma plus suicidal thoughts or actions, alcohol or substance abuse, or excessive health care service utilization may increase the recognition rate of these disorders in their practices [157; 158; 160; (11i)]. 1.4. Mental disorders and general medical conditions in primary care Primary care is usually the first point of contact for people with any health issues, included mental disorders and/or suicidal ideation [5, 138]. Effective recognition of anxiety and mood disorders in primary care may also positively impact on the economic burden of these disorders, may assist primary care physicians better understand the comorbidity issues and to prevent from severe mental health issues like suicide. The early recognition of psychotic symptoms in patients with somatic illnesses, as well as somatic 24 illness in patients primarily treated because of psychotic disorder concluded to be crucial [102; 143; 193]. Primary care settings are ideal for implementing mental health checkups, given the regularity with which patients see their PC practitioners and the existing screening practices already in place there for other health issues [311; (6i)], but only few studies were performed. There is still limited information that accounts for comorbidity on the impact of role disability associated with a wide range of mental and general medical conditions in primary care samples, as most research has been completed in the community and only rarely in PC samples [193]. Data regarding the prevalence of mental disorders in association of general medical conditions in primary care are scarce [26]. This presents treatment difficulty as primary care physicians are not trained to identify the clinical signs and symptoms of psychiatric illness. Researchers have found the association of depression only with severe, but not with the mild or moderate physical illness which is commonly found in PC, and unmet needs in this area of research have been discussed. Similarly, the association of anxiety disturbance and medical conditions needs more attention in primary care, since most research has been completed in the community, and only rarely in PC samples. The first study - the ZARADEMP Project documented that there is a positive and statistically significant association between general somatic morbidity and general psychiatric morbidity in the (predominantly) elderly population in 2007. It has been concluded that cardiovascular accidents and thyroid disease may have more weight in this association [173]. The high prevalence and clinical consequences of the co-occurrence of mental and physical disorders, attention to their comorbidity should remain a clinical and research priority [247]. Physical-mental comorbidity is very common in the general population , people with mental disorders have a higher prevalence of physical illnesses and reduced life expectancy [290] and leads to a greater absenteeism from work than pure disorders that also cause personal and social problems [32; 122], further increases the disability experienced by sufferers [5; 159; (11i)]. It is important to recognize psychotic symptoms in patients with somatic illnesses, as well as somatic illness in patients primarily treated because of psychotic disorder [143; 193]. As up to one third of patients presenting to primary care clinics with somatic complaints have a mood or anxiety disorder, they often remains hidden under the guise of somatic physical complaints so that the underlying mental condition is essentially untreated [230]. Anxiety and depression are the two most common psychiatric disorders observed in patients with a general medical condition. In early, primary care studies estimated 25 psychiatric illnesses are commonly found in acute care settings, with estimations as high as 30 to 60% of general medical inpatients having experienced some type of comorbid psychiatric illness [18; 169]. The majority of patients with psychiatric illness are in fact most often treated by non psychiatrists: fewer than 25% of patients with psychiatric disorders see specialty mental health providers and the majority of patients are seen in primary care settings [5; 138; 139]. The literature clearly supports the view that primary care services have a key role in the provision of mental health services for those with mild to moderate mental health and/or addiction issues. Primary mental health care also has a role to play in supporting people with severe mental health issue [158; 176]. Many factors may conspire against the diagnosis of a mental health condition, particularly when patients present with a complicated somatic history [147; 159; 271; 289]. Long-standing chronic medical conditions such as obesity, cardiovascular disease and diabetes mellitus, known to have major public health effects, are frequently found coexisting with mood and anxiety disorders [13; 20; 81; 118; 135; 159; 193; 191; 236; 253 271; (1i); (14i)]. An association between mood disorders and thyroid immunity has been demonstrated in different studies [34; 40; 74; 100; 151; 216]. These studies suggest that an AITD, even without clinical or subclinical thyroid dysfunction, is related to mood and anxiety disorders. The impact of thyroid immunity on cardiovascular risk factors such as increased blood pressure or increased BMI in primary care patients has never been studied. There is limited information on the subject of co-morbidity of general medical conditions and general psychiatric disorder in primary care, the association of anxiety disorder and medical conditions needs new studies, since most research has been completed in the community, and only rarely in PC samples. Still further research is needed on the evaluation of the prevalence and management of mental disorders in primary care patients in association with suicidal ideation and general medical conditions [55]. 1.4.1. The association of depression and anxiety disorders with general medical conditions Psychiatric comorbidity with many chronic physical disorders has remained neglected. Long-standing chronic medical conditions such as obesity, cardiovascular disease and diabetes mellitus, known to have major public health effects, are frequently found coexisting with mood and anxiety 26 disorders [13; 20; 81; 118; 135; 159; 193; 236; 253; 271; 275; 293]. Persistent depression increases mortality and decreases medication adherence [88]. Evaluation of a person and their family psychiatric history, current psychiatric symptoms, temporary relationship of the psychiatric symptoms to the physical illness, and concurrent substance abuse is essential [158; 311; (6i)]. Medically ill depressed patients more commonly have an onset of depression over the age of 40, have no previous psychiatric history, lower family history of alcoholism, less suicidal ideation, and fewer suicide attempts when compared to nonmedically ill depressed patient. A negative personal or family history of anxiety disorders, substance abuse, or personality disorders increases the likelihood of the anxiety disorder resulting from a secondary source [113; 202; 224; 296]. It was estimated 53.4 % of USA adults have 1 or more of the mental or physical conditions and these respondents report an average 32.1 more roledisability days in the past year than demographically matched controls, equivalent to nearly 3.6 billion days of role disability in the population. Authors conclude that the staggering amount of health-related disability associated with mental and physical conditions should be considered in establishing priorities for the allocation of health care and research resources, bearing in mind frequent comorbidity between of psychotic and somatic disorders, early recognition of such comorbidity as very important issue, as well as the selection of antipsychotics. With the exception of depression, there is considerable less information on the issue of psychiatric disturbances co-morbid with general medical conditions. Furthermore, some studies found the association of depression only with severe, but not with the mild or moderate physical illness which is commonly found in PC, and unmet needs in this area of research have been discussed. Similarly, the association of anxiety disturbance and medical conditions needs more studies, since most research has been completed in the community, and only rarely in PC samples. Anxiety, like depression, is a normal reaction to certain events that occur in everyday life; however, a true anxiety disorder has more serious implications. Anxiety related to medical illness is generally associated with one of the following: 1) acute anxiety secondary to acute medical illness; 2) acute anxiety secondary to a chronic medical illness; 3) chronic anxiety existing prior to the medical illness; and 4) chronic anxiety and medical illness [297]. In the DSM-IV, anxiety disorders are differentiated to include panic disorder with or without agoraphobia, agoraphobia without a history of panic disorder, specific phobia, social phobia, obsessive–compulsive disorder, posttraumatic stress disorder, acute stress disorder, generalized anxiety disorder, substance27 induced anxiety disorder, anxiety disorder not otherwise specified, and anxiety disorder due to a general medical condition. Early recognition and treatment is vital to improved patient outcome, quality of life, and cost of care [263; 311; (6i)]. The ZARADEMP Project documented that there is a positive and statistically significant association between general somatic morbidity and general psychiatric morbidity in the (predominantly) elderly population in 2007. It has been concluded that cardiovascular accidents and thyroid disease may have more weight in this association [173]. GAD is chronic, disabling, and associated with other health problems. Anxiety was found to be an independent risk factor for the incidence of CHD and cardiac mortality in initially healthy individuals [228]. Patients with concomitant diagnoses of stable CAD and either major depressive disorder (MDD) or generalized anxiety disorder (GAD) had a greater-than-twofold increase in the risk of major adverse cardiac events in the two years following a baseline assessment, although comorbid MDD and GAD appeared not to be additive in their effects on cardiac risk [77]. Depression has long had a popular link to cardiovascular disease and death. However, only during the last 15 years scientific evidence supporting this common wisdom has been available [89]. Major depressive disorder is the most common psychiatric disorder in patients with CAD, with a prevalence of approximately 15% to 20% in those with stable or unstable coronary artery disease (CAD) (ie, myocardial infarction and unstable angina). Since the early 1990s studies have reported prevalence of major depression between 17% and 27% in hospitalized patients with coronary artery disease [239]. MDD may be even more common after coronary artery bypass graft surgery, approaching 30% in some studies [25]. Depression is also very common in congestive heart failure, with a prevalence of up to 20%. Studies using depression symptom (ie, not diagnostic) measures report even higher rates in cardiac patients. Despite such extensive studies of depression in heart disease, the diagnosis is still often missed, and only a minority of depressed patients receives treatment; fewer, yet, receive adequate treatment [164]. Research has demonstrated an association between psychological factors such as stress and both the development of coronary heart disease (CHD) and CHD outcomes [30; 235]. Most studies have focused on the role of depression, with several meta-analyses indicating that depression is an independent risk factor for the development of CHD in the general population [303] as well as a prognostic risk factor in CHD patients [279]. It is becoming clear that the comorbidity of depression and cardiovascular disease does not occur by chance but the mechanisms 28 responsible for this relationship are poorly understood. Platelet abnormalities, autonomic tone, and health behaviours have all been implicated. There exists also the possibility that depression and vascular disease share certain vulnerability genes [190]. A new study confirms that patients with stable CAD and a diagnosis of depression or anxiety have a greater risk of cardiac events [77]. Moreover, it is now apparent that depression aggravates the course of multiple cardiovascular conditions [89] and has regularly been shown to lower adherence to prescribed medication and secondary prevention measures [87]. Several early studies have demonstrated that depression increases the risk of developing cardiac disease, in particular coronary artery disease, and to worsen prognosis after myocardial infarction [39; 75; 199; 248; 249; 263; 297]. Few randomized controlled trials have evaluated the efficacy of treatments for major depression in patients with coronary artery disease. The impact of depression was mostly related to the premorbid cardiac disease status with a two- to fourfold increased risk of mortality during the first 6 months following myocardial infarction, but it has been shown that depression increases the risk for cardiac mortality independently of baseline cardiac status. The mechanisms of increased cardiac risk attributable to depressive illness are at present uncertain, but activation of the sympathetic nervous system with increased levels of monoamines, exaggerated platelet activity, and/or enhanced inflammatory-mediated atherogenesis are likely to be of primary importance. New research helps us to understand which common biological changes are involved in the already known link between depression and life-threatening cardiovascular disease [(5i)]. The Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy, a randomized, controlled, 12-week, parallel-group trial (CREATE) [162], was the first trial specifically designed to evaluate the short-term efficacy and tolerability of 2 depression treatments in patients with CAD: citalopram, a first-line selective seratonin reabsorption inhibitor (SSRI) antidepressant and interpersonal psychotherapy (IPT), a short-term, manualbased psychotherapy focusing on the social context of depression. The trial documents the efficacy of citalopram administered in conjunction with weekly clinical management for major depression among patients with coronary artery disease and found no evidence of added value of IPT over clinical management. Similar to the results of SADHART, CREATE found the benefits of SSRIs for patients with CAD to be clearer for recurrent episodes of major depression than for first episodes [(5i)] Depression is a painful state, and it should be treated aggressively when indicators of benefit are present; major depression following myocardial 29 infarction is consistently associated with about a 3-fold increase in cardiac mortality and evidence continues to accumulate [87]. There is burgeoning literature on the relationship between mood disorders and cardiovascular Table 1.2.1 summarizes results of large studies of the relationship between depression and prognosis of coronary artery disease, in people without preexisting CAD [144]. Table 1.4.1.1. Studies of the relationship between depression and prognosis of coronary artery disease), in people without preexisting CAD (144) Study Age (years) Follow-up (years) Hallstrom et al., 1986 38-54 12 Appels and Mulder, 1988 39-65 4.5 Anda et al., 1993 45-77 12.4 Aromaa et al., 1994 40-64 6.6 Wassertheil-Smoller et al., 1996 ≥ 60 4.5 Barefoot and Schroll, 1996 50 24 Pratt et al., 1996 >18 13 Ford et al., 1998 26±2 37 RR* Severity of depression, predicted angina only RR = 2.28 for nonfatal MI; no association with fatal MI RR = 1.5 for depressive affect RR = 3.36 Deaths: RR = 1.26 MI or stroke: RR = 1.18 MI: RR = 1.14, but not significant* Death: RR = 1.59 MI: RR= 1.71 MI: RR= 4.54 for major depressive episode MI: RR = 12.07 for dysphoria MI or CAD: RR = 2.12 Mendes de Leon et al, 1998 65-99 9 Mortality: RR = 1.03 *Adjusted for multiple factors (varies between studies, in general age, conventional cardiovascular risk factors, such as smoking, cholesterol, weight, or body mass index, and physical conditions at entry of the study). MI, myocardial infarction; RR, relative risk. Major depression severely impairs heart rate variability recovery following an acute coronary event. It is now clear, that depression is also associated with biological changes involving increased heart rate, inflammatory response, plasma norepinephrine, platelet reactivity, absent post-ACS HRV recovery -- all of which is associated with life-threatening consequences. It also impairs compliance with doctor’s advice and health behaviours. From a clinician's point of view, patients with depression after myocardial infarction, especially those with prior episodes, should be both carefully watched and aggressively treated, because they are at an elevated cardiac risk and less likely to get better spontaneously [(5i)]. Several epidemiological studies have associated depressive symptoms with cardiovascular disease. The slogan “no health without mental health” 30 supports an insistence on the similarities between physical and mental health. A study by Prince et al. (2007) looked at the interaction between mental and physical health status [219]. Disease Factors The symptoms of a mental illness can increase a person’s risk of developing some chronic diseases. For example, depression changes: • Serotonin levels (i.e., a chemical found in the brain), impacting heart function, red blood cell clotting, and the narrowing of blood vessels. • Cortisol levels (i.e., a hormone involved in the stress process), increasing red blood cell clotting and causing swelling of the blood vessels. These changes may increase a person’s risk of developing coronary heart disease or having a stroke [219]. Treatment Factors The medications used to treat a mental illness may have side effects that increase a person’s risk of developing some chronic diseases. For example, antipsychotic medication used to treat schizophrenia, bipolar disorder, and dementia may cause weight gain and increase the risk of developing type 2 diabetes and cardiovascular disease [227]. Additionally, the physical health of a person with a mental illness may be neglected during the treatment process, delaying early diagnosis of a physical condition and increasing the risk of chronic disease development [227]. Studies of psychological treatments for hypertension, primarily relaxation techniques and biofeedback, have sometimes found modest but clinically significant sustained reductions in blood pressure. However, drug therapy is much more effective than such techniques [164]. Neuropsychiatric side effects are common with many cardiovascular drugs. Common psychiatric side effects of selected cardiovascular drugs are shown in the Table 1.2.2. While a number of clinical authorities have reported the safe use of modest doses of stimulants in patients with significant cardiac disease, including congestive heart failure, coronary artery disease, arrhythmias, and hypertension, recent concern has been raised regarding cardiac risk. Here, too, a careful weighing of potential risks versus benefits is warranted rather than total avoidance [164]. Table 1.4.1.2. Common psychiatric side effects of selected cardiovascular drugs [164] 31 Agent Side effects Antiarrhythmics Lidocaine Psychosis, anxiety Digitalis α–β blockers Visual hallucinations, anorexia, depression, delirium Fatigue, insomnia, lethargy, decreased libido, discontinuation syndrome Insomnia α–blockers Depression ACE–inhibitors Mood change (uncommon) β–blockers Thiazide diuretics Fatigue, weakness, anorexia (when hypokalemic) ACE = angiotensin-converting enzyme In a metaanalysis of 11 studies of coronary heart disease, major depressive disorder, which had been measured in only three studies, was a much stronger predictor of CHD outcomes than depressed mood [213]. Anxiety seemed to be an independent risk factor for incident CHD and cardiac mortality [228]. Although evidence suggests that anxiety also has an adverse impact on prognosis in CHD patients independent of depression [237; 254; 265], the role of anxiety as an etiological risk factor is less clear. Although several studies suggest that anxiety might contribute to the development of CHD in initially healthy individuals [148] and found an effect on cardiac death [101; 127] or incident myocardial infarction (MI) [252], others have found no association [195] Anxiety disorders typically present with a number of somatic physical complaints (e.g., palpitations, sweating, shortness of breath, chest pain, and nausea) resembling cardiac disorders [166]. Additional cardiovascular conditions that may contribute to a clinical presentation of anxiety include angina, congestive heart failure and syncope as well as anxiety disorders are associated with significantly lower heart rate (HR) variability [166; 297]. Extreme anxiety and psychological distress have been associated with increased risk for sudden cardiac death. Few studies have examined GAD as a risk factor for all-cause mortality, although two population studies suggest that, for causes of death other than suicide, GAD does not present a significant risk [110; 213]. However, other manifestations of anxiety have been associated with an increased risk of cardiovascular disease (CVD) morbidity and/or mortality [62; 213]. Common considerations in the differential diagnosis of depression include thyroid disorders and other endocrinopathies, medication side effects, malignancy, and neurologic disorders. Anxiety may be caused by thyroid disorders, a variety of medications including over-the-counter 32 preparations and herbal remedies, and substance abuse. Cardinal signs of depression (ie, mood disturbance or anhedonia) or anxiety (eg, fears, worries, compulsions, avoidance) may help initially suggest a psychiatric condition [147, 289]. Most standard textbooks include long lists for both anxiety and depression. The more common conditions associated with depression include endocrine disorders are hypothyroidism, hyperthyroidism, Cushing’s disease and Addison’s disease. Underlying malignancies should also be considered. For anxiety disorders, consider endocrine disorders such as thyroid, parathyroid, and adrenal dysfunction (phaeochromocytoma), seizure disorders and cardiac conditions such as arrhythmias, supraventricular tachycardia, and mitral-valve prolapse. Alternatively, depression may be a direct consequence of the physical illness. Both Cushing’s disease and hypothyroidism are well known examples of endocrinopathies for which depression may be the first manifestation. The same is true for anxiety, where hyperthyroidism and vitamin B12 deficiency are frequently associated with anxiety symptoms [(12i)]. Anxiety and major depression are frequent psychiatric presentations seen in a number of individuals with endocrine disorders. Treatment of the underlying medical disorder will often resolve the symptoms of mental illness. Endocrine disorders, including hyperadrenalism, hyperthyroidism, hypocalcemia, and hypothyroidism have all been associated with being responsible for the clinical presentation of anxiety. It has been demonstrated that thyroid autoimmunity is related to changes in general medical conditions such as body mass index [256], to increased cardiovascular morbidity in general [180], or to specific cardiovascular dysfunction such as pulmonary arterial hypertension [46]. These findings indicate that autoimmune thyroid disease may have significant impact on mental and physical health. However, this has never been studied in an unselected medical population, such as in primary care patients. Obesity and common mental disorders, such as anxiety and depression, independently account for a substantial proportion of the global burden of disease and its associated economic costs, so it is important to determine the interaction between these conditions [12; 58; 199]. Such comorbidity with cardiac, respiratory, Gastrointestinal, endocrinal, and neurological disorders, trauma, and other conditions like HIV, etc., needs to be addressed too [263, 271]. There is evidence that people with mental disorders are more likely to suffer from metabolic syndrome as cardiovascular risk. In the last decades there has been an increase in interest for researching metabolic syndrome in psychiatric patients and plenty of evidence about their association. 33 Metabolic syndrome is present in 8-56% of patients suffering from bipolar disorder. Metabolic syndrome in patients with bipolar disorder can significantly contribute to morbidity and mortality, and it is certainly necessary to think of it, to take adequate preventive and therapeutic measures in treating its individual components [13]. Multiple studies have documented an inverse relationship between body mass index and suicide deaths, but positive relationship with suicide attempts. Reasons for this may be the association between extreme obesity and certain mental health disorders, such as panic disorders, substance use disorder (in males but not females), and major depression [253]. Obesity, eating disorders and unhealthy dieting practices are of serious public health concern due to their high prevalence and adverse effects on psychosocial and physical health. As a result of the high prevalence of obesity which becomes pandemic nowadays [118; 236; 293], eating disorders and disordering eating among youth and the evidence suggesting these disorders may not be distinct from one another, there has been increasing interest among obesity and eating disorder researchers to utilize an integrated approach to the prevention of these disorders. Identification of risk factors (e.g. depression, self-esteem, dietary intake patterns, etc.) that are shared among these weight-related disorders is an essential step to developing effective prevention interventions [102]. Authors conclude that despite numerous investigations of cardiometabolic risks, many issues remain unclear, becoming objectives for future research as metabolic syndrome can contribute to significant morbidity and premature mortality and should be accounted for in the treatment of mental disorders [13; 142]. Depression occurs in up to one-quarter of patients with cardiovascular disease and diabetes, in approximately 8.7% to 27.3% of cases [94]. Causes underlying the association between depression and diabetes are unclear. Depression may develop because of stress but also may result from the metabolic effects of diabetes on the brain. Studies suggest that people with diabetes who have a history of depression are more likely to develop diabetic complications than those without depression. People who suffer from both diabetes and depression tend to have higher health care costs in primary care [(11i)] Depressed patients with heart disease have poorer medical outcomes including increased risk of reinfarction and all-cause mortality. Patients with diabetes and depression have poorer glycemic control, more diabetes symptoms, and greater all-cause mortality. Depression is associated with both biological (hypothalamic-pituitary-adrenal axis dysregulation) and psychosocial processes (adherence, poorer diet, and exercise) that may mediate adverse medical outcomes. Antidepressant treatments are effective 34 in treating depression in medically ill patients, but their impact on medical outcomes remains to be quantified [68]. Depression, cardiovascular disease, and diabetes are among the most common chronic illnesses affecting an aging population. Depression is treatable in patients with medical illnesses, and collaborative care models can yield better detection and depression treatment in primary care settings in which most patients with depression are seen [68]. Hypertension affects from 20% to 50% of adults in most countries [104] and is a major risk factor for cardiovascular morbidity and mortality [43], representing two-thirds of all strokes and one-half of all ischemic heart disease [155; (7i)]. Depression is a risk factor for hypertension [192] and it is associated with poor adherence to antihypertensive medications [26]. Growing evidence suggests high levels of comorbidity between hypertension and mental illness. Chronic forms of morbidity, including mental disorders and hypertension, play a central role in shaping the burden of disease. A number of studies described an increased prevalence of chronic physical conditions among those with mental disorders [66; 96]. There have been mixed findings for an association between hypertension and anxiety disorders in developed countries, with conflicting results from studies using the same design, and using the same measurements. Some studies have shown a positive association between hypertension and anxiety in both crude and multivariate analyses [270]. Conversely, there are studies that show no crude or adjusted association between hypertension and anxiety [96]. Several studies have observed a positive crude association between hypertension and anxiety disorders that does not persist after adjustment in general practice settings [125]. Evidence is inconclusive and does not always include adjustment for relevant confounding variables, particularly traumatic life experiences. Less evidence is available on the relationship between hypertension and depressive disorders. A handful of studies have suggested that depression may be more common among individuals with hypertension while a much larger body of evidence shows no association between hypertension and depression [96]. Additional research found no crude or adjusted association between hypertension and depression. In general population the relationship between comorbid anxiety-depression and chronic physical conditions was examined in the data from 17 countries that completed World Mental Health surveys [247]. Those with noncomorbid depressive disorder, non-comorbid anxiety disorder, and comorbid depression-anxiety were all more likely to have hypertension compared to persons with neither a depressive nor an anxiety disorder [247; 96]. A recent pilot randomized controlled trial integrating depression and 35 hypertension treatment was successful in improving patient outcomes in primary care. Authors concluded that integrated interventions may be more feasible and effective in real-world practices, where there are competing demands for limited resources [26]. In some (but not all) studies, a high level of anxiety has been a strong prospective predictor for the development of hypertension, as has job strain. One prospective study of psychosocial risk factors for hypertension found that two of the components of type-A behaviour (time urgency/impatience and hostility) were each associated with double the risk of hypertension at follow-up, but symptoms of anxiety and depression were not predictive [116]. However, another prospective epidemiologic study found that combined symptoms of depression and anxiety were associated with an increase for hypertension [123]. Hypertension is often a risk factor for other chronic conditions, and therefore an observed association between hypertension and a mental health disorder may not persist after adjustment for other chronic conditions as the true association may be between more severe chronic conditions and the mental health disorder [96]. Because most hypertension is essential (ie, idiopathic hypertension), psychiatric factors have been intensively studied as potential contributors to its pathogenesis [165]. The influence of such in the development of hypertension is less clear than in CAD despite many studies of the potential role of personality, coping style, and blood pressure reactivity in hypertension. In one recent study the blood pressure levels were compared between subjects with clinical anxiety and depressive disorders with healthy controls. Significantly higher mean diastolic blood pressure was found among the current anxious subjects, although anxiety was not significantly related to hypertension risk. Remitted and current depressed subjects had a lower mean systolic blood pressure and were significantly less likely to have isolated systolic hypertension than controls. Users of tricyclic antidepressants had higher mean systolic and diastolic blood pressures and were more likely to have hypertension. Users of noradrenergic and serotonergic working antidepressants were more likely to have hypertension. The study showed that depressive disorder was associated with low systolic blood pressure and less hypertension, whereas the use of certain antidepressants was associated with both high diastolic and systolic blood pressures and hypertension [166]. Despite these findings, there is a lack of studies to be conducted in primary care, integrating the management of depression with management of general medical conditions [26]. 36 1.4.2. Suicide ideation, mental disorders and general medical conditions Suicide, depression and addiction is recognised as a major public health issue and should be given high priority with regard to prevention and research [113; 124; 158; 159; 188; 202; 243; 266; 273; (7i); (11i)]. The estimated global burden of suicide is a 1000000 deaths per year [181], suicidal behaviour is a leading cause of injury and death [202]. There is an evidence that the prevalence of common mental disorders and suicide varies across Europe and all over the world and the rates of mental illness continuing to increase internationally [113; 202; (7i); (8i)] (Fig 1.2.1; Fig 1.2.2.). The literature clearly supports the view that primary care services have a key role in the provision of mental health services for those with mild to moderate mental health and/or addiction issues. Primary mental health care also has a role to play in supporting people with severe mental health issue. Luoma and colleagues found that over 50% of people who committed suicide had had health care contact within the month prior to their death [176]. The high prevalence and clinical consequences of the cooccurrence of mental and physical disorders, attention to their comorbidity should remain a clinical and research priority [247]. Still further research is needed on the evaluation of the prevalence and management of mental disorders in primary care patients in association with suicidal ideation and general medical conditions [55]. The comorbid anxiety and depression portends an even greater chance of nonresponse to treatment [129; 210], long-term poor outcome, and suicide: for those with uncomplicated panic disorder, the risk of suicide is 7%, but if comorbid depression exists, the risk is increased to 23.6%. Likewise, MDD without anxiety was associated with a 7.9% risk of suicide, but when comorbid anxiety was present, this risk jumped to 19.8% [1]. As major depression is highly comorbidity with other mental disorders such as alcohol misuse [266] it is found in 60% of those who commit suicide and it is in accordance with the data from Eugloreh 2007 Project and Eurostat statistics [(8i), (9i)]. Another authors address that 90% of completed suicides are associated with mental disorders, especially with mood disorders and substance misuse [176; 183; 242] and conclude that the link between common psychiatric comorbidities, alcohol misuse and suicidal behaviour is the robust and very complex issue [29]. The presence of mental disorders, especially mood disorders, substance use disorders and schizophrenia is a well-established risk factor for suicidal behaviour [243]. In the general population, suicidal ideation (SI) is associated with negative outcomes such distress, psychiatric comorbidity, 37 and increased health services utilization [81; 84]. Suicidal behaviour has a large number of underlying causes and is associated with a complex array of factors that interact with each other and place individuals at risk. These include: -psychiatric factors such as major depression, schizophrenia, alcohol and other drug use, and anxiety disorders; -biological factors or genetical traits (family history of suicide); -life events (loss of a loved one, loss of a job); -psychological factors such as interpersonal conflict, violence or a history of physical and sexual abuse in childhood, and feelings of hopelessness; -social and environmental factors, including availability of the means of suicide, social isolation and economic hardship; Some risk factors vary with age, gender, sexual orientation and ethic group. Marginalized groups such as minorities, refugees, the unemployed, people in or leaving prisons and those already with mental health problems, are particularly at risk. However, the presence of sufficiently strong protective factors (which are related to emotional well-being, social integration through participation in sport, etc.) may reduce the risk of suicide. It is vital to the overall outcome and well-being of patients that comorbid states be identified and treated to improve quality of life, increase rates of compliance, improve psychosocial functioning, and decrease the total costs of treating the disease state. A number of disease states are reviewed that have been studied and shown to have improved outcomes and decreased mortality rates when both the psychiatric conditions and medical illness are treated [263; (1i)]. Controversly, many health conditions increase the risk for mental disorder, and comorbidity complicates help-seeking, diagnosis, and treatment, and influences prognosis. Health services are not provided equitably to people with mental disorders, and the quality of care for both mental and physical health conditions for these people should be improved [(1i), (7i)]. Although there has been significant interest in whether anxiety disorders are risk factors for suicidal behaviour, this remains a controversial area as anxiety disorders are highly comorbid with other anxiety disorders and tend to cluster together, not only amplify the risk of suicide attempts in persons with mood disorders [133; 243; (8i)]. From 1950 to 1995 the global prevalence of suicide (for men and women) increased by 60 %. Suicide and attempt suicide result in major economic losses as suicidal and self-harming behaviours make increasing demands on services across the entire spectrum of health and social care. Reports from the WHO indicate that suicide accounts for the largest share of the intentional injury burden in developed counties and that suicide is projected to become an even greater contributor 38 to the global burden of disease over the coming decades [188]. Among young and middle-aged people, especially men, suicide is currently a leading cause of death. It was reported suicide to be the thirteenth leading cause of death globally and the seventh leading cause of death in the European Region (WHO European Ministerial Conference on Mental Health 2005). The highest rates in the European Region were also stated as the highest in all over the world. In the European Region, in the age group 15-35 years, suicide was stated as the second most common cause of death after traffic accidents [(7i)]. Researchers found that the number of disability days associated with all mental conditions at the population level equals more than half (54%) the number of days associated with all the physical conditions considered herein at the population level. This demonstrates the enormous significance of mental conditions to overall illness-related disability. The substantial impact of mental disorders can be attributed to their high prevalence, substantial comorbidity with physical conditions, comparatively early age at onset, and broad influence on functional impairment [193]. Suicide is not only personal tragedy; it represents a serious public health problem, particularly in the WHO European region. From 1950 to 1995 the global prevalence of suicide (for men and women) increased by 60 %. The very first data showed that the prevalence of mood disorders in outpatient clinic of internal medicine in Lithuania twenty years ago was 23% [35] and it remained in the same high level in the past decade, with the very high numbers of suicide [83] in the period between 1990 and 1996 when suicide mortality in Lithuania rose 82.4%, with the rate peaking at more than 47 per 100,000 persons in 1996. After a slight decrease in 1997 (to 45.6) and in 1998 (to 43.8), suicide rates stabilized at a very high level (in 1998–2002 the average rate was 44.6) [83; 304]. In 2004 Puras and colleagues discussed that the real prevalence of mental disorders in Lithuania was unknown [221]. Throughout the last decade of the twentieth century, Lithuania had the highest suicide rates in Europe among both men and women, aged 25-64 years [269]. The data from EU Public Health Project Global Report on the Health Status in the European Union [(11i)] conclude that Lithuania has the highest rate for males at 50-54 years of age (121.1) and at 15-19 (25.9). The suicidality among both men and women in Lithuania still remains standing as one of the highest suicide rates all over the World [112; 202; (11i)]. There is lack of research on primary care recognition and management of suicide in Lithuania [221] Suicide and attempt suicide result in major economic losses as suicidal and self-harming behaviours make increasing demands on services across the entire spectrum of health and social care. Reports from the WHO indicate that suicide 39 accounts for the largest share of the intentional injury burden in developed counties and that suicide is projected to become an even greater contributor to the global burden of disease over the coming decades. Projections of Global Mortality and Burden of Disease from 2002 to 2030 represented that self-inflicted injuries, rated as the 14th rank place on the rankings for 15 leading causes of death all over the world in 2002 would be on the position No.12 in the year 2030 [188]. The existence of mental disorders is almost constant in subjects who try to kill themselves. In addition, a majority of attempters have more than one diagnosis [159]. According to WHO, Suicide rates can be reduced if depression and anxiety are recognized and treated. (www.euro.who.int, 2004). The comorbidity of major depressive and anxiety disorders is associated with barriers to treatment and worse psychiatric outcomes, including treatment resistance, increased risk for suicide, greater chance for recurrence, and greater utilization of medical resources. There are several important risk groups such as psychiatric patients, persons with alcohol and drug abuse, persons with newly diagnosed severe physical illness, all who previously attempted suicide, and groups of homeless, institutionalized, prisoners and other socially excluded persons [203]. Effective recognition and treatment of anxiety and depression may be associated with functional improvement in the medical disorders. Mood and substance use disorders, in particular, have been found to frequently co-occur and have been frequently found coexisting with a number of conditions known to have major public health effects, long-standing chronic medical conditions such as cardiovascular disease and diabetes mellitus [159; 135; 193; 81]. There is a lack of data of the mood and anxiety disorders in association with suicide and general medical conditions in primary care [158; 159; 160;]. Depression has long had a popular link to cardiovascular disease and death. Major depression following myocardial infarction is consistently associated with about a 3-fold increase in cardiac mortality and evidence continues to accumulate [87]. However, only during the last 15 years scientific evidence supporting this common wisdom has been available [89]. Major depressive disorder is the most common psychiatric disorder in patients with CAD, with a prevalence of approximately 15% to 20% in those with stable or unstable CAD (ie, myocardial infarction and unstable angina). Nevertheless Pompili and colleagues found no increased risk of suicide in the cardiac patients, although there was a strong tendency for the patients with cardiac diseases to have more negative expectations for the future [215]. Myocardial infarction is associated with an increased risk of anxiety, depression, low quality of life, and all-cause mortality. MI is followed by an 40 increased risk of suicide for persons with and without psychiatric illness. The risk of suicide was highest during the first month after discharge for MI for patients with no history of psychiatric illness and for patients with a history of psychiatric illness compared with those with no history of MI or psychiatric illness. However, the risk remained high for at least 5 years after MI. [154]. In a metaanalysis of 11 studies of coronary heart disease, major depressive disorder, which had been measured in only three studies, was a much stronger predictor of CHD outcomes than depressed mood [213; 240]. Anxiety seemed to be an independent risk factor for incident CHD and cardiac mortality [228]. Although evidence suggests that anxiety also has an adverse impact on prognosis in CHD patients independent of depression [237; 254; 265], the role of anxiety as an etiological risk factor is less clear. Although several studies suggest that anxiety might contribute to the development of CHD in initially healthy individuals [148] and found an effect on cardiac death [101; 127] or incident myocardial infarction [252], others have found no association [195]. Older adults have high rates of suicide and typically seek care in primary medical practices. Older adults often do not directly or spontaneously report thoughts of suicide, which can impede suicide prevention efforts. Depression is a major cause of suicide among the elderly. Very few studies have been performed on screening for mood, and suicide in primary care elderlies [109; 206]. Obesity, typically indexed by body mass index, and common mental disorders, such as anxiety, depression independently account for a substantial proportion of the global burden of disease and its associated economic costs, so it is important to determine the interaction between these conditions [12; 19]. It is known that extreme obesity is strongly associated with attempt suicide [58]. BMI has been inversely associated with risk of completed suicide in several cohort studies, but putative mechanisms for this association and its generalizability are uncertain [199]. Obesity in patients with bipolar disorder can significantly contribute to morbidity and mortality, and it is certainly necessary to think of it, to take adequate preventive and therapeutic measures in treating its individual components [13]. Obesity, eating disorders and unhealthy dieting practices are of serious public health concern due to their high prevalence and adverse effects on psychosocial and physical health. European psychiatrists view obesity and metabolic syndrome as highly prevalent in the general population and in bipolar patients, presented in 8-56% of patients; two-thirds have changed their management of bipolar patients because of metabolic health concerns [20]. In the last decades there has been an increase in interest for researching metabolic syndrome in psychiatric patients and plenty of evidence about 41 their association. Multiple studies have documented an inverse relationship between body mass index and suicide deaths, but positive relationship with suicide attempts. Reasons for this may be the association between extreme obesity and certain mental health disorders, such as panic disorders, substance use disorder (in males but not females), and major depression [253]. On another hand, authors conclude that conventional risk factors for suicide are inconsistently associated with BMI, making them unlikely mediators for the observed relationship of BMI with lower risk of suicide. In some cases, risk factors are actually greater with heavier BMI [102; 199]. Further study of the relationship of BMI and suicide may yield novel modifiable risk factors that could cause or prevent this important cause of death [199]. A recent meta-analysis concluded that there is a significant positive association between depression and obesity in the general population, which appeared to be more marked among women [55] As a result of the high prevalence of obesity which becomes pandemic nowadays [118; 236; 293], eating disorders and disordering eating among youth and the evidence suggesting these disorders may not be distinct from one another, there has been increasing interest among obesity and eating disorder researchers to utilize an integrated approach to the prevention of these disorders. Identification of risk factors (e.g. depression, self-esteem, dietary intake patterns, etc.) that are shared among these weight-related disorders is an essential step to developing effective prevention interventions [102]. Authors conclude that despite numerous investigations of cardiometabolic risks, many issues remain unclear, becoming objectives for future research as obesity, metabolic syndrome can contribute to significant morbidity and premature mortality and should be accounted for in the treatment of mental disorders [13; 142]. Mental disorders increase risk for communicable and non-communicable diseases, and contribute to unintentional and intentional injury. Mental health awareness needs to be integrated into all aspects of health and social policy, health-system planning, and delivery of primary and secondary general health care [219]. 1.4.3. Thyroid immunity, blood pressure and body mass index in primary care patients It has been demonstrated by investigators that thyroid autoimmunity is related to changes in BMI [256], to increased cardiovascular morbidity in general [180], or to specific cardiovascular dysfunction such as pulmonary arterial hypertension [46]. AITD may have significant impact on mental and 42 physical health. However, the impact of thyroid immunity on cardiovascular risk factors such as increased blood pressure or increased BMI in primary care patients has never been studied. AITD may present with or without thyroid dysfunction [286]. AITD, autoimmune thyroiditis or Graves’ disease, is an autoimmune process characterized by the lymphocytic infiltration of the thyroid gland and by the presence of autoantibodies against the normal thyroid gland [275]. It affects women more frequently than men, and the prevalence increases with age [212]. Autopsy results show that up to 40% of women have AITD evident by lymphocytic infiltration of the thyroid gland [286]. Assessment of thyroid antibodies in peripheral circulation shows that the prevalence of AITD is close to 17% in the female population [141]. Clinical diagnoses of AITD are based on the presence of thyroid antibodies in serum [50]. On the other hand, not all AITD patients are positive for thyroid antibodies in peripheral circulation and ultrasonographic evaluation of the thyroid gland with hypo-echoic ultrasound pattern of the thyroid gland, indicating lymphocytic infiltration of the gland may serve as a sensitive indicator of AITD [50; 103; 184; 212; 222; 256]. 1.4.4. Mental disorders and thyroid immunity in primary care An association between mood disorders and thyroid immunity has been demonstrated in different studies [34; 40; 74; 100; 151; 216], however, this has never been studied in an unselected medical population, such as in primary care patients. These studies suggest that an autoimmune thyroid disease, even without clinical or subclinical thyroid dysfunction, is related to mood and anxiety disorders. It has been demonstrated that thyroid autoimmunity is related to changes in general medical conditions such as body mass index [256], to increased cardiovascular morbidity in general [180], or to specific cardiovascular dysfunction such as pulmonary arterial hypertension [46]. These findings indicate that autoimmune thyroid disease may have significant impact on mental and physical health. There are two major forms of AITD, autoimmune thyroiditis and Graves' disease. AITD is an autoimmune process characterized by the lymphocytic infiltration of the thyroid gland and by the presence of auto-antibodies against the thyroid antigens [275]. In 1992, Harris and colleagues evaluated thyroid dysfunction, antibodies and depression in outpatient women during the eight months after delivery and concluded that depression is associated with positive thyroid antibody status in postpartum period [107] 43 Results of fine needle aspiration biopsy as well as results of autopsy show that up to 40% of women have AITD evident by lymphocytic infiltration of the thyroid gland [286]. Assessment of thyroid antibodies in peripheral circulation show that the prevalence of AITD is close to 17% in the female population [141]. In clinical practice, a diagnosis of AITD is usually based on the presence of thyroid antibodies in serum; however, that approach could miss some patients with AITD, because not all AITD patients are positive for thyroid antibodies in peripheral circulation, including those with thyroid dysfunction [50]. In this regard, hypo-echoic ultrasound pattern of the thyroid gland that is related to lymphocytic infiltration of thyroid gland, assessed by ultrasound evaluation, may serve as a sensitive indicator of AITD [103; 184; 223]. It was demonstrated in recent studies that an abnormal hypo-echoic thyroid ultrasound pattern is highly indicative for AITD [212; 222; 256). Common considerations in the differential diagnosis of depression include not only thyroid disorders but other endocrinopathies as well. Medication side effects, malignancy, and neurologic disorders could play a role. Anxiety may be caused by thyroid disorders, a variety of medications including over-the-counter preparations and herbal remedies, and substance abuse. Recognition of cardinal signs of depression (ie, mood disturbance or anhedonia) or anxiety (eg, fears, worries, compulsions, avoidance) may help initially suggest a psychiatric condition [147, 289] in primary care. 44 2. MATERIALS AND METHODS Ethics The study and its consent procedures were approved by the Regional Committee of Ethics in Biomedical Research at the Kaunas University of Medicine, Kaunas, and The Lithuanian Bioethics Committee, Vilnius, Lithuania (pls. see Appendixes 1, 2a,b). All patients gave written informed consent. 2.1. Subjects A cross-sectional cohort study was performed in a family medicine residency training University clinic in the Kaunas and Vilnius, Lithuania. All the adult (at age 18 or older) consecutive patients who visited a primary care physician were invited to participate in the study, during a 4-week period. Any acute status which required urgent medical care was the only one restriction on the patient selection. Fig. 2.1.1 shows the flowchart of the study population. Recruited N=1170 Refused N=95 Agreed N=1075 Not contacted N=65 Interviewed N=1010 Incomplete data N=12 N=998 Psychiatric evaluation Women 678 (67.9%) N=474 Thyroid gland ultrasonographic evaluation; Psychiatric evaluation Women 348 (73.% )men 126 (27%) Fig 2.1.1. Flowchart of the study population 45 The family doctors recruited 1170 patients: 95 of them declined, making contact with 65 of the patients failed and 12 interviews were excluded due to incomplete data. Thus the final study group consisted of 998 patients. The people who refused to attend (N=95) did not differ from the participants in gender, age, marital status and education. Overall, of the people approached 85% participated in the study. Women made up two-thirds of participants, giving a total study population of 678 (67.9%) women and 320 men (32.1%). The median age of the sample was 51 (Q1–Q3: 33.0–66.0). Q1 stands for 25th percentile; Q3 stands for 75th percentile; range 18-89. Information on characteristics of patient was extracted from the medical records. The following characteristics of patients were: determined: number of cardiovascular risk factors (risk factors include ≥45 years of age, male gender, smoker, type 2 diabetes, high blood pressure, BMI >25 kg/ m2); diagnoses related to hypertension, the prescriptions antidepressants, anxiolytics, antipsychotics, psychotric medication, or diagnoses related to psychiatric disorders (e.g., depression, anxiety, psychosis), prescriptions or diagnoses related to cardiovascular events (search terms angina pectoris, arrhythmias, cardiac arrhythmias, cardiovascular disease, coronary heart disease, heart failure, ischemic heart disease, myocardial infarction, stroke). In addition, information was collected on gender, smoking status, menses status in women, type of diabetes mellitus and antidiabetic drug prescriptions (insulins and oral antidiabetic drugs), other somatic diagnoses (e.g. CAD), number of drugs prescribed at the index date and the psychiatrist visit in the year before the index . The demographic data of the study group are presented in Table 2.1.2. Table 2.1.2. Demographic data of male and female patients Characteristics Age, mean (SD) Marital status Never married Married Divorced/separate d Widowed Education Illiterate Primary school Secondary school Higher University All, N=998 50.2 (18.7) Male, N=320 Female, N=678 49.2 (18.6) 50.6 (18.8) 181 (18..2) 596 (59.8) 58 (18.1) 234 (73.1) 123 (18.2) 362 (53.5) 97 (9.7) 20 (6.3) 77 (11.4) 123 (12.3) 8 (2.5) 115 (17.0) p p=0.30 2=56.8 p<0.001 2=2.3 p=0.67 3 (0.3) 70 (7.0) 259 (26.1) 228 (22.9) 434 (43.7) 0 22 (6.9) 87 (27.3) 68 (21.3) 142 (44.5) 46 3 (0.4) 48 (7.1) 172 (25.5) 160 (23.7) 292 (43.3) A subsample of 474 persons (~50% of the sample) took part in the thyroid gland ultrasonographic evaluation into the Kaunas study. In all, 550 patients were invited into the Kaunas study and 504 patients agreed to participate and 503 patients correctly filled in questionnaires: 367 (73%) were women and 136 (27%) were men. All study patients were interviewed for demographic data and general health status after visiting their general practitioner, and relevant data from the patients’ medical records were collected. Ultrasound evaluation of the thyroid gland was performed to all patients. The mean age of the study population was 52 years (range, 18–89 years). The main reasons to visit a primary care physician were cardiovascular disease in 205 (41%) patients and respiratory diseases in 59 (12%) patients. Seventy-four subjects (16%) were healthy individuals who visited a primary care center for administrative reasons and had no medical diagnosis. Seventy-two (15%) patients had psychiatric diagnoses. Among them, diagnoses of insomnia 25 (5%), depression 19 (4%), and anxiety disorders 19 (4%) were the most prevalent. One hundred (20%) patients used psychiatric medications, mostly benzodiazepines; 28 had no psychiatric diagnoses but used benzodiazepines or over-the-counter sleeping pills for insomnia. Patients with uncompensated hypothyroidism or uncompensated hyperthyroidism evident by abnormal thyroid hormone or/and thyroid stimulating hormone concentration, and patients without thyroid tissue were excluded from the study. Four hundred seventy-four (474) patients completed the study. The mean age of the study population was 52 years, ranging from 18 to 89 years, and 348 (73%) were women. One hundred ninety-five study women (56%) were post-menopausal, based on self-report absence of menses for at least 12 months. Sixty-seven patients (14%) had a history of endocrine disease; sixty-eight patients (14%) had a history of mental disorder. Eighty four patients (18%) used psychotropic medication, mostly benzodiazepines, 69 patients (15%); no patient used lithium. Six women had diagnoses of hypothyroidism and were treated with L-thyroxine. No men were diagnosed with hypothyroidism. Twelve men and 62 women visited the primary care health center for administrative reasons and had no medical diagnoses. 2.2. Methods After written informed consent was obtained, all study subjects entered the study. Mental status of the patient was evaluated twice: first time by 47 family physician, using his or her routine method, and secondly by trained investigator, using MINI International Neuropsychiatric Interview. All the participants were asked to fill in the HAD Scale during the same visit. Assessment of risk factors At entry to the study, attending physicians collected data on variables that are known to be strongly associated with the outcomes of interest and are potential confounders, including age, gender, level of education (below or above 12th grade), history of hypertension (those who were using antihypertensive medication or with >140 mm Hg systolic or >90 mm Hg diastolic blood pressure), diabetes mellitus (those who were being treated for diabetes). Blood pressure and body mass index were recorded by standard methods. Assessment of anxiety We used HADS to measure anxiety. In addition to anxiety, HADS measures depression. Each subscale has scores ranging from 0 to 21 points. Scores 8 were considered to be abnormally high. Because categorical analysis has clinical relevance and can detect graded effect, we further divided anxiety scores into tertiles based on our sample size and event rate, fitting the intuitive classification of low, intermediate, and high level of anxiety. A primary care physician was trained to administer the MINI by a study psychiatrist over two 120-min training sessions that included concert evaluation of patients. During the study all diagnostic obscurities were discussed between the primary care physician and psychiatrist when needed. In this study we used a validated Lithuanian translation of the HADS [35], which is widely used in research studies [33] in Lithuania (Appendix 3). The HADS was administered as a paper-and-pencil questionnaire that takes 2–5 min to complete. The HADS consists of two subscales: depression (HADS-D) and anxiety (HADS-A), designed to measure levels of either anxiety or depression independently of each other. Each subscale consists of seven items scored from 0–3 to which patients respond based on their experience over the past week. Possible scores for either depression or anxiety subscale ranges from 0–21. In this study we chose the MINI [250] as a standard for comparison. The MINI is a standardized structured diagnostic interview that provides an extensive evaluation of patients psychiatric diagnoses meeting DSM-IV-TR criteria [6] and ICD-10 criteria [194] and is widely used in clinical trials and for nonresearch purposes [48; 73]. The MINI is a validated instrument for evaluation of emotional disorders in psychiatric populations [31; 41] and in general medical populations [34; 48 80](Appendix 4). The MINI has several versions and consists of several models pertaining to past and current diagnoses of mental disorders. To address the aims of our study we used the models of the MINI that cover current diagnoses of major depressive episode (MDE), suicidal ideation, PTSD, panic disorder, social phobia (social anxiety disorder), alcohol misuse and generalized anxiety disorder. Each model consists of screening questions and of diagnostic questions. To administer these models in the MINI may take from 2–20 min, depending on the presence and complexity of the psychiatric diagnosis. The 4 most common anxiety disorders (generalized anxiety disorder, panic disorder, social anxiety disorder, and posttraumatic stress disorder) were evaluated separately and in one “anxiety disorders” diagnosis when MINI results assessed. The order of administration of HADS and the MINI was changed randomly, so that the results of one scale could not influence the response to the other. Screening for depression and anxiety disorders was assessed using HADS [307] vs. the MINI International Interview [250]. Measures Weight, height, heart rate, and BP were measured by standard procedures. Patients’ weight and height were measured and BMI was calculated using the WHO formula: BMI = weight (kilograms)/height2 (meters). Subjects with BMI higher than 30 kg/m2 were considered as obese. Standard BP measurements with a random-zero sphygmomanometer were performed by the same investigator (J.P.). BP measurement was obtained after the subjects rested for 5 min in the seated position. Systolic BP was measured as the point of appearance (phase I) of Korotkoff sounds; diastolic BP was measured as the point of disappearance (phase V) of Korotkoff sounds. Patients who had systolic BP higher than 140 mmHg and/or diastolic BP higher than 90 mmHg, regardless of whether they had a clinical diagnosis of hypertension or were receiving treatment for high BP, were classified as a group of patients with BP > 140/90 mmHg. Information on the clinical diagnoses of hypertension, coronary artery disease, and diabetes was obtained from the patients’ medical records. Information concerning the use of antihypertensive medications (diuretics, β-blockers, adenosine-converting enzyme inhibitors, and calcium channels blockers) was also obtained from the medical records. Thyroid gland ultrasonographic evaluation was performed with a realtime scanner equipped with 5 MHz liner transducer with water pillow (SSD210 Dx, Aloka, Japan). Normal echoic thyroid pattern was considered 49 when the density of the thyroid gland was similar to submandibular gland and hypo-echoic to neck muscles; hypo-echoic thyroid pattern was considered when the density of the thyroid gland was hypo-echoic to submandibular gland and hypo-echoic or isohypo-echoic to neck muscles [222]. All ultrasonographic measurements of the thyroid gland were performed by the same investigator (N.M.). The investigator who performed BP measurements, and anthropometric measurements as well as mental status, evaluated by MINI, was blind to the results of ultrasonographic evaluation of the thyroid gland, and the investigator who performed ultrasonographic evaluation of the thyroid gland was blind to the results of BP measurements, anthropometric measurements and mental status evaluated by MINI. Statistical Analysis The Statistical Package for Social Sciences for Windows program was used for statistical analysis. Descriptive statistics of frequency, the Student's t-test, χ2-test, and linear regression were used for comparisons when appropriate. All continuous data are presented as means ± standard deviations, all categorical data as number and percent; p<0.05 was considered statistically significant. We evaluated the internal consistency of HADS-A and HADS-D separately using Cronbach’s coefficient alpha, which is a numerical coefficient of reliability. Alpha coefficients range in value from 0–1 and are used to describe the reliability of factors extracted from dichotomous and/or multipoint formatted questionnaires or scales. The higher the score the more reliable the scale. Self-report instrument is reliable when its Cronbach’s coefficient alpha is at least 0.60 and an instrument can be used for screening purposes when its Cronbach’s alpha is about 0.80 [205]. Second, we addressed the issue of how well different cutoff values for HADS-D and HADS-A predicted MINI diagnoses of MDE and dysthymia and MINI diagnoses of panic disorder, social phobia and GAD separately, and overall anxiety disorders. For each comparison we computed sensitivity (the truepositive rate), specificity (the true-negative rate), positive predictive value (proportion of subjects with positive test results who are correctly diagnosed), negative predictive value (proportion of subjects with negative test results who are correctly diagnosed), and the area under the receiver operating characteristics (ROC) curve (AUC). The AUC is an index of the amount of information the test provides over its entire scoring range. An AUC can range from 0.50, which indicates a worthless test, to 1.0, which indicates a perfect test with a perfect sensitivity and specificity [105]. 50 Since previous research suggests that women are more likely than men to receive a diagnosis of major depression or anxiety disorder [4; 259] we initially tested gender differences, when the ratio of mental disorders was investigated. We examined whether demographic data and measurements of health status are associated with gender, Comparisons between men and women on categorical variables were performed using a two-tailed χ2 analyses, and comparisons on continuous data were performed using nonpaired two-tailed t-tests. We provided univariate estimates for all associations, because the aim of this study was not whether such an association was causal in nature. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Logistic regression was used for analysis of single main effects and for building a model. The following variables were forced into the covariateadjusted models: age, sex, education, hypertension, diabetes, marital status, body mass index. There was no indication of collinearity between the covariates and depressive and/or anxiety symptoms or between the covariates themselves. HADS anxiety scores were dichotomized at a cutoff score of 8, and were categorized into tertiles with roughly one third of the observations in each tertile. We categorized this continuous outcome because the HADS scale, like any other scale, is only quasicontinuous and has an artificial lower and upper boundary. Moreover, the categorization reduces the influence of outliers. Finally, although the cutoff points alone cannot and should not be used to make a psychiatric diagnosis, we wanted to use the binary changes (normal vs. abnormal) to capture substantial and qualitative changes in addition to numerical changes. The tertile categorization has added benefits because it was based on the distribution of our study population and could show a graded effect. The slightly finer categorization (tertiles vs. binary) also helps to recover some of the statistical power that is lost by categorizing a continuous variable. Summary statistics of baseline characteristics in relation to tertiles of baseline anxiety scores on the HAD scale were provided. The association between an individual covariate measure and baseline anxiety scores was assessed using a chi-square test for categorical data and analysis of variance for continuous variables. Associations between depressive symptoms and other baseline risk factors were examined using logistic regression (with presence/absence of depressive symptoms as the outcome measure) to allow adjustment for age, sex and marital status, education, city of residence. For ease of interpretation, continuous risk factors in the final models were expressed using categorical classifications since it had been established that the results were not sensitive to continuous or categorical 51 expression. Where a conventional cut-off was not available, the upper or lower quartile of age was used to categorize the covariate. We investigated whether scores of depression and anxiety were associated with an echoic thyroid pattern in the total sample of men, and in the total sample of women. General linear multivariate models were employed for these comparisons where scores on subscales of anxiety and depression of the HADS were used as dependent variables, echoic thyroid pattern was used as the independent factor, and age was used as covariate. Eventually the prevalence of mental disorders and the use of psychiatric medication were compared in two subgroups of women with respect to their menopausal status. Comparisons between women with a normoechoic thyroid pattern and those with a hypo-echoic thyroid pattern were performed using a two-tailed χ2 analysis separately in pre-menopausal women and in post-menopausal women. A probability level of p<0.05 was taken as significant. Cardiovascular measurements and BMI were investigated in association with an echoic thyroid pattern in the total sample of men and in the total sample of women. General linear multivariate models were used for these comparisons where BMI, systolic and diastolic BP, and heart rate were used as dependent variables; echoic thyroid pattern was used as independent factor; and age was used as covariate. Eventually, the prevalence of obesity and hypertension was compared in two subgroups of women with respect to their menopausal status. Comparisons between women with a normo-echoic thyroid pattern and those with a hypoechoic thyroid pattern were performed using a two-tailed χ2 analysis separately in premenopausal women and in post-menopausal women. We also compared the prevalence of obese women and women with BP > 140/90 mmHg in normo-echoic women and in hypo-echoic women with respect to their menopausal status. A probability level of p < 0.05 was considered as significant. SPSS 12.0 for Windows (Chicago, IL) was used for data analyses. 52 3. RESULTS 3.1. Screening for depression and anxiety disorders in primary care patients We assessed performance of the Hospital Anxiety and Depression Scale (HADS) for screening of depression and anxiety disorders in a population of primary care patients with the MINI as a standard for comparison. We found that the internal consistency of HADS-D using Cronbach’s alpha coefficient was 0.78, indicating a satisfactory reliability, and the internal consistency of HADS-A was 0.83, indicating good reliability for a screening instrument [205]. In all, 112 patients (22%) were found to have a diagnosis of MDE according to the MINI. The area under the ROC curve for the MINI diagnosis of MDE was highest at a HADS-D cutoff score of 6 or more and cutoff score of 8 or more. However, HADS-D sensitivity was higher at a cutoff score of 6 or more, indicating that this cutoff score is more sensitive for screening for MDE (Table 3.1.1). Other characteristics of HADS-D at the optimal cutoff score of 6 or more for diagnosing MDE are presented in Table 3.1.2. Dysthymia was diagnosed in 52 (10%) patients. The AUC for dysthymia was low at all HADS-D cutoff scores (Table 3.1.1). Table 3.1.1. Receiver-operating characteristics for diagnoses of major depressive episode and dysthymia using different cutoff scores of the depression subscale of the Hospital Anxiety and Depression scale (HADSD) Major depressive episode Dysthymia AUC Sensitivity AUC Sensitivity ≥5 0.71 85% 0.62 75% ≥6 0.75 80% 0.59 58% ≥7 0.74 72% 0.60 54% ≥8 0.75 66% 0.56* 39% ≥9 0.71 55% 0.55* 21% ≥10 0.68 45% 0.54* 23% ≥11 0.66 36% 0.52* 15% HADS-D cutoff score ≥12 0.62 27% 0.51* AUC, area under the curve, * p>0.05, Optimal characteristic in bold 53 10% Table 3.1.2. Characteristics of the depressive subscale of the Hospital Anxiety and Depression Scale (HADS-D) at optimal cutoff score (≥6) against the MINI diagnoses of major depressive episode Major depressive episode Prevalence 112 (22%) HADS-D cutoff score ≥6 Sensitivity 80% Specificity 69% Positive predictive value 80% Negative predictive value 92% Area under the ROC curve 0.75 A total of 134 patients (27%) had a MINI diagnosis of at least one anxiety disorder. We found that the AUC of HADS-A for MINI diagnoses of social phobia, panic disorder, or GAD was largest at the cutoff score of 9 or more (Table 3.1.3). Other characteristics of HADS-A at the optimal cutoff point of 9 or more in diagnosing anxiety disorder are presented in Table 3.1.4. Nineteen (4%) patients had a diagnosis of social phobia, 14 (3%) patients had a diagnosis of panic disorder, and 127 (25%) patients had a diagnosis of GAD according to the MINI. The AUCs for MINI diagnoses of social phobia and GAD were highest at HADS-A cutoff scores of 9 or more; for panic disorder at HADS-A cutoff scores of 11 or more (Table 3.5.3). Other characteristics of HADS-A at optimal cutoff values in diagnosing MINI diagnoses of social phobia, panic disorder, and GAD are presented in Table 3.5.4. Table 3.1.3. Receiver-operating characteristics for anxiety disorders using different cutoff scores of the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A) HADS-A cutoff score Social phobia Panic disorder AUC Sensitivity AUC Sensitivity ≥5 0.63 100% 0.63* 100% ≥6 0.68 100% 0.68 100% ≥7 0.69 95% 0.72 100% ≥8 0.74 95% 0.76 100% ≥9 0.79 95% 0.81 100% ≥10 0.69 68% 0.86 100% ≥11 0.73 68% 0.89 100% ≥12 0.73 63% 0.80 79% 54 Table 3.1.3. (continued) HADS-A cutoff score Generalized disorder AUC anxiety Either anxiety disorder Sensitivity AUC Sensitivity ≥5 0.64 96% 0.65 96% ≥6 0.67 91% 0.68 92% ≥7 0.69 86% 0.70 87% ≥8 0.71 81% 0.72 82% ≥9 0.75 76% 0.76 77% ≥10 0.74 66% 0.74 66% ≥11 0.71 57% 0.72 58% ≥12 0.69 48% 0.70 AUC, area under the curve, * p>0.05, Optimal characteristic in bold 49% Table 3.1.4. Characteristics of the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A) at optimal cutoff scores against the MINI diagnoses of anxiety disorders Prevalence 19 (4%) 14 (3%) Generalized anxiety disorder 127 (25%) HADS-D cutoff score ≥9 ≥11 ≥9 ≥9 Sensitivity 95% 100% 76% 77% Specificity 63% 77% 73% 75% 9% 11% 49% 53% 100% 100% 90% 90% 0.79 0.89 0.75 0.76 Social phobia Positive predictive value Negative predictive value Area under the ROC curve Panic disorder Either anxiety disorder 134 (27%) 3.2. The prevalence of mental disorders in an adult primary care population The prevalence of the different current psychiatric disorders in primary care, detected by MINI International Neuropsychiatric Interview, is presented in Fig. 3.2.1. Most commonly detected disorders were MDE disorders in 15.2%, anxiety disorders in 26.3% (generalized anxiety disorder, 18.1%, suicidality in 6.1% and alcohol misuse/probable alcohol abuse in 34.8%. 55 21.0 Generalized anxiety disorder 11.6 18.1 54.4 25.7 Alcohol abuse or dependence 34.8 Posttraumatic Stress Disorder 2.8 1.3 2.3 Social Anxiety Disorder 3.2 3.1 3.2 Panic disorder 3.5 0.9 2.7 6.7 5.0 6.1 Suicidality Female Mal All 17.4 Major depressive episode 10.6 15.2 10 20 30 40 50 60 % 0 Fig. 3.2.1. Prevalence of current mental disorders detected by MINI in the total sample (N=998), comparison of women (N=678) and men (N=320) seen in primary care practices Women, 30.4 % 35 All, 26.7 * 30 25 Men, 18.8 20 15 10 5 0 * p < 0,001 by gender Fig. 3.2.2. Proportions of the respondents having at least one (≥1) current mental disorder according to MINI (or MDE or one of four anxiety disorders) 56 According to the MINI, 160 (16.1%; 95% CI, 13.8–18.3) of the sample had only one current mental disorder (or MDE or one of four anxiety disorders): 38 (11.9%; 95% CI, 8.4–15.4) of men and 122 (18.0%; 95% CI, 15.1–20.9) of women. Of the all respondents 266 (26.7%) were diagnosed as having at least one (≥1) current mental disorder according to MINI (or MDE or one of four anxiety disorders): 60 (18.8%) of men and 206 (30.4%) of women (p<0.001) {Fig. 3.2.2). The prevalence of mental disorders detected by MINI and HAD Sale in the total sample in comparison of women and men are presented in Table 3.2.1. The total current mental diagnoses made by general practitioner vs. MINI are presented in Table 3.2.2. Table 3.2.1. The prevalence of mental disorders detected by MINI and HAD in the total sample, comparison of women and men Disorder Major depressive episode Suicidality Male, N=320 Prevalence,% Female, N=678 N Prevalence,% N Prevalence % N 152 15.2 34 10.6 118 17.4 61 6.1 16 5.0 45 6.7 Panic disorder 27 2.7 3 0.9 24 3.5 Social anxiety 32 3.2 10 3.1 22 3.2 disorder Posttraumatic stress 23 2.3 4 1.3 19 2.8 disorder Alcohol abuse or 348 34.8 174 54.4 174 25.7 a dependence Generalized anxiety 180 18.1 37 11.6 142 21.0 b disorder MDE+GAD 90 9.0 17 5.3 73 10.8 b HADS-D, mean 998 4.5(4.3–4.7) 320 3.8 (3.5–4.1) 678 4.8 (4.3–5.2)b (95%CI) HADS-A, mean 998 6.9 (6.6–7.2) 320 5.8 (5.4–6.2) 678 7.4 (6.9–7.9)b (95%CI) HADS-D categorical >7 195 19.5 46 14.4 149 22.0 b >10 76 7.6 8 2.5 68 10.0 a HADS-A categorical >7 411 41.2 100 31.3 311 45.9 a >10 194 19.4 36 11.3 158 23.3a a b p<0.001; p<0.01, between male and female MDE+GAD, Major Depressive Episode coexisted with Generalized Anxiety Disorder HADS-D, depression subscale of the Hospital Anxiety and Depression Scale. HADS-A, anxiety subscale of the Hospital Anxiety and Depression Scale 57 The results demonstrated several clear gender differences. Panic (2 = 5.6, p = 0.02) and generalized anxiety (2 = 15.1, p = 0.001) disorders were significantly more frequent amongst female than male patients. In contrast, probable alcohol disorders were significantly more frequent in males (2 = 78.6, p < 0.001). MDE had tendency to be more frequent in females (2 = 7.8, p = 0.06) (Table 3.2.1). Table 3.2.2 Psychiatric diagnoses by GP and MINI Diagnosis of general Total practitioner N (GP) No MINI diagnosis N % Major depressive episode N % MINI diagnose Generalized Suicidiality Alcohol anxiety abuse or disorder dependence N % N % N % None 848 380 44.8 110 13.0 125 14.7 45 5.3 313 36.9 Mood disorders 45 15 33.3 16 35.6 22 48.9 7 15.6 8 17.8 Anxiety disorders 30 11 36.7 6 20.0 7 23.3 3 10.0 9 30.0 Other 75 31 41.3 20 26.7 26 34.7 6 8.0 18 24.0 Data, presented in Table 3.2.2 and Table 3.2.3. show that only 44.8 % of patients, who had no psychiatric diagnosis after general practitioner evaluation had no psychiatric disorders detected by MINI as well. Most common disorder which is omitted by general practitioners – alcohol abuse or dependence (36.9 %) and suicidal ideation. Patients having generalized anxiety disorder or any by MINI quite often are considered as having mood disorders (48.9 % patients). Yet most patients having major depressive episode are correctly classified as having mood disorders by general practitioner (GP). Most common diagnosis made by GP was insomnia - 50 patients (5%) were diagnosed having such disorder. Almost in 90% of alcohol abusers had no diagnosis of mental disorder by primary care physician. Diagnose of mental disorder was not found in 45 primary care patients with SI (74% of patients); in total sample of patients who were treated as mental healthy by GP. In the sample of patients who were treated as mental healthy by GP there were 5.3% patients having SI. Patients with alcohol abuse were found to have higher number of anxiety disorder (34.8%) diagnosis and insomnia (20%) diagnosis made by GP. Patients with suicide ideation had the higher number of psychiatric consultation history (37.7%) and established depression (15.6%). Anxiolytic 58 use was the highest (35.5%) in anxiety disorder group and in appr. 25% in both MINI diagnoses of major depression episode and suicidal ideation patients. Significant numbers of patients have used no medication in MINI MDE and any anxiety group (62.5% and 65.1%). Antidepressant use was found higher in suicide ideation (8.2%) and any anxiety (7.2%) group but low in MDE patients (3.2%). Almost no-one took antidepressants in alcohol abuse group (0.3%). MINI anxiety disorders and anxiety diagnosis by GP was found in 7% only as well as low number of depression diagnosis (10.5%) was found in MINI MDE group. Table 3.2.3. Current psychiatric diagnoses established by MINI as function of psychiatric diagnoses and treatments documented by primary care physician Current psychiatric diagnoses established by MINI Major depressive Any anxiety Alcohol Suicidal episode disorder abuse ideation n (%) n (%) n (%) n (%) N=152 (100.0) N=212 (100.0) N=348 (100.0) N=61 (100.0) Documented psychiatric diagnosis No diagnosis (n=848) 110 (72.3) 179 (84.4) 313 (89.9) 45 (73.7) 16 (10.5) 32 (15.0) 8 (2.2) 7 (15.6) Anxiety disorder (n=30) 6 (3.9) 15 (7.0) 9 (34.8) 3 (4.9) Insomnia (n=50) 11 (7.2) 20 (9.4) 10 (20) 4 (6.5) 9 (5.9) 16 (7.5) 8 (2.3) 2 (3.2) 45 (36.1) 76 (35.8) 55 (15.8) 23 (37.7) 85 (62.5) 138 (65.1) 303 (87.1) 39 (63.9) 4 (2.6) 4 (1.9) 1 (0.3) 1 (1.6) 5 (3.2) 15 (7.2) 1 (0.3) 5 (8.2) 39 (25.6) 75 (35.3) 37 (10.6) 15 (24.6) 9 (5.9) 7 (3.3) 6 (1.7) 1 (1.6) Depression (n=45) Other (n=25) History of psychiatric consultation Current use of psychiatric medication No psychiatric medication Antipsychotic Antidepressant Anxiolytic Other Comorbidity among mental disorders The results also showed the prevalence of comorbidity between these disorders. Comorbid subjects were those who had one or more other disorders. 59 The prevalence of anxiety disorder, psychiatric comorbidity Generalized anxiety disorder was present in 180 patients (18.1%), social anxiety disorder in 32 patients (3.2), panic disorder in 27 patients (2.7%), and posttraumatic stress disorder in 23 patients (2.3%), according MINI. Of the 212 patients (21.2%) with at least 1 of four anxiety disorders: 173 (17.3%) had 1 disorder, 28 (2.8%) had 2 disorders, 11 (1.1%) had 3 disorders. The prevalence of major depressive episode, psychiatric comorbidity Of the 152 patients with a major depressive disorder 43.4% also met criteria for at least one anxiety disorder (Table 3.2.4.; Fig.3.2.3.) Table 3.2.4. The prevalence of major depressive episode, psychiatric comorbidity Comorbidity with anxietya Disorder No present 1 2 3 MDE 54 66 22 10 35.5% 43.4% 14.5% 6.6% number of comorbided anxiety disorders – GAD, panic disorder, social anxiety disorder, posttraumatic stress syndrome disorder. a 11.2 DDE + Posttraumic stres disorder N = 152 11.8 DDE + Social anxiety disorder 9.9 DDE + Panic disorder 59.2 DDE + GAD 35.5 DDE 0 % 10 20 30 40 50 60 70 Fig.3.2.3. Major Depression episode comorbidity with anxiety disorders (proportion and 95% CI among patients with major depressive disorder, N=152) 60 Comorbid anxiety disorders are seen in 98 (64.5%) of 152 patients with major depressive disorder when MINI was used. The pure and comorbid mood and anxiety disorders adjusted by gender are seen in Fig.3.2.4. % 14 12.3 * 12 * 10 * Men Women 7.8 7.1 8 6 10.8 5.7 5.3 4.6 4.0 4 p <0,01 by the gender 2 0 MDE Anxiety MDE+Anxiety MDE+GAD Pure disorders Fig. 3.2.4. The prevalence of pure and comorbid current mood, anxiety (at least one of four anxiety disorders) and GAD in total sample (N=998; M320; F-678)), according MINI. Pure anxiety illness and depressive disorders were significantly more frequent amongst female than male patients. In the total sample (N=998) proportion and 95% CI of Major Depression episode comorbidity with GAD was established 9.0% (6.1–9.5). Age adjusted odd ratio of comorbid MDE&GAD according to gender was OR = 2.15 (1.25–3.68) with higher prevalence among women (Table 3.2.7). 61 Table 3.2.7. Univariate Odds Ratios of MDE and GAD according to sociodemographic variables Variable Gender, female Age, quartiles, mean (95% CI) year Q1, 25.5 (24.9-26.1) Univariate OR (95% CI)b MDE GAD 1.78 (1.18-2.67) 1.97 (1.34-2.89) pfor trend=0.08 pfor trend=0.28 1 1 Q2, 43.0 (42.4-43.7) 0.94 (0.56-1.60) 1.41 (0.88-2.27) Q3, 58.9 (58.3-59.4) 1.32 (0.80-2.17) 1.48 (0.93-2.37) Q4, 74.1 (73.5-74.8) 1.65 (1.02-2.27) 1.53 (0.95-2.45) Age, >45 years 1.53 (1.06-2.20) 1.45 (1.03-2.04) Age, 10 years contin 1.10 (1.01-1.21) 1.09 (0.99-1.19) 1.01 (1.00-1.02) pfor trend=0.001 1 1.01 (0.99-1.02) pfor trend=0.12 1 Married 1.25 (0.74-2.11) 1.03 (1.0-0.65) Divorced/separated 2.09 (1.06-4.11) 1.07 (0.56-2.06) Widowed 2.83 (1.53-5.24) 1.77 (1.01-3.11) Age, 1 years Marital status Never married Education, Some postsecondary 0.86 (0.62-1.21) 0.61 (0.43-0.87) a adjusted for age, sex, family status, education b OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval Table 3.2.8. Univariate Odds Ratios of MDE among males and females according to sociodemographic variables Variable Age, >45 years Age, 10 years contin Univariate OR (95% CI)a Male, N=320 Female, N=678 0.97 (0.47-2.01) 1.77 (1.15-2.72) 0.93 (0.76-1.13) 1.16 (1.04-1.29) 0.99 (0.97-1.01) pfor trend=0.58 1 1.02 (1.00-1.03) pfor trend=0.006 1 Married 1.27 (0.46-3.47) 1.29 (0.70-2.39) Divorced/separated 2.65 (0.63-11.06) 1.89 (0.87-4.08) – pfor trend=0.40 1 2.78 (1.41-5.46) pfor trend=0.006 1 Age, 1 years Marital status Never married Widowed Education No postsecondary Some postsecondary 0.82 (0.39-1.71) 0.55 (0.37-0.83) OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval a 62 Table 3.2.9. Univariate Odds Ratios of comorbid MDE & GAD among males and females according to sociodemographic variables Variable Age, >45 years Age, 10 years contin N 7/10 17 Age, 1 years Marital status Single 17 * Univariate OR (95% CI)b Male, N=320 N Female, N=678 21/52 1.7 (1.0–2.89) 1.56 (0.76–3.21) 73 1.05 (0.87–1.27) 1.16 (1.02–1.33) 73 3 1.00 (0.99–1.02) pfor trend=0.58 1 9 1.01 (1.00–1.03) pfor trend=0.072 1 Married 14 1.17 (0.32–4.20) 35 1.36 (0.63–2.92) Divorced/separated 0 – 9 1.68 (0.64–4.43) – pfor trend=0.40 1 20 2.67 (1.16–6.17) pfor trend=0.073 1 Widowed Education No postsecondary 0 7 31 10 42 Some postsecondary 0.73 (0.27–1.97) 0.64 (0.39–1.04) adjusted for age, sex, family status, education b OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval * N with MD&CD a Several socioeconomic factors were significantly associated with positive diagnoses for females: being widowed (OR=2.7; 1.2–6.2) and a low level of education. (Table 3.2.7., Table 3.2.8., Table 3.2.9.) 3.3. Suicidality and mental disorders in primary care Significant differences were noted for a number of variables between suicidal and not-suicidal patients (Table 3.3.1). The suicidal patients were more likely to have a history of a mood disorder (OR=3.3; 1.4–7.7), lower education, than non suicidal patients. Suicidal patients were more likely to have a current MDE (OR=3.7; 2.2–6.6), social anxiety (OR=3.0; 1.2-8.1) posttraumic stress disorder (OR=3.4; 1.1-10.3) and GAD (OR=3.3; 1.9–5.6). Panic disorder was not significantly different between suicidal and notsuicidal patients. History of an alcohol use disorder also was not significantly different between groups, but was included in the analysis due to the comorbidity with mood disorder. The most important risk factor is the presence of a mental illness. Coexisted MDE and GAD were established in 90 patients (9%; 95% CI 7.2 to 10.7). Age and gender adjusted OR for coexisted MDE and GAD according suicidality was 4.56 (95% CI, 2.48 to 8.38). 63 Table 3.3.1. The differences of demographic and clinic variables between suicidal and not-suicidal patients Variable Gender, women Marital status, alone Single Married Divorced/separated Widowed Education Primary school Secondary school High school University Psychiatric treatment Major depressive episode (MDE) Anxiety disorders Social anxiety disorder Panic Posttraumic stress disorder Generalizes anxiety disorder (GAD) MDE&GAD Alcohol abuse Tertiles of HADS depression score, Lower, 0–2 Middle, 3–5 Upper, 6–21 Tertiles of HADS anxiety score, Lower, 0–4 Middle, 5–8 Upper, 9–21 Diabetes (2 type) Psychiatric diagnosis No Mood disorder Anxiety disorder Insomnia Other Cardiovascular disease diagnose Diabetes mellitus diagnose N OR (95% CI)b 678 1.36 (0.75–2.44) 181 596 97 123 1reference 0.88 (0.4–1.93) 1.25 (0.45–3.48) 0.79 (0.24–2.56) 70 259 228 434 205 152 3.6 (1.6-8.1) 1.05 (0.5-2.2) 1.9 (1.02-3.8) 1reference 2.6 (1.5-4.5) 3.7 (2.2-6.6) 32 27 23 180 3.0 (1.2-8.1) 1.96 (0.57–6.7) 3.4 (1.1-10.3) 3.26 (1.89–5.61) 0.030 0.28 0.032 <0.001 90 348 3.32 (1.97–5.6) 1.32 (0.78–2.24) <0.001 0.30a p for trend=0.006a 320 348 330 1reference 2.38 (1.07–5.27) 3.60 (1.64–7.89) 294 396 308 19 1reference 1.35 (0.61–2.89) 3.56 (1.61–6.95) 4.3 (1.38–13.4) 848 45 30 50 4 314 19 1reference 3.3 (1.4-7.7) 1.9 (0.6-6.7) 1.5 (0.5-4.4) 5.1 (1.02-25.1) 0.83 (0.43–1.58) 1.36 (0.76–2.45) a p 0.31a P for trend=0.81a 0.75 0.66 0.67 p for trend=0.015a 0.002 0.89 0.042 0.001 <0.001 0.033 0.001 p for trend=0.001a 0.46 0.001 0.012 p for trend=0.076a 0.007 0.28 0.42 0.046 0.58a 0.30a Age and gender adjusted OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval b 64 The odds ratios for suicidal ideation in relationship with other mental disorders were evaluated (table 3.3.1.1.). It was found that when other mental disorders presented (major depression episode, generalized anxiety disorder, MDE&GAD or any anxiety disorder) the odds ratios for suicidality increase. Table 3.3.1.1.Suicidal ideation and other mental disorders OR (95% PI)a Mental disorder Total; N=998 Men, n=320 Women, N=678 MDE and suicidal ideation 3.7 (2.2-6.6) 2.96 (1.60–5.47) 3.16 (1.03–9.70) GAD and suicidal ideation MDE&GAD, and suicidal ideation Anxiety disorders (1/ 4) and suicidal ideation 3.26 (1.89–5.60) 3.7 (1.2–11.4) 3.05 (1.63–5.68) 4.56 (2.47–8.38) 4.78 (1.2–18.7) 4.38 (2.2–8.69) 3.01 (1.76–5.12) 2.96 (1.60–5.47) 3.17 (1.04–9.69) Table 3.3.2. Multivariate analyses predicting suicidality in primary care population Variable Model 1 Psychiatric treatment MDE GAD Type 2 diabetes Alcohol abuse Model 2 Psychiatric treatment Coexisted MDE&GAD Type 2 diabetes N Adjusted OR (95% CI)a p 205 152 180 19 348 2.9 (1.17–3.73) 2.49 (1.26–4.94) 1.98 (1.01–3.88) 4.63 (1.41–15.15) 1.69 (0.98–2.98) 0.013 0.009 0.047 0.011 0.056 205 90 19 2.21 (1.25–3.92) 3.43 (1.77–6.62) 4.38 (1.37–13.99) 0.007 0<0.001 0.013 Model 3 Psychiatric treatment 205 2.25 (1.27–3.96) 0.005 Type 2 diabetes 19 1.13 (1.02–1.26) 0.002 Tertiles of HADS anxiety score, p for trend=0.013 Lower, 0–4 320 1reference Middle, 5–8 348 1.28 (0.58–2.83) 0.054 Upper, 9–21 330 2.62 (1.24–5.55) 0.012 a All models adjusted for age, sex, marital status, education, psychiatric treatment, body mass index, type 2 diabetes and additionally: Model 1 for diagnoses according to MINI – major depressive episode, social anxiety, posttraumic stress disorder, GAD, alcohol use; Model 2: all variables in model 1 and coexisted MDE&GAD; Model 3: for tertiles of both, HADS depression and anxiety score. b OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval 65 Multivariate analyses suggest that suicidality is mainly associated with depression and anxiety, generally with coexisted MDE&GAD, with type2 diabetes and with the lower alcohol influence. Subjects with both generalized anxiety disorder and major depressive disorder were at greatest risk of suicidality (Table 3.3.2). 3.4. Mental disorders and general medical conditions in primary care Primary reasons for consultation are presented in Table 3.4.1., with cardiovascular (31.5%), acute colds (10.4%) and musculoskeletal problems (9.4%) being the most frequently cited. A psychiatric problem as the main reason for the GP visit was not mentioned. Table 3.4.1. Main reason for the consultation of the patients Somatic diseases n (%) The cardiovascular system (CVD) 314 (31.5) Acute colds 104 (10.4) The musculoskeletal system and the connective tissue 94 (9.4) The digestive system 69 (6.9) The respiratory system 33 (3.3) Ophthalmology 22 (2.2) Endrocrin (Diabetes mellitus) 19 (1.9) Administrative reason 176 (17.6) Other 167 (16.7) 3.4.1. The association of depression and anxiety symptoms, with general medical conditions in primary care patients The relationship of diagnostic MDE and psychiatric medical category was stronger for female in comparison to men (OR=3.79; 95% CI 1.738.31).MDE as associated with suicidality especially in women. The association of GAD and psychiatric treatment was stronger in men (OR=2.53; 95% CI 1.68-3.78) as well as with both MDE&GAD disorders and psychiatric treatment (OR=3.39; 95% CI 1.19-9.65). MDE&GAD disorders was stronger associated with psychiatric treatment (OR=3.36; 95% CI 2.1-5.3) and suicidality (OR= 4.56; 95% CI 2.47-8.38). The anxiety disorders were stronger associated with psychiatric treatment in females 66 (OR=2.94; 95% CI 2.0-4.33), particularly in the category of cardiovascular diseases (OR=2.32; 95% CI 1.09–4.94), but there was also a significant association with diabetes mellitus in males (OR=5.54; 95% CI 1.6–19.18) Neurotic illness symptoms were less frequent associated when acute cold presented among males (OR=0.31; 95% CI 0.13–0.74). Suicidality has stronger associations with GAD (OR=3.7; 95% CI 1.2-11.4) and with both MDE& GAD (OR=4.78; 95% CI 1.2-18.7) in male. Significant association was found in males with GAD and diabetes (OR=6.88; 95% CI 1.98-23.8). Table 3.4.1.1. The probability of having mood or anxiety disorders among males and females according to somatic diagnosis OR (95% CI)a All; N=998 Male, n=320 Female, N=678 Psychiatric treatment. 2.68 (1.84-3.91) 2.29 (1.49-3.53) 3.79 (1.73-8.31) CVD 1.33 (0.92-1.90) 1.31 (0.86-1.98) 1.39 (0.67-2.91) Diabetes 1.49 (0.49-4.57) 1.79 (0.47-6.87) 1.2 (0.14-10.1) Suicidality 3.7 (2.2-6.6) 2.96 (1.60–5.47) 3.16 (1.03–9.70) Psychiatric treatment 2.52 (1.76-3.60) 2.53 (1.68-3.78) 1.93 (0.85-4.39) CVD 1.53 (1.10-2.15) 1.39 (0.95-2.06) 2.16 (1.09-4.29) Diabetes 3.49 (1.35_9.19) 6.88 (1.98-23.8) 1.06 (0.13-8.87) Suicidality 3.26 (1.89–5.60) 3.7 (1.2–11.4) 3.05 (1.63–5.68) Psychiatric treatment 3.36 (2.1–5.3) 3.39 (1.19–9.65) 3.14 (1.89–5.22) CVD 1.36 (0.86-2.13) 1.19 (0.43–3.33) 1.41 (0.85–23.3) Diabetes 2.76 (0.89-8.52) 2.64 (0.31–22.7) 3.19 (0.83–12.3) Suicidality 4.56 (2.47–8.38) 4.78 (1.2–18.7) 4.38 (2.2–8.69) Psychiatric treatment 2.88 (2.05–4.04) 2.12 (0.99–4.56) 2.94 (2.0–4.33) CVD 1.44 (0.99–2.07) 1.26 (0.82–1.94) 2.32 (1.09–4.94) Diabetes 2.7 (1.09–6.96) 5.54 (1.60–19.18) 0.90 (0.11–7.53) Acute Cold 0.45 (0.24–0.86) 0.31 (0.13–0.74) 0.93 (0.35–2.45) MDE GAD MDE+GAD Neurotic illness (1 of 4) Suicidality 3.01 (1.76–5.12) 2.96 (1.60–5.47) 3.17 (1.04–9.69) OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval a 67 MDE&GAD was associated with a significant number of psychiatric treatment in comparison MDE and/or GAD alone, (OR=3.36; 95% CI 2.478.38 vs. OR=2.68; 95% CI 1.84-3.91/ OR=2.52; 95% CI 1.76-3.6), but only GAD has significant association wit both general medical conditions and suicidality. Suicidality was stronger associated when both mental disorders (MDE&GAD) were presented in both gender, especially in men (OR=4.78; 95% CI, 1.2-11.4) (Table 3.4.1.1). A number of possible mediators that could explain an association between depressive symptoms and cardiovascular diseases were evaluated, including biomedical risk factors, medical treatments, and sociodemographic data. HADS. Of all 998 patients, 42.5% showed a HADS-A of 8 or more, whereas 29.8% showed a HADS-D of 8 or higher, respectively. Of all patients, 21.7 and 19.4% showed a HADS-A of 8–10 and 11 or more, whereas 11.9 and 7.6% showed a HADS-D of 8–10 and 11 or higher, respectively. Both summary scores were highly correlated (Spearman correlation coefficient r=0.59, p<0.0001). Frequency of cardiovascular risk factors is shown in Table 3.4.1.2 Table 3.4.1.2 Frequency of cardiovascular risk factors Characteristics All; N=998 Male, n=320 Female, N=678 p Menopausal Cardiovascular diagnoses Diabetes 314 (31.5) 101 (31.6) 213 (31.4) 0.51 19 (1.9) 8 (2.5) 11 (1.6) 0.34 Height, cm (SD) 168.9 (9.2) 177.8 (7.5) 164.8 (6.5) <0.001 Weight, kg (SD) 74.7 (15.8) 84.5 (14.7) 70.1 (14.2) <0.001 26.2 (5. 1) 26.7 (4.1) 25.9 (5.4) p=0.008 212 (21.3) 67 (20.9) 145 (21.5) 2=0.038 p=0.87 77.03 (11.6) 76.9 (11.6) 77.1 (11.6) 0.854 Systolic BP(SD) 135.4 (21.3) 139.4 (20.1) 133.4 (21.6) <0.001 Diastolic BP(SD) Hypertension (BP >140/90mmHg) Pulse pressure 82.4 (11.4) 84.4 (11.4) 81.5 (11.2) <0.001 398 (39.9) 153 (47.8) 245 (36.2) 2=12.2 p=0.001 52.9 (15.1) 55.1 (14.9) 52.0 (15.1) 0.003 2 BMI, kg/m (SD) BMI >30 kg/m 2 Heart rate (SD) 349 (51.6) Blood pressure A significantly higher rate of CVD was observed in the tertile of patients with the highest mean anxiety score (9–20) as compared with the tertile with the lowest score (0–4). Age and sex adjusted odd ratio was 1.49 (95% CI 68 1.06 to 2.08, p = 0.021). After adjusting for age, sex, duration of school education, family status, history of diabetes mellitus, body mass index, clinical center event rate remained significantly elevated for the highest tertile: odd ratio = 1.88 (95% CI 1.22 to 2.89, p = 0.004). The odd ratio associated with an increased HADS-A was similar after adjustment for multiple covariates and it was 2.05 and still statistically significant after further adjustment for use of cardiac medication at baseline. Notably, if symptoms of anxiety and depression were considered simultaneously in the final model 4, in the tertile of patients with the highest mean anxiety score (9–20) significant odd ratio was 2.27 (95% CI 1.34– 3.85, p=0.002). In contrast, compared to patients with a HADS-D in lower tertile (<3) CVD rate remained elevated for the highest tertile but not significantly: odd ratio = 1.6 (95% CI 0.98 to 2.65, p = 0.059) (Table 3.4.1.3.). Table 3.4.1.3. Association of anxiety and depressive symptoms score categories with CVD Tertile of Results of multivariate analysis, Odd Ratio (95% CI) a HADS Model 1 Model 2 Model 3 Model 4 score HADS anxiety Lower, 1 Reference 1 Reference 1 Reference 1 Reference 0–4 Middle 0.79 (0.56–1.10) 1.38 (0.91–2.11) 1.33 (0.84–2.11) 1.39 (0.87–2.24) (5–8) Upper 1.49 (1.06–2.08) 1.88 (1.22–2.89) 2.05 (1.28–3.28) 2.27 (1.34–3.85) (9–21) HADS depression Lower, 1 Reference 1 Reference 1 Reference 1 Reference 0–2 Middle, 1.86 (1.31–2.65) 1.56 (1.06–2.28) 1.53 (0.99–2.37) 1.47 (0.94–2.30) 3–5 Upper, 2.78 (1.96–3.95) 1.77 (1.19–2.63) 1.78 (1.14–2.78) 1.6 (0.98–2.65) 6–21 CVD, cardiovascular disease. Model 1 adjusted for age and sex. Model 2 adjusted for age, sex, body mass index, duration of school education, family status, history of diabetes mellitus, clinical center. Model 3 adjusted for covariates of model 2 and additionally for use of cardiac medication. Model 4 adjusted for covariates of model 3 and symptoms of anxiety and depression considered simultaneously in one model. a OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval. 69 Table 3.4.1.4. Symptoms of Anxiety in relation to characteristics of population N Variable Tertiles of HADS Anxiety scores Lower 3rd Middle 3rd Upper 3rd (0-4) (5-8) (9-20) n=294 n=396 n=308 1 2 3 Gender <0.001 Male (%) 320 36.3 Female (%) 678 26.3 Age (yrs) Education High school graduate or less (%) Marital status p 678 662 40.9 22.8 39.1 53.3±19.3 1,2 25.9 46.2±18.2 34.7 1,2 38.3 52.3±18.12,3 <0.001 35.8. 0.037 123 24.4 34.1 41.5 0.025 992 26.3±4.6 25.9±5.1 26.4±5.4 0.37 Hypertension (%) 398 32.7 35.4 31.9 0.06 CAD (%) 314 28.7 32.5 39.9 <0.001 Diabetes (%) 19 10.5 36.8 52.6 0.06 Systolic 998 136.1±19.8 133.5±11.9 137.1±22.92,3 0.07 Diastolic 998 82.3±10.6 82.6±11.9 82.3±11.3 0.93 Heart rate, beat/min 998 75.7±10.6 77.3±11.8 Cardiac 172 32.6 36.0 31.4 Anxiolitic 143 21.7 25.9 52.4 Widowed/separated Body mass index (kg/m2) History of Blood pressure (mmHg) 77.9±12.3 1,3 0.044 Medication use 0.45 23 Antidepressants 4.3 43.5 52.2 * Anxiety scores were assessed using a chi-square test for categorical data and analysis of variance for continuous variables (ANOVA). The p value is based on the difference among the 3 groups: 1,2 - p value is based on post hoc comparison Table 3.4.1.4 and Table 3.4.1.5. shows the age and sex-adjusted mean values or frequency of various factors links to CVD-events associated with HADS-A and HADS-D The prevalence of other traditional CVD risk factors (except for age, HR, Pulse pressure, systolic BP) was similar among the tertiles of anxiety scores. 70 Table 3.4.1.5. Symptoms of Depression in relation to characteristics of study population Variable N Tertiles of HADS Depression scores Lower 3rd Middle 3rd Upper 3rd (0-2) (3-5) (6-21) n=320 n=348 n=330 Gender p 0.012 Male (%) 320 37.2 35.6 27.2 Female (%) 678 29.6 34.5 35.8 Age (yrs) 678 43.8±17.9 49.6±18.9 56.8±17.4 <0.001 Education High school graduate or less (%) Marital status 662 29.2 33.7 37.0 0.14 Widoved/separated 123 17.1 24.4 58.5 <0.001 992 25.3±4.6 26.1±5.2 27.0±5.02,3 <0.001 Hypertension (%) 398 31.2 33.7 35.2 0.49 CAD 314 20.7 35.7 43.6 <0.001 Diabetes (%) 19 21.1 15.8 63.2 0.018 Systolic 998 136.1±19.8 133.5±11.91,2 137.1±22.91,3 0.001 Diastolic 998 81.9±11.0 82.4±11.9 83.0±11.1 0.44 Heart rate, beat/min 998 76.9±10.9 76.7±12.6 77.4±11.2 0.73 Cardiac 172 23.8 35.5 40.7 <0.001 Anxiolytics 143 14.7 33.6 51.7 <0.001 Body mass index (kg/m2) History of Blood pressure (mmHg) Medication use Antidepresents 23 8.7 26.1 65.2 <0.001 * depression scores were assessed using a chi-square test for categorical data and analysis of variance for continuous variables (ANOVA). The p value is based on the difference among the 3 groups. After adjustment for age and sex we found an increased systolic blood pressure associated with HADS-A (p=0.07) and HADS-D (p=0.001). Furthermore, body mass index was higher in subjects with a HADS-D of 6 or higher (p<0.001). We found no statistically significant association between BMI and HADS-A. (Table 3.4.1.4.; Table 3.4.1.5). We found no statistically significant association between history of hypertension in both HADS-A and HADS-D, but the history of CAD has been associated with 71 higher HADS-D numbers in the upper tertile. Relationship between anxiety and depression score and CVD is presented in the Table 3.4.1.6. and Table 3.4.1.7. Table 3.4.1.6. Relationship between Anxiety Score and CVD OR (95% CI)a p Age-adjusted 1.05 (1.01–1.09) 0.010 Multivariate-adjusted† 1.07 (1.03–1.11) 0.001 Age-adjusted; Trend 1.07 (1.06–1.09) <0.001 Multivariate-adjusted, Trend 2.65 (1.91–3.68) <0.001 1.07 (1.06–1.09) <0.001 Model Continuous anxiety score* Tertiles of anxiety score Dichotomous anxiety score ≥8 Age-adjusted Multivariate-adjusted 1.54 (1.10–2.14) 0.011 *Based on logistic regression. †Adjusted for age, gender, education, hypertension, diabetes, body mass index, and use of cardiac medication. a OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval Anxiety score alone (per unit increase) was significant in either age or multivariate adjusted models in predicting the risk of CVD (OR 1.05 95% CI 1.01 - 1.09, p = 0.010; multivariate-adjusted OR 1.07 95% CI 1.03 1.11, p = 0.001 (Table 3.4.1.6.). Table 3.4.1.7. Relationship between Depression Score and CVD OR (95% CI)a p Age-adjusted 1.07 (1.06–1.08) <0.001 Multivariate-adjusted† 1.05 (0.99–1.09) 0.056 Age-adjusted; Trend 1.07 (1.06–1.08) <0.001 Multivariate-adjusted, Trend 1.26 (1.02–1.56) <0.033 1.07 (1.06–1.08) <0.001 Model Continuous depression score* Tertiles of depression score Dichotomous depression score ≥8 Age-adjusted Multivariate-adjusted 1.38 (0.92–2.06) 0.117 *Based on logistic regression. †Adjusted for age, gender, education, hypertension, diabetes, body mass index, and use of cardiac medication. a OR – odds ratio, CI – confidence interval; odds ratio was statistically significant when 1 was not included into its 95% confidence interval 72 Trend analyses of anxiety score tertiles provided evidence that anxiety score could independently predict risk of CVD (multivariate-adjusted OR 2.65 95% CI 1.91 - 3.68) (p < 0.001). After dichotomizing the mean anxiety score at the predetermined cutoff point of 8, we observed an age-adjusted OR of 1.07 (95% CI 1.06 -1.08), p < 0.001, and a multivariate adjusted OR of 1.54 (95% CI 1.10 to 2.14, p = 0.011. Fig. 3.4.1.1 differences of BMI in relation to suicidal ideation (SUI) in 998 primary care patients. The results, adjusted by gender presented in Fig. 3.4.1.2. Fig. 3.4.1.1 differences of BMI in relation to suicidal ideation (SUI) in 998 primary care patients BMI was significantly higher in patients with suicidal ideation (SUI): (27.2±5.7 vs. 24.4±4.6, p=0.004) and remained higher in men with suicidal ideation (29.2±0.6 vs. 24.96±3.9, p=0.005) and in women with suicidal ideation (SUI) (26.54±6.3 vs. 24.27±4.8, p=NS). 73 Fig. 3.4.1.2. differences of BMI in relation to suicidal ideation (SUI) adjusted by gender in 998 primary care patients. Patients with suicidality (SI) alone had higher BMI vs. depressed patients, respectively (27.75± 5.74 vs. 25.37 ±4.83; p=0.011). Those who had no current MD as well as SI were slightly overweight (26.27±5.05 and 26.07±4.98), p=NS. (Fig. 3.4.1.3.) Fig. 3.4.1.3. Differences in BMI in relation to suicide ideation and depression alone in 998 primary care patients. 74 Patients with suicidality (SI) alone had higher BMI vs. depressed patients, respectively (27.75± 5.74 vs. 25.37 ±4.83; p=0.011). Those who had no current MD as well as SI were slightly overweight (26.27±5.05 and 26.07±4.98), p=NS. For the patients with co-morbid depression with SUI the BMI was higher in men (30.15±3.6 vs. 24.97±3.9, p=0.03), but not in women (25.3±5.7 vs. 24.26±4.8, NS). (Fig. 3.4.1.4.) Fig. 3.4.1.4. Differences in BMI in relation to comorbid suicide ideation and depression in 998 primary care patients. 3.4.2. The association of thyroid immunity with blood pressure and body mass index in primary care patients Among 465 primary care patients, 96 patients (21%) were obese (BMI > 30 kg/m2), 190 (41%) patients were diagnosed with hypertension, and 107 (23%) patients were diagnosed with coronary artery disease. One hundred and seventy-seven (38%) patients were receiving treatment for hypertension. Forty-three (9%) patients were taking diuretics, 86 (18%) patients were taking β-blockers, 136 (29%) patients were taking ACEs, and 79 (17%) patients were taking calcium channel blockers. Fourteen (3%) patients were diagnosed with diabetes. 75 Ultrasonographic evaluation of the thyroid gland revealed that 115 patients (25%) had a hypo-echoic thyroid pattern, indicating AITD. On ultrasonographic evaluation women had a higher prevalence of a hypoechoic thyroid pattern of the thyroid gland (29 and 13%, p < 0.001) compared to men. Women also had a lower systolic BP (134 ± 21 and 140 ± 21 mmHg, p = 0.003), a lower diastolic BP (81 ± 11 and 84 ± 11 mmHg, p = 0.01), and a lower prevalence of BP > 140/90 mmHg (33 and 43%, p = 0.04) compared to men. Because there were significant gender differences in endocrine and cardiovascular status, data pertaining to thyroid immunity were analyzed separately for men and women. Table 3.4.2.1 Association of Hypo-Echoic Thyroid Pattern with Obesity and with Cardiovascular Measurements in 465 Men and Women in Primary Care Setting [mean ± SD, n (%)] Women, n = 340 (73) Normo-echoic Hypo-echoic thyroid thyroid n=241 (71) n=99 (29) Variable p <0.00 Age (years) 47±20 64±14 Menopausal 105 (44) 84 (85) Hypertension 83 (34) 54 (55) 0.001 Coronary artery disease 45 (19) 33 (33) 0.005 Diuretics 22 (9) 12 (12) - Blockers 31 (13) 30 (30) 0.43 <0.00 ACE inhibitors 61 (25) 42 (42) 0.003 Calcium channels blockers 39 (16) 24(924) Any antihypertensive 75 (31) 55 (56) 0.09 <0.00 4 (2) 5 (5) 0.13 Body mass index (kg/m ) 25±5 28±5 0.04a Body mass index >30 kg/m2 40 (17) 29 (29) 0.01 Heart rate (beats/min) 79±12 77±12 0.7a Systolic BP (mmHg) 130±21 141±21 0.5a Diastolic BP (mmHg) 80±10 84±11 0.03a 1 <0.00 1 Cardiovascular diagnoses Medications use Diabetes 2 76 1 1 BP >140/90 mmHg 66 (27) 45 (45) 0.001 Table 3.4.2.1 continued Men, n = 125 (27) Normo-echoic Hypo-echoic thyroid thyroid n=109 (87) n=16 (13) 51 ±20 61±14 Variable Age (years) p 0.05 Cardiovascular diagnoses Hypertension 41 (38) 12 (75) 0.006 Coronary artery disease 25 (23) 4 (25) 1.00 Diuretics 6 (6) 3 (19) 0.09 - Blockers 19 (17) 6 (38) 0.09 ACE inhibitors 26 (24) 7 (44) 0.13 Calcium channels blockers 12 (11) 4 (25) 0.13 Any antihypertensive 38 (35) 9 (56) 0.17 5 (5) 0 (0) 1.00 Body mass index (kg/m ) 26±4 29±4 0.006a Body mass index >30 kg/m2 19 (17) 8 (50) 0.007 Heart rate (beats/min) 77±11 80±17 0.3a Systolic BP (mmHg) 138±21 153±17 0.03a Diastolic BP (mmHg) 83±12 88±7 0.2a BP >140/90 mmHg a Adjusted for age Value in boldface p<0.05 42 (39) 12 (75) 0.007 Medications use Diabetes 2 Table 3.4.2.1 shows the association of hypo-echoic thyroid pattern with BMI and with cardiovascular measurements in these primary care patients. Men and women with hypo-echoic thyroid pattern were significantly older (p = 0.05 and p < 0.001, respectively), so other comparisons were adjusted for age. It was found that men and women with a hypo-echoic thyroid pattern had higher BMIs (p = 0.006 and 0.04, respectively) compared to men and women with a normo-echoic thyroid pattern. Among men and women with a hypo-echoic thyroid pattern, there was a higher prevalence of patients with a clinical diagnosis of hypertension (p = 0.006 and 0.001, respectively), a higher prevalence of patient with BP > 140/90 mmHg (p = 0.007 and 0.001, respectively), and a higher prevalence of patients with 77 BMI > 30 kg/m2 (p = 0.007 and 0.01, respectively) compared to men and women with a normo-echoic thyroid. Women with hypo-echoic thyroid in comparison to women with normo-echoic thyroid were more likely to use βblockers, ACEis, or any antihypertensive medications (p < 0.001, p = 0.003, and p < 0.001, respectively) and more likely to have a clinical diagnosis of coronary artery disease (p = 0.005). Women with a hypo-echoic pattern in comparison to women with normo-echoic pattern had higher diastolic BP (p = 0.03). Men with a hypo-echoic thyroid pattern in comparison to men with normo-echoic thyroid had higher systolic BP (p = 0.03). Fig. 3.4.2.1. Thyroid echoic pattern and prevalence of obesity (BMI > 30 kg/m2) in primary care female patients as a function of menopausal status [n (%)]. 78 Fig. 3.4.2.2. Thyroid echoic pattern and prevalence of increase blood pressure (BP) in primary care female patients as a function of menopausal status [n (%)]. When women were divided into two groups in relation to their menopausal status, only in premenopausal women a hypo-echoic thyroid pattern was associated with an increased prevalence of obesity (33 and 8%, respectively, p = 0.01) and BP > 140/90 mmHg (33 and 11%, p = 0.03) (Fig. 3.4.2.1 and 3.4.2.2). Premenopausal women with hypo-echoic thyroid pattern had higher systolic BP (133 ± 16 mmHg and 120 ± 14 mmHg p < 0.001), higher diastolic BP (84 ± 11 mmHg and 77 ± 10 mmHg, p < 0.001), and higher BMI (28 ± 5 and 22 ± 4 kg/m2, p < 0.001) compared to premenopausal women with normo-echoic thyroid pattern. Postmenopausal women with hypo-echoic thyroid pattern had no significant differences in BP or BMI compared to postmenopausal women with normo-echoic thyroid pattern. When women were divided into two groups in relation to their thyroid echoic pattern, only in women with normo-echoic thyroid pattern postmenopausal status was associated with increased prevalence of obesity (26 and 8%, p < 0.001) and increased BP (49 and 11%, p < 0.001). In hypoechoic women there were no significant differences in prevalence of obesity and in prevalence of increased BP > 140/90 mmHg with respect to their menopausal status. 3.4.3. Mood and thyroid immunity assessed by ultrasonographic imaging in primary care Among 474 primary care patients, underwent an ultrasonographic imaging, 56 (12%) had scores on the subscale of depression of the HADS higher then 10, indicating a depressive disorder; 121 (26%) had scores on the subscale of anxiety higher then 10, indicating an anxiety disorder; 169 (36%) had specific MINI diagnoses of depression or anxiety disorder. Ultrasonographic evaluation of the thyroid gland revealed that 122 patients (26%) had a hypoechoic thyroid pattern, indicating AITD. Women compared to men had higher scores on the subscale of depression (5.9±4.2 vs. 4.9±3.3; p=0.01) and on the subscale of anxiety (8.1±4.4 vs.6.7±4.0; p=0.001) of the HADS. According to the MINI women had higher prevalence of generalized anxiety disorder (28% vs. 19%; p=0.04) and higher total prevalence of depression or anxiety disorder (38% vs. 29%; p=0.05). On ultrasonographic evaluation women compared to men had a higher prevalence of a hypo-echoic thyroid pattern (30% vs.14%; p=0.001). 79 Because there were significant gender differences in endocrine and mental status, data pertaining to thyroid immunity were analyzed separately for men and for women. Men and women with hypo-echoic thyroid compared to those with normo-echoic thyroid were significantly older (61±14 vs. 51±20; p=0.05; and 64±14 vs. 47±20; p<0.001; respectively), so other comparisons were adjusted for age. Fig. 3.4.3.1. Differences of scores on subscales of depression and anxiety of the Hospital Anxiety and Depression Scale (HADS) in relation to echoic thyroid pattern in 348 female primary care patients (adjusted for age). Fig. 3.4.3.1. shows that women with a hypo-echoic thyroid compared to women with normo-echoic thyroid had higher scores on the anxiety subscale of the HADS (9.0±4.6 vs. 7.8±4.4; p=0.03). Scores on the depression subscale of the HADS also were higher among women with a hypo-echoic thyroid; however, this difference lost statistical significance after adjusting for age. Echoic thyroid pattern was not associated with the HADS scores in men nor with the prevalence of MINI diagnoses in men or in women. When women were divided into two groups in relation to their menopausal status, only pre-menopausal women with hypo-echoic thyroid compared to those with normo-echoic thyroid had higher prevalence of use of psychiatric medication (31% vs. 6%; p=0.001), and higher prevalence of 80 depression according to the HADS (19% vs. 3%; p=0.02) but there were no difference in the prevalence of specific mental disorders diagnosed by MINI (Table 3.4.3.1). However, prevalence of total MINI depression or anxiety disorders tended to be higher (50% vs. 29%; p=0.09) in pre-menopausal women with hypo-echoic thyroid compared to those with normoechoic thyroid. There were no significant differences in regards to echoic thyroid pattern in the prevalence of mood disorders or the use of psychiatric medication in post-menopausal women. Table 3.4.3.1. Thyroid echoic pattern and prevalence of mental disorders in primary care female patients before and after menopause (n (%)) Variable Pre-menopausal women, n = 153 Normo-echoic Hypo-echoic thyroid (n=137) thyroid (n=16) p Hospital anxiety and depression scale Depression >10 4 (3) 3 (19) 0.02 Anxiety >10 27 (20) 6 (38) 0.2 21 (15) 3 (19) 0.7 Panic disorder 6 (4) 2 (13) 0.2 Social phobia 8 (6) 2 (13) 0.3 Generalized anxiety 30 (22) 5 (31) 0.4 Depression or Anxiety disorder 40 (29) 8 (50) 0.09 Use of psychiatric medications 8 (6) 5 (31) 0.001 Use of benzodiazepines 6 (4) 4 (25) 0.002 MINI diagnoses Major depression Anxiety disorders Table 3.4.3.1. continued Variable Post-menopausal women, n = 195 Normo-echoic Hypo-echoic thyroid (n=107) thyroid (n=88) p Hospital anxiety and depression scale Depression >10 24 (22) 19 (22) 0.9 Anxiety >10 33 (31) 35 (40) 0.09 32 (30) 28 (32) 0.8 Panic disorder 2 (2) 2 (2) 0.8 Social phobia 2 (2) 1 (1) 0.7 MINI diagnoses Major depression Anxiety disorders 81 Generalized anxiety 35 (32) 28 (32) 0.9 Depression or Anxiety disorder 46 (43) 39 (44) 0.9 Use of psychiatric medications 27 (26) 20 (23) 0.7 Use of benzodiazepines 22 (21) 17 (20) 0.8 82 4. DISCUSSION 4.1. Screening for depression and anxiety disorders in primary care patients The present study indicates that in primary care patients HADS-D is a sensitive and accurate screening instrument for diagnoses of MDE when a cutoff score of 6 or more is used. These findings support the results from the study performed in a Chinese elderly general practice population [153] demonstrating that an optimal balance between sensitivity and specificity when HADS-D is used for screening of depression was at a cutoff score of 6 or more. However, the standard for comparison in that study was not reported. Studies that used the Structured Clinical Interview for DSM (SCID) [47] and Structured Clinical Assessment for Neuropsychiatric disorders (SCAN) [255] as a standard for comparison in screening for MDE in general practice found optimal cutoff scores of 10 or more and 8 or more, respectively, for HADS-D. These differences may be explained by different sample sizes and profile of study populations as well as by different standards for comparisons used. The results of this study suggest that HADS-D is not an optimal screening instrument for dysthymia. The AUC was largest at a cutoff score of 7 or more— however, with low accuracy and sensitivity. Results from other studies suggest that dysthymia and minor depression are prevalent among general and hospitalized populations and strongly predict MDE [71; 79; 282]. However, other instruments other than HADS-D must be used to screen for these minor depressive disorders. Other screening instruments for depression, such as the Edinburgh Postnatal Depression scale or the Center for Epidemiological Studies Depression scale, were validated against the MINI in different populations with sensitivity similar to HADS-D (0.82 and 0.85, respectively) [106; 120]. In this study HADS-A showed variable performance, from good to fair, identifying different MINI diagnoses of anxiety disorders at a cutoff point of 9 or more. It supports findings from other studies performed in general practice populations with the Clinical Interview Schedule as a standard for comparison [28; 64] that the cutoff point of 9 or more of HADS-A is optimal in screening for anxiety disorders.[209] recently reported that HADS-A is an adequate screening instrument for GAD when a cutoff score of 9 or more was used. We found no studies on the validation of screening instruments other than HADS-A for anxiety against the MINI. 83 There is a debate in the literature on how many dimensions there are in HADS based on factor analysis [61; 186]. There are studies that suggest that HADS contains two, three, or even four dimensions in a 14-item questionnaire. In this study we did not take this issue into consideration because we focused on how precise HADS is identifying MINI diagnoses. We used HADS as a twodimensional questionnaire for screening for depressive disorders and anxiety disorders. The internal consistency measured by the Cronbach’s alpha of HADS-D. and HADS-A was found to be satisfactory. It fulfilled the recommendation that Cronbach’s alpha should be at least 0.60 for a self-report instrument to be reliable [205]. However, the value of Cronbach’s alpha of HADS-D did not reach the recommended level of 0.80 for a screening instrument to be reliable. These results are in line with other reports where internal consistency measured with Cronbach’s alpha has been found to be 0.82–0.90 for HADS-D and 0.78–0.93 for HADS-A [170; 196; 197; 246]. The HADS-D scores as well as HADS-A scores obtained in our study are similar to HADS scores obtained in primary care patients reported by others [241]. The prevalence of a MINI diagnosis of MDE in our study (22%) is similar to the prevalence of depression reported in other primary care studies employing the MINI (15–20%) [80; 82]. However, employment of other instruments, such as the SCID, shows a lower prevalence of MDE [281] in a population of primary care patients. We do not know studies other than ours that used the MINI to diagnose anxiety disorders in primary care patients. Employing other instruments to assess the prevalence of anxiety disorders in primary care patients it fluctuates from as high as 44% using the Primary Care Evaluation of Mental Disorders [232] to about 15% using the SCID [201]. These significant fluctuations in the prevalence of depression and anxiety disorders depending on diagnostic instrument used plays an important role in estimating validity of the screening instrument. The diagnostic instruments that serve as a ‘‘standard for comparison’’ may be an important confounder validating different screening instruments for mental disorders. In summary, the results from this validation study of HADS against the MINI reveals that HADS is an adequate screening instrument for MINI diagnoses of major depressive episode and anxiety disorders, but not for dysthymia, in a population of primary care patients. It should be mentioned that both subscales of the HADS, HADS-D and HADS-A, when used as a screening instrument will miss about 20% of patients with depression or anxiety disorders. Whenever it is possible the MINI or other structured diagnostic interview must be used to diagnose mood or anxiety disorder. 84 4.2. The prevalence of mood and anxiety disorders in primary care The results of this study indicate that the prevalence of mental disorders and suicide ideation is very high in primary care and the recognition of them is very poor: depression was found in 4.5%, anxiety disorders in 3.0% of patients only by FP. The prevalence of mental disorders in primary care in Europe has been estimated to range approximately between 20 and 55% [7; 8; 10; 14] with only 23% of pure anxiety cases being recognized [230]. In the present study GAD was found in (18.1%) and the rates of major depression was found for 15.2% are also comparable with the data from the recent paper from National Institute for Health and Clinical Excellence where it was stated that common mental health disorders, such as depression, generalised anxiety disorder, panic disorder, obsessive-compulsive disorder , post-traumatic stress disorder (PTSD) and social anxiety disorder, may affect up to 15% of the population at any one time [(11i)] The WHO survey (diagnosis based on ICD - 10 criteria) shows the prevalence of major depression with 16% in The Netherlands, 13% in France and 11% in Germany [274; (7i)]. In the present study PTSD was found in 2.3%, social anxiety - in 3.2% and panic disorder was found in 2.7% of study participants, when evaluated by standard instrument. A criterion standard primary care study (by Kroenke and colleagues) found two-fold lower number of GAD (7.6%), .but higher numbers of panic disorder (6.8% ), PTSD (8.6%) and social anxiety disorder (6.2% ), when evaluated with 7-item anxiety measure (Generalized Anxiety Disorder [GAD]-7 scale) [145]. Moreover, McManus and colleagues reported (the Office of National Statistics 2007 national survey) the 1-week prevalence of individual common mental health disorders which concluded to vary considerably. The 1-week prevalence rates were 4.4% for generalised anxiety disorder, 3.0% for PTSD, 2.3% for depression, 1.4% for phobias, 1.1% for OCD, and 1.1% for panic disorder. Estimates of the proportion of people who are likely to experience specific disorders during their lifetime are from 4% to 10% for major depression, 2.5% to 5% for dysthymia, 5.7% for generalised anxiety disorder, 1.4% for panic disorder, 12.5% for specific phobias, 12.1% for social anxiety disorder, 1.6% for OCD and 6.8% for PTSD. However, despite the substantial disability associated with each anxiety disorder and the availability of effective treatments, only a minority of patients (15% to 36%) with anxiety are recognized in primary care [49; 131; 160; 175]. The possible explanation of the different results for GAD found by Kroenke could be a design as the study included a nonrandom sample of 85 selected primary care practices. The differences seen in these two primary care studies could address the question on the screening methodology and could serve for future discussions on choosing the screening tool to use in primary care. The recognition of any mental disorders by family physician is poor all over the world [113; 158; 293; etc.). The most common diagnosis made by FP in the present study was insomnia (5.0%). Insomnia has historically been considered a symptom of depression and recent evidence suggests that insomnia is a risk factor for depression onset and recurrence, especially in eldery [2i]. Whether insomnia represents a separate disorder remains open to question. A full understanding of the relationship between those two disorders awaits a full description. Alcohol abuse and suicidal ideation was not detected at all by family doctor, whilst 54.4% of patients had alcohol abuse diagnosis and 6.1% of patients had suicidality diagnosis, after evaluated by MINI. The cultural stigma could be suggested as reason for such results, not only awareness of thee problem and screening issues. We found that only 44.8 % of patients, who had no psychiatric diagnosis after general practitioner evaluation had no psychiatric disorders detected by MINI as well. In comparison to MINI anxiety diagnosis was found in 7% only by GP as well as low number of depression diagnosis (10.5%). Most common disorders which are omitted by general practitioners – alcohol abuse or dependence and suicidal ideation. In general, family physicians diagnosed depression for 45 patients (4.5%) and anxiety for 30 (3%) patients only in the present study. Patients having generalized anxiety disorder by MINI quite often are considered as having mood disorders (48.9 % patients), thus here is a great risk of ineffective treatment. Yet most patients having major depressive episode are correctly classified as having mood disorders by GP. Unfortunately, over 60 percent of major depressions are accompanied by varying levels of anxious feelings and behaviour, according the literature [29; 133]. Both anxiety and depression are frequently treated in much the same manner, which may explain why the two disorders are so often confused. Antidepressant medication is often used for anxiety, while behavioural therapy frequently helps people overcome both conditions. Only a minority of the present study patients with GAD and/or MD was treated with an antidepressant and almost half of subjects with GAD and/or MD were treated with a tranquilizer (25% anxiolytics). In the present study almost in 90% of alcohol abusers found by MINI there were no diagnosis of mental disorder by primary care physician as well as in 74% of patients with suicide ideation. Patients with alcohol abuse 86 were found to have higher number of insomnia (20%) diagnosis made by GP. Patients with suicide ideation had the higher number of psychiatric consultation history (37.7%) and established depression (15.6%). Anxiolytic use was the highest (35.5%) in anxiety disorder group and in appr. 25% in both MINI diagnoses of major depression episode and suicidal ideation. Significant number of patients with MINI MDE and anxiety diagnoses have used no medication (62.5% and 65.1%). Antidepressant use was found higher in suicide ideation (8.2%) and anxiety (7.2%) group but low in MDE patients (3.2%). Almost no-one took antidepressants in alcohol abuse group (0.3%). The results could be discussed in the light of the numerous literatures where the alcohol use was discussed. It is known that up to 40 per cent of people who drink heavily have symptoms that resemble a depressive illness. However, when these same people are not drinking heavily, only 5 per cent of men and 10 per cent of woman have symptoms meeting the diagnostic criteria for depression – not that different from the rates of depression in the general population. About 5 to 10 per cent of people with a depressive illness also have symptoms of an alcohol problem [(13i)]. In our study we did not specified if the patient was heavy drinker or not, when he was positive to MINI alcohol diagnosis and probably this issue should be taken into consideration on the future research. The comorbidity between depression and anxiety is so high that debate continues as to whether they are categorically separate disorders or part of a continuum. For example, studies suggest that 30%–40% of patients with panic disorder or obsessive compulsive disorders also have depression. Comorbidity between anxiety disorders is common (e.g., 30% of patients with OCD report simple or social phobias, and 15% report panic disorder). The results of the present study also showed the prevalence of comorbidity between mental disorders. The prevalence of depression comorbidity at least with one anxiety disorders was very high in the present study – for 43.3% of primary care patients and these data are consistent with the epidemiological research by Kessler, where it was found that 45% of those who warrant at least one diagnosis also meet the criteria for one or more additional disorders [132]. Overall, 24.2% of the population was positive for GAD and/or MD. Both disorders were significantly more frequent in women than in men. In 59.2% of patients we found the presence of current GAD&MDE. Data are in character with the recent NICE Guideline Paper for common mental health disorder, where it was stated that half of people aged 16 to 64 years who meet the diagnostic criteria for at least one common mental health disorder experience comorbid anxiety and depressive disorders [(11i)]. Data of our study apply the results by other investigators who conclude that anxiety and depression are the two most common mental 87 health problems seen in primary care [7; 145; 204p; 208]. Although increasing attention has been paid to anxiety, it still lags far behind depression in terms of research as well as clinical and public health efforts in screening, diagnosis, and treating affected individuals. This is unfortunate given the prevalence of anxiety and its substantial impact on patient functioning, work productivity, and health care costs. Authors conclude that clinicians and researchers should no longer look for depression or anxiety alone. Considering the frequency with which depression and anxiety cooccur, a search for one condition should always be accompanied by an assessment of the other. Our study also confirms the gender differences for studies for certain mental disorders. Comorbidity of depression and anxiety, which are usually more frequent among women with alcohol use disorder significantly more frequent among men [8; 168]. We found that 12.3% of women and 7.1% of men had at least one anxiety disorder. Clear gender differences were seen in panic disorder (2 = 5.6, p = 0.02) and generalized anxiety (2 = 15.1, p = 0.001) disorder - significantly more frequent amongst female than male patients. In contrast, alcohol disorders were significantly more frequent in males (2 = 78.6, p < 0.001). MDE had tendency to be more frequent in females (2 = 7.8, p = 0.06). (Age adjusted odd ratio of comorbid MDE&GAD according to gender was OR = 2.15 (1.25–3.68) with higher prevalence among women. These data are consistent with the literature discussing that although men and women are affected equally by such mental health conditions as obsessive-compulsive disorder and social phobias, women are twice as likely as men to have panic disorder, generalized anxiety, and specific phobias. Women are twice as likely as men (12 percent of women compared to 6 percent of men) to get depression and women are twice as likely to develop PTSD following a traumatic event. Men die from suicide at four times the rate that women do, but women attempt suicide two or three times more often than men. The answers may lie in biological influences, sociocultural influences, behaviour influences, etc. Many issues related to women's mental health should be studied in the future, including: differences in brain development that may provide insights into treating and preventing depression and bipolar disorder, mood and memory processes in women that may make it harder for them to quit smoking, effects of estrogens on memory, behaviour, cognition, and emotion, and particularly how estrogens seems to increase rates of PTSD and depression and genetics specific to women that may contribute to alcoholism (Hook, 2009(15i)]. 88 Depression can be a feature of virtually any psychiatric disorder. Particularly high rates of depression are found in alcohol-related disorders, eating disorders, schizophrenia and somatoform disorders [12i]. Considering the frequency with which depression and anxiety co-occur, a search for one condition should always be accompanied by an assessment of the other [145],as the presence of comorbid mental disorders is associated with possibility of suicide [93; 102; 177]. The problem of under-detection and under-treatment of psychiatric morbidity in PC has not been solved despite increasing evidence both of the negative outcome even in subsyndromal morbidity, and of the effectiveness of different types of interventions, particularly in cases of depression [171; 172] and this remains the very significant health care issue in primary care. 4.3. The prevalence of suicidal ideation in primary care The results of this study indicate that suicidal ideation is highly prevalent in primary care. The present study supports data that suicidal ideation is unrecognized and untreated in primary care. We found that 61 patients of the study had suicidal ideation, but no one had been recognized by family doctor. The high prevalence of suicide ideation in the present study confirms the data that suicide is not only personal tragedy, it represents a serious public health problem [81; 83; 112; 202; 269; 304; (8i);]. Being both anxious and depressed is a tremendous challenge. The most important risk factor is the presence of a current mental illness. Age and gender adjusted OR for coexisted MDE and GAD according suicidality was high (OR=4.56) in our study. Although there has been significant interest in whether anxiety disorders are risk factors for suicidal behaviour, this remains a controversial area as anxiety disorders are highly comorbid with other anxiety disorders and tend to cluster together, not only amplify the risk of suicide attempts in persons with mood disorders [133; 243; (8i)]. We found significant differences for a number of variables between suicidal and not-suicidal patients: the suicidal patients were more likely to have a history of a mood disorder (OR=3.3; 1.4–7.7), than non suicidal patients. Suicidal patients were more likely to have a current MDE, social anxiety, posttraumic stress disorder and GAD. Panic disorder was not significantly different between suicidal and not-suicidal patients. History of an alcohol use disorder also was not significantly different between groups, but was included in the analysis due to the comorbidity with mood disorder as both alcohol problems and depression are extremely common [(13i)]. They may occur together completely independently. The results support the literature 89 that significant number of completed suicides are associated with mental disorders, especially with mood disorders [176; 183; 242; 243] and conclude that the link between common psychiatric comorbidities and suicidal behaviour is robust and the very complex issue [29]. Alcohol consumption could play a role as it is known that up to 40 per cent of people who drink heavily have symptoms that resemble a depressive illness which strongly associates with suicide [(13i)]. We found in our multivariate analyses that suicidality was mainly associated with depression and anxiety, generally coexisted MDE&GAD, with type2 diabetes and with the lower alcohol influence. According the literature, the direction of the relationship between suicide and alcoholism is unclear: suicidal people may drink heavily as a way of coping or it might be that alcoholic individuals put themselves at risk through progressive reductions in the quality and quantity of their social relationships (which are thought to buffer against suicide) [238]. In our study we did not specified if the patient was heavy drinker or not, when he/she was positive to MINI alcohol diagnosis and probably this issue should be taken into consideration on the future research. Subjects with both generalized anxiety disorder and major depressive disorder were at greatest risk of suicidality. It confirms that comorbidity of mental disorders is the rule rather than exception [70]. Clinicians have observed that when anxiety occurs "comorbidly" with depression, the symptoms of both the depression and anxiety are more severe compared to when those disorders occur independently. Moreover, the symptoms of the depression take longer to resolve, making the illness more chronic and more resistant to treatment, when accompanied by anxiety [(11i)]. Finally, depression exacerbated by anxiety has a much higher suicide rate than depression alone. Most of depressed patients who had attempted suicide are also plagued by severe anxiety [(1i)]. As alcohol and barbiturates, depression and anxiety are a deadly combination when taken together, this comprises a probable majority of depressed individuals seen within routine primary clinical practice setting and carries a high risk of suicide. 4.4. Mental disorders and general medical conditions in primary care The results of this study indicate that mental disorders are highly prevalent, comorbid with general medical conditions and unrecognized by primary care physicians. In terms of definitions, primary care is often used interchangeably with primary medical care as its focus is on clinical services provided 90 predominantly by GPs, as well as by practice nurses, primary/community health care nurses, early childhood nurses and community pharmacists. Primary health care incorporates primary care, but has a broader focus through providing a comprehensive range of generalist services by multidisciplinary teams that include not only GPs and nurses but also allied health professionals and other health workers, such as multicultural health workers and Indigenous health workers, health education, promotion and community development workers, as well as providing services for individuals and families, PHC services also operated at the level of communities [18i]. The present study corresponds to findings from other studies on mentalphysical comorbidity in community with regard that there is still limited information that accounts for comorbidity with a wide range of mental and general medical conditions in primary care samples [193; 301]. Bogner et al. discussed that studies on the prevalence of mental disorders in association of general medical conditions in primary care are scarce [26] even cognizing that patients with mental and physical disorders visit their primary care physician as the first point of the contact [(11i)]. People with mental disorder have a higher prevalence of chronic physical conditions including chronic pain, cardiovascular disease, high blood pressure and respiratory conditions. Fernandez A. and colleagues found that mood disorders are responsible for a large percentage of quality-adjusted life-years lost in primary care [69]. Somatisation is the most important cause of missed diagnosis but about two thirds of depressed patients present with somatic symptoms, making it critical always to consider emotional health in a differential [67; 219]. Many patients seen have a pre-existing physical illness which can also divert attention away from their mental state. In example, anxiety disorders typically present with a number of somatic physical complaints (e.g., palpitations, sweating, shortness of breath, chest pain, and nausea) resembling cardiac disorders [166]. In the elderly, depression can present as pseudodementia, with abnormalities of memory and behaviour that are typical of true dementia. Several socioeconomic factors are significantly associated with positive diagnoses: living alone, a low level of education. The most common reason for a patient to seek a primary care doctor consultation was cardiovascular disease (31.5%), administrative case (17.6%) and acute respiratory tract disease/cold (10.4%) with a bit less number of muscle sceletal / connective tissue disease (6.9%) in the present study. This could indicate cardiovascular disorders, joint tissue diseases as well as administrative cases to be a possible “hint” for primary care physician on mental disorder to overlap but further studies are needed to clarify these characteristics. Kroenke and colleagues found that 91 chronic medical conditions not only tend to overlap mood and anxiety disorders, but mental disorders also frequently occur in patients with chronic medical disorders and increase the disability in such patients [145]. In contrast, acute cold disease was found to be associated with lower anxiety in men. There are no data to comment the acute cold or flu association on mental health issues in primary care, to the best of our knowledge, so it needs to be evaluated in the further studies. As non-steroid antiinflammatory drugs are commonly used for the treatment of cold-like diseases, so the probable influence should be evaluated on the further research. There is still limited information that accounts for comorbidity with a wide range of mental and general medical conditions in primary care samples, as most research has been completed in the community and only rarely in PC samples [193]. This presents treatment difficulty as primary care physicians are not trained to identify the clinical signs and symptoms of psychiatric illness. We found that the prevalence of mental disorders and general medical conditions are high and underdetected in primary care. Our findings suggest that mental disorders are highly comorbid with each other, and with general medical conditions in primary care. The comorbidity with anxiety disorders that are share with one another, as well as with depressive and somatic symptoms is noteworthy. A number of possible mediators that could explain an association between depressive symptoms and cardiovascular diseases were evaluated, including biomedical risk factors, medical treatments, and sociodemographic data in the present study. A significantly higher prevalence of CVD was observed in the tertile of patients with the highest mean anxiety score, as compared with the tertile with the lowest score meaning that severity of anxiety plays a role. After adjusting for age, sex, duration of school education, family status, history of diabetes mellitus, body mass index, clinical center event rate remained significantly elevated for the highest tertile. Notably, if symptoms of anxiety and depression were considered simultaneously for patients with severe anxiety, significant odd ratio was 2.27 (95% CI 1.34–3.85, p=0.002). In contrast, compared to patients with a HADS-D in lower tertile CVD rate remained elevated for the highest tertile but not significantly. The prevalence of other traditional CVD risk factors (except for age, HR, Pulse pressure, systolic BP) was similar among the patients with highest anxiety scores. We found no statistically significant association between history of hypertension in both HADS-A and HADS-D, but the history of CAD has been associated with higher HADS-D numbers. Anxiety score alone was significant in predicting the risk of CVD. So, the most important finding of the study provided evidence that severity of symptoms of anxiety could independently predict risk of CVD .Severity of mood and anxiety disorders 92 but not the presence is associated with higher systolic BP in primary care patients as severity of depression could have a significant impact on increased BMI. There is abundant evidence about the potential of specific medical diseases such as cerebro-vascular disease [226], or diabetes [53] to increase the risk of psychiatric morbidity, and specifically depression. Some studies have also found an association between depression and general medical conditions [274], but others reported the association only with severe, and not with the mild or moderate physical illness which is commonly seen in PC [22]. In the present study we found that symptoms of anxiety seem to be a much stronger predictor for subsequent adverse cardiovascular events than symptoms of depression in patients with CVD. Furthermore, the study suggested that the increased risk may be mediated in some minor part by several known risk factors of CHD such as increased blood pressure, and factors possibly associated with health behaviour and diet (e.g. body mass index). Anxiety can be treated effectively with cognitive behaviour therapy and medications (e.g., benzodiazepines and selective serotonin reuptake inhibitors). Unfortunately, many patients do not receive adequate treatment [51]. Besides the impact of anxiety on disability and decreased quality of life, clinicians should be aware of the risk of anxiety associated with incident heart disease [119]. Future research needs to investigate whether the treatment of anxiety has a significant beneficial effect on the incidence or course of cardiac disease [149]. Results reflect the plenty of data that mental disorders as major depressive disorder, which is the most common psychiatric disorder in patients with CAD, play the role [87]. It is in line with a numerous literature where the comorbidity was discussed from the point of psychiatric treatment issues, development of severe mental illnesses as suicide for those with physical diseases as type2 diabetes mellitus or myocardial ischaemia [113; 145; 160; 176; (1i); (8i); (11i)]. Thyroid immunity may be such a process affecting cardiovascular function. Effects of thyroid hormones on functioning of the cardiovascular system have been known for many years and are observed in both hyperthyroidism and hypothyroidism [140]. Good evidence exists for increased cardiovascular morbidity in overt hyperthyroidism as well as in overt hypothyroidism [59]. It is well recognized that overt thyroid dysfunction affects body weight [167], but the influence of minor perturbations of thyroid function on body weight remains unclear. In our study we also found that significantly more women with hypoechoic thyroid pattern were using antihypertensive medications when compared to women with normo-echoic thyroid pattern (pls. see 4.5). From the point of thyroid immunity and mental disorders, we found an association with mood symptoms in primary care patients, evaluated by HADS 93 especially in pre-menopausal women (pls. see 4.4.2). This finding, together with the higher prevalence of hypertension among patients with hypo-echoic thyroid pattern, suggests that an association between AITD and hypertension may be clinically significant especially in women. However, we found no statistically significant differences in the prevalence of specific mood and anxiety disorders assessed by structured diagnostic interview in relation to thyroid echogenicity. We found that in men and in women with hypo-echoic thyroid pattern there was a higher prevalence of obesity and higher prevalence of increased. BP when compared to men and women with normo-echoic thyroid pattern, respectively. In women this association was related to menopausal status. The most important findings of our study pertain to the association between thyroid immunity and mood or anxiety symptoms in primary care female patients, especially in pre-menopausal women. These data are consistent with the report of Pop et al. [216] who together with colleagues in their community studied 583 randomly selected pre-menopausal women and found that those with elevated thyroid antibody concentrations were especially vulnerable for depression, whereas postmenopausal status and thyroid hormone status did not increase risk of depression. In premenopausal but not in postmenopausal women, hypo-echoic thyroid pattern was associated with increased prevalence of obesity and increased BP. Moreover, premenopausal women with hypo-echoic thyroid pattern also had higher systolic and diastolic BP and higher BMI compared to premenopausal women with normo-echoic thyroid pattern. As regards to premenopausal women, our study demonstrates that thyroid immunity is associated with obesity and high BP. The association of thyroid autoimmunity with BMI, found in this study, is consistent with other reports, demonstrating that thyroid autoimmunity is related to increases in BMI [256] and may be of value in understanding the relationship between thyroid autoimmunity and other autoimmune endocrinopathies such as diabetes [287]. Our findings, together with findings of others suggest that thyroid immunity per se may be an important predictor of mood disorders. Involvement of thyroid immunity in brain functioning was reported by several neuro-imagining studies, demonstrating a higher prevalence of brain perfusion abnormalities in euthyroid patients with autoimmune thyroiditis [214; 305] and higher levels of anxiety and depression in these patients [305]. However, we did not find an association involving thyroid autoimmunity and diabetes in our study. We found that 3% of primary care patients had a diagnosis of diabetes. These findings correspond to findings from a recent 94 epidemiological study where the prevalence of diabetes among primary care patients was also found to be about 3% [194]. A significant number of primary care attenders were people with no complaints („administrative reason“ patients). They were found having mood and anxiety disorders, too, after evaluation by MINI. This could be taken as the very important message for primary care physicians to address into their practice as mental disorders could have the significant impact on the mental and general medical conditions to develop. It is now clear, that depression is also associated with biological changes involving increased heart rate, inflammatory response, plasma norepinephrine, platelet reactivity, absent post-ACS HRV recovery - all of which is associated with life-threatening consequences. It also impairs compliance with doctor advice and health behaviours. Although several studies suggest that anxiety might contribute to the development of CHD in initially healthy individuals [148] and found an effect on cardiac death [101; 127] or incident myocardial infarction [252], others have found no association [195]. Anxiety disorders typically present with a number of somatic physical complaints (e.g., palpitations, sweating, shortness of breath, chest pain, and nausea) resembling cardiac disorders [166]. Additional cardiovascular conditions that may contribute to a clinical presentation of anxiety include angina, congestive heart failure and syncope as well as anxiety disorders are associated with significantly lower heart rate variability [166; 297]. Extreme anxiety and psychological distress have been associated with increased risk for sudden cardiac death. However, other manifestations of anxiety have been associated with an increased risk of CVD morbidity and/or mortality [62; 213]. The study by Lobo et al. shows an association of predominantly mild medical conditions and psychiatric disturbances, in particular anxiety and depression, add to the existing evidence on the co-morbidity issue in PC [172]. One study confirms that patients with stable CAD and a diagnosis of depression or anxiety have a greater risk of cardiac events [77]. Patients with concomitant diagnoses of stable CAD and either major depressive disorder or generalized anxiety disorder had a greater-than-twofold increase in the risk of major adverse cardiac events in the two years following a baseline assessment, although comorbid MDD and GAD appeared not to be additive in their effects on cardiac risk. The work that has shown apparent links between anxiety and prognosis in cardiac patients has largely explained this association by other factors such as disease severity, FrasureSmith said. However, both GAD and MDD have many overlapping symptoms and some genetic links, and antidepressants can be used to treat both conditions, leaving open the question of a prognostic association 95 between anxiety and cardiac prognosis [77]. Several early studies have demonstrated that depression increases the risk of developing cardiac disease, in particular coronary artery disease, and to worsen prognosis after myocardial infarction [39; 75; 199; 248; 249; 263; 297]. Cardiovascular diseases, especially CAD, are often associated with depression [179; 278]. A number of possible mediators that could explain an association between depressive symptoms and cardiovascular diseases were evaluated, including biomedical risk factors, medical treatments, etc. Still the mechanisms of increased cardiac risk attributable to depressive illness are at present uncertain, but activation of the sympathetic nervous system with increased levels of monoamines, exaggerated platelet activity, and/or enhanced inflammatory-mediated atherogenesis are likely to be of primary importance. Still further research is needed on the evaluation of the prevalence and management of mental disorders in primary care patients in association with suicidal ideation and general medical conditions [55]. It was observed that anxiety symptoms might be more important than symptoms of depression is supported by a study of Strik and colleagues who showed in 318 men with MI that the risk for secondary cardiac events (n=25 fatal or non-fatal MI) was mainly explained by symptoms of anxiety (HR 2.79, 95% CI 1.11–7.03) and not by depression or hostility; additionally symptoms of anxiety were also a predictor of other measures of health care utilization [237]. Several previous studies reported that symptoms of anxiety are a risk factor for primary CHD [101; 127; 267], too and authors suggest that they may be an independent determinant for prognosis in patients with already existing CHD. A dose–response relationship was also found between phobic anxiety and fatal CHD in the US Health Professionals’ follow-up study [127]. In patients with MI, anxiety also appeared as a predictor of recurrent cardiac events independent of depression [76]. There are several potential mechanisms that might help to explain the adverse association between anxiety and CHD. Anxiety has been associated with progression of atherosclerosis [211], decreased heart rate variability [185], and risk of ventricular arrhythmias [277; 284]. Research supports the risk of arrhythmias particularly in the case of phobic anxiety, with studies showing an association between phobic anxiety and sudden cardiac death but not with nonfatal MI [2; 128]. More research is needed focusing on these possible mechanisms and the impact on different outcomes, particularly MI versus (sudden) cardiac death. Furthermore, anxiety is related to an unhealthy lifestyle in patients at risk of CHD [27]. The recent studies demonstrate that unhealthy lifestyles (e.g., physical inactivity and smoking) might also mediate the relationship between anxiety and CHD. This might 96 indicate that the association between anxiety and CHD might be larger than reported here [228]. We found that anxiety disorders were stronger associated with cardiovascular disease in both men and women, psychiatric treatment in females, particularly in the category of cardiovascular, but there was also a significant association with diabetes mellitus in males. 4.4.1. The association of depression, anxiety symptoms and suicidal ideation with general medical conditions in primary care patients The results of this study indicate that mental disorders and suicidal ideation are highly prevalent and comorbid with general medical conditions in primary care. The association of mental disorders with general mental conditions found in this study is consistent with other reports, demonstrating that depression, anxiety and suicidal ideation is related to general medical conditions and has the very significant impact on the individual’s health status. We found no statistically significant association between BMI and anxiety, evaluated by HADS. Main results on the mood and anxiety disorders and general medical conditions are discussed in 4.1chapter so the focus of the discussion of this chapter would be more on suicidal ideation and associations with mental and general medical conditions in this chapter. The present study found significant differences for a number of variables between suicidal and not-suicidal patients. The suicidal patients were more likely to have a history of a mood disorder (OR=3.3) lower education, than non suicidal patients. Suicidal patients were more likely to have a current MDE (OR=3.7), social anxiety (OR=3.0) posttraumic stress disorder (OR=3.4) and GAD (OR=3.3). History of an alcohol use disorder also was not significantly different between groups, but was included in the analysis due to the comorbidity with mood disorder. Alcohol consumption could play a role as it is known that up to 40 per cent of people who drink heavily have symptoms that resemble a depressive illness which strongly associates with suicide [(13i)]. We found in our multivariate analyses that suicidality was mainly associated with depression and anxiety, generally coexisted MDE&GAD, with type2 diabetes and with the lower alcohol influence. According the literature, the direction of the relationship between suicide and alcoholism is unclear: suicidal people may drink heavily as a way of coping or it might be that alcoholic individuals put themselves at risk through progressive reductions in the quality and quantity of their social relationships (which are thought to buffer against suicide) [17i]. In our study 97 we did not specified if the patient was heavy drinker or not, when he/she was positive to MINI alcohol diagnosis and probably this issue should be taken into consideration on the future research. Study suggests that suicidality is mainly associated with depression and anxiety, generally with coexisted MDE&GAD and with type 2 diabetes Subjects with both generalized anxiety disorder and major depressive disorder were at greatest risk of suicidality in the present study. These data are consistent with the WHO report on suicide [(1i)]. We found comorbidity of MDE & GAD disorders was stronger associated with psychiatric treatment (OR=3.36) and suicidality (OR= 4.56). Gender differences were seen after adjustment by gender. These data are consistent with the literature discussing that although men and women are affected equally by such mental health conditions as obsessive-compulsive disorder and social phobias, women are twice as likely as men to have panic disorder, generalized anxiety, and specific phobias. Women are twice as likely as men to get depression and women are twice as likely to develop PTSD following a traumatic event. Men die from suicide at four times the rate that women do, but women attempt suicide two or three times more often than men. The answers may lie in biological influences, sociocultural influences, behaviour influences, etc. An association of GAD and psychiatric treatment was stronger in men (OR=2.53) as well as with both MDE&GAD disorders and psychiatric treatment (OR=3.39). The anxiety disorders were stronger associated with psychiatric treatment in females (OR=2.94), particularly in the category of cardiovascular diseases (OR=2.32), but there was also a significant association with diabetes mellitus in males (OR=5.54). Having diabetes can lead to other complications (e.g., eye damage, kidney damage, sexual dysfunction) and significantly influence the quality of life. People with diabetes have to follow a strict diet and get insulin injections at some point of the disease. An inability to effectively cope with these factors can cause a person with diabetes to develop depression [219]. We found that patients with type 2 diabetes mellitus had no association with mental disorder with exception of suicidal ideation. Eating disorders are serious psychiatric disorders associated with high levels of suicidality, particularly if depression is also present [93; 102; 177] and multiple studies have documented the relationship between BMI and suicide [58; 199]. Identification of BMI that is shared among these weightrelated disorders could be one of an essential step to developing effective prevention interventions [13; 102; 142]. We found that the higher BMI had statistically significant association with the presence of suicidal ideation in primary care patients, especially in depressed men (30.15±3.6 vs. 24.97±3.9, 98 p=0.03). Symptoms of depression alone had no significant difference on the higher BMI in both men and women. Of note, patients who had no depression and had no suicidal ideation were slightly overweight. It could be the issue for the discussion if the overweight could have the preventive impact for suicide, as it was stated by Goldney and colleagues in his recent article [93]. As it was discussed previously, summarization in PC has stirred much interest and is one of the problems related to under-detection [146]. On the contrary, with the exception of depression [117], there is considerable less information on the issue of psychiatric disturbances co-morbid with general medical conditions. In a study by Phillips et al. [213], subjects with both generalized anxiety disorder and major depressive disorder were at greatest risk of subsequent cardiac death, suggesting that anxiety and depression might also interact synergistically to affect CHD. Anxiety and depression have a moderate-tostrong correlation, and it is possible that anxiety and depression are both part of a larger and more stable psychological factor influencing heart disease, like negative affectivity [56; 267]. A recent meta-analysis focusing on the association of anger and hostility with CHD found a 19% increased risk, but: 1) this association was no longer significant after adjusting for possible behavioural covariates; and 2) the association with CHD mortality was not significant [42]. This difference in anxiety and anger as potential predictors of cardiac death is of interest and calls for confirmation in future research. [228] Therefore, depressed patients might become trapped in a harmful loop, where mental symptoms might be worsened by the synergistic effects of stress and cardiovascular risk factors, and where they are otherwise vulnerable to acute cardiovascular events due to the synergistic effects of mental stress and an underlying atherothrombotic disorder. Although the exact pathway(s) underlying the interplay between depression and cardiovascular disease remains to be elucidated, the mechanisms most often implicated include hormonal variations, metabolic abnormalities, hypercoagulability, increased platelet aggregation, inflammation, and endothelial dysfunction. A number of disease states are reviewed that have been studied and shown to have improved outcomes and decreased mortality rates when both the psychiatric conditions and medical illness are treated [263, (1i)]. Controversly, many health conditions increase the risk for mental disorder, and comorbidity complicates help-seeking, diagnosis, and treatment, and influences prognosis. Health services are not provided equitably to people with mental disorders, and the quality of care for both 99 mental and physical health conditions for these people should be improved [291, 292].The high prevalence and clinical consequences of the cooccurrence of mental and physical disorders, attention to their comorbidity should remain a clinical and research priority [247], especially in primary care. 4.4.2. The association of thyroid immunity with blood pressure and body mass index in primary care patients The results of this study indicate that thyroid autoimmunity, evaluated by ultrasonographic imaging of the thyroid gland, is associated with increased BMI and with increased arterial BP, in primary care patients, especially in premenopausal women. The association of thyroid autoimmunity with BMI, found in this study, is consistent with other reports, demonstrating that thyroid autoimmunity is related to increases in BMI [256] and may be of value in understanding the relationship between thyroid autoimmunity and other autoimmune endocrinopathies such as diabetes [287]. However, we did not find an association involving thyroid autoimmunity and diabetes in our study. We found that 3% of primary care patients had a diagnosis of diabetes. These findings correspond to findings from a recent epidemiological study where the prevalence of diabetes among primary care patients was also found to be about 3% [194]. It is well recognized that overt thyroid dysfunction affects body weight [167], but the influence of minor perturbations of thyroid function on body weight remains unclear. One study found no association between thyroid stimulating hormone (TSH) concentrations and BMI in euthyroid obese and nonobese population [182]. However, another study reported that triiodothyronine (T3) concentrations and TSH concentrations were directly associated with waist circumference, independent of insulin resistance in overweight and obese women [54]. Portmann and colleagues concluded that treatment of a subclinical thyroid dysfunction has almost no influence on body weight in their review [217]. However, another study reported that treatment of hypothyroidism with a combination of thyroxine (T4) and T3 in comparison to monotherapy with T4 had some effect on body weight [9], suggesting that even small fluctuations in thyroid hormone concentrations may be important for body weight. Moreover, it has been suggested that thyroid hormone analogs may be useful in treating obesity as adjunctive therapy to appetite suppressants along with exercise and diet restriction [98]. It was reported by Stichel et al. that thyroid autoantibodies were found to be increased in obese children, but usually in conjunction with elevated serum 100 TSH concentration [262]. Our study confirms relationship between obesity and thyroid immunity; however, we have not evaluated relationship between obesity and subclinical thyroid dysfunction. Effects of thyroid hormones on functioning of the cardiovascular system have been known for many years and are observed in both hyperthyroidism and hypothyroidism [140]. Thyroid hormones increase cardiac inotropy and chronotropy and also directly affect vascular smooth muscle cells, promoting relaxation of resistance arterioles and decreasing peripheral vascular resistance. Normal thyroid hormone concentrations are required for normal cardiovascular functioning, whereas an excess or deficiency of thyroid hormones disorganizes it [140]. Good evidence exists for increased cardiovascular morbidity in overt hyperthyroidism as well as in overt hypothyroidism [59]. In contrast, data on cardiovascular morbidity and mortality in subclinical hyperthyroidism and in subclinical hypothyroidism are inconsistent [280]. As regards to BP, several recent studies [280; 283] reported that they found no association between subclinical hypothyroidism and increased BP. However, two other population-based studies found that increased concentrations of TSH within the normal range was associated with increased BP [11; 114], suggesting no subclinical thyroid dysfunction, but some other processes related to even milder changes in the functional state of the thyroid axis may be involved in this association. Thyroid immunity may be such a process affecting cardiovascular function. Indeed, it has been reported that cardiovascular morbidity [180] and specific cardiovascular dysfunction such as pulmonary hypertension [46] are related to thyroid immunity. In a small clinical sample it was demonstrated that in comparison to healthy controls, euthyroid patients with autoimmune thyroiditis have significant differences in systolic and diastolic cardiac function, measured by pulsed-wave tissue Doppler imaging [307]. It remains unclear how these cardiovascular differences are associated with thyroid immunity. In our study we also found that significantly more women with hypoechoic thyroid pattern were using antihypertensive medications when compared to women with normo-echoic thyroid pattern. This finding, together with the higher prevalence of hypertension among patients with hypo-echoic thyroid pattern, suggests that an association between AITD and hypertension may be clinically significant especially in women. We found that in men and in women with hypo-echoic thyroid pattern there was a higher prevalence of obesity and higher prevalence of increased BP when compared to men and women with normo-echoic thyroid pattern, respectively. In women this association was related to menopausal status. In premenopausal but not in postmenopausal women, hypo-echoic thyroid 101 pattern was associated with increased prevalence of obesity and increased BP. Moreover, premenopausal women with hypo-echoic thyroid pattern also had higher systolic and diastolic BP and higher BMI compared to premenopausal women with normo-echoic thyroid pattern. Our data also demonstrated that in women with normo-echoic thyroid pattern, but not in women with hypo-echoic thyroid pattern, a postmenopausal status was similarly associated with increased BP and increased BMI, suggesting that thyroid immunity may have similar effects on cardiovascular risk factors such as obesity or increased BP in premenopausal women as the menopause transition has for postmenopausal women. It is well known that the menopause transition, because of estrogen withdrawal, increases the risk of cardiovascular disease [264]. Menopause compounds many traditional risk factors for cardiovascular disease, among which are changes in body fat distribution and increased BP [234]. Our study confirms these findings on the association of menopausal status with obesity and increased BP. It also suggests an association between the menopause transition and autoimmune thyroiditis. There are scant data on this association. One short follow-up study found no association between menopausal status and concentration of thyroid antibodies [187]; however, the authors concluded that long-term follow-up is warranted to ascertain whether the presence of antibodies is associated with subsequent risk of coronary heart disease. As regards to premenopausal women, our study demonstrates that thyroid immunity is associated with obesity and high BP. The main disadvantage of our study is that we did not measure the presence of serum thyroid autoantibodies that serves as an indicator of AITD in clinical practice. However, ultrasonographic evaluation of the thyroid gland with hypo-echoic ultrasound pattern indicating lymphocytic infiltration of the gland was used as an indicator of AITD [50; 103; 184; 212; 222; 256]. In conclusion, thyroid autoimmunity evaluated by ultrasonographic imaging of thyroid gland is associated with high BP and high BMI are associated with hypoechoic thyroid pattern in both male and female primary care patients. In women this association was significant in premenopausal but not in postmenopausal patients. There is a good evidence that overt thyroid dysfunction is related to changes in body weight as well as to changes in cardiovascular functioning. Data on the association of subclinical thyroid dysfunction with obesity and cardiovascular functioning are less clear and need further studies. Our study, performed in primary care setting, suggests that thyroid immunity itself is associated with obesity and high BP. 102 4.4.3. Mood and thyroid immunity assessed by ultrasonographic imaging in primary care The results of this study indicate that thyroid autoimmunity, evaluated by a relatively simple, cost effective but reliable technique, ultrosonographic imaging of the thyroid gland, is associated with mood symptoms in primary care patients, especially in pre-menopausal women. This observation corresponds to findings from other studies on the relationship between thyroid autoimmunity and mood disorders where thyroid immunity was measured by the assessment of thyroid antibodies in peripheral circulation [40; 100; 151). Indeed, recent findings (212; 223; 256) suggest that thyroid hypo-echogenicity found by ultrasonographic evaluation of the thyroid gland is a strong predictor of AITD and there is a close correlation between this marker of the AITD and the presence of thyroid antibodies (222). The most important findings of our study pertain to the association between thyroid immunity and mood or anxiety symptoms in primary care female patients, especially in pre-menopausal women. These data are consistent with the report of Pop et al. [216] who together with colleagues in their community studied 583 randomly selected pre-menopausal women and found that those with elevated thyroid antibody concentrations were especially vulnerable for depression, whereas postmenopausal status and thyroid hormone status did not increase risk of depression. In a similar way it was demonstrated in the post-partum period that women who had a higher serum thyroid antibody concentration postpartum [107] or during gestation [150] had a higher prevalence of post-partum depression. In combination with our results, these findings, taken together, suggest a role of the female sex hormones in the association of thyroid autoimmune process and mood or anxiety disorders. While this remains an area of further inquiry, evidence that thyroid hormone concentrations [85; 86] as well as thyroid gland size [108] vary with phase of the menstrual cycle in pre-menopausal women provide partial support for this supposition. In our study, it is curious to note that the self-rating instrument to measure symptoms of depression and anxiety, the HADS, revealed associations between mood symptoms and thyroid immunity in pre-menopausal women. However, we found no statistically significant differences in the prevalence of specific mood and anxiety disorders assessed by structured diagnostic interview in relation to thyroid echogenicity. The possible explanation for this inconsistency may be related to the treatment of mental symptoms. Indeed, pre-menopausal women with hypo-echoic thyroid pattern were treated more frequently with psychotropic medication, including benzodiazepines, in comparison to 103 women with normoechoic thyroid. This may have decreased the incidence of patients that fulfil criteria for specific mental disorders in the hypo-echoic thyroid group. AITD is frequently related to thyroid dysfunction and it is suggested that even marginal thyroid dysfunction may be associated with mood and anxiety disorders [218]. However, a large epidemiological study found no statistical association between clinical or subclinical thyroid dysfunction, and the presence of depression or anxiety disorders in a large unselected population [65]. Moreover, several studies that reported an association between depression and increased levels of thyroid antibodies found that depression was not related to thyroid dysfunction [107; 150; 216]. A recent study of Grabe et al. found that a general population of women with AITD, diagnosed by hypoechoic thyroid pattern and by the presence of thyroid antibodies in serum, showed higher scores of anxiety independently from their thyroid function [95]. It may be that it is not marginal thyroid dysfunction, but rather thyroid autoimmune processes, frequently responsible for this dysfunction [36; 37], that are responsible for co-morbidity with mood disorders. In our study we did not assess thyroid axis hormone concentrations and did not address this important question directly. However, our findings, together with findings of others suggest that thyroid immunity per se may be an important predictor of mood disorders. Involvement of thyroid immunity in brain functioning was reported by several neuro-imagining studies, demonstrating a higher prevalence of brain perfusion abnormalities in euthyroid patients with autoimmune thyroiditis [214; 305] and higher levels of anxiety and depression in these patients [305]. These brain perfusion abnormalities are similar to those observed in Hashimoto's encephalopathy [44] and may suggest a higher than expected involvement of the brain in AITD. Findings from this study obtained from an unselected primary care population, along with other studies, provide evidence that an autoimmune thyroid process per se may be related to mood and anxiety disorders. A full understanding of the relationship between thyroid autoimmunity and mental functioning awaits a full description. Further studies on the involvement of thyroid immunity in mental disorders as well as on the involvement of mental disorders in euthyroid patients with autoimmune thyroid disease are needed. This possibility can be investigated by the use of different techniques for the evaluation of thyroid autoimmunity: by the measurement of serum thyroid antibodies; by the cytological assessment of thyroid tissue, or by the ultrasonographic evaluation of the thyroid gland. 104 CONCLUSIONS 1. HADS is a valid and sensitive screening tool evaluating depressive disorders and anxiety disorders in primary care population. However, cutoff scores for depressive disorder (≥6) should be lower than suggested in original version (≥8). 2. Depressive disorders and anxiety disorders as well suicidal ideation and excessive alcohol use are prevalent; however poorly recognized and treated in primary care population. 3. Suicidal ideation in primary care patients is associated with gender, history of current psychiatric treatment, with the presence of current major depression episode, generalized anxiety disorder and comorbidity of type 2 diabetes mellitus. Coexistance of current major depressive episode and generalized anxiety disorder as well as severity of symptoms of anxiety increases suicidal ideation in primary care patients. 4. Type 2 diabetes in men and cardiovascular disorders in women are associated with the presence of current generalized anxiety disorder. Severity of symptoms of anxiety and symptoms of depression, but not the presence of current psychiatric disorders is associated with higher systolic blood pressure in primary care patients. Moreover, severity of symptoms of depression is associated with higher body mass index. 5. Thyroid autoimmunity, assessed by ultrasonographic imaging of thyroid gland is associated with more severe anxiety symptoms in female but not male in primary care patients. It is also associated with higher blood pressure and higher body mass index in male and female primary care patients. 105 PRACTICAL RECOMMENDATIONS 1. As depression, anxiety disorders, suicidal ideation and alcohol abuse are prevalent, unrecognized and poorly treated in primary care, the improvement on the individual mental status recognition could play the crucial role on the management of this significant health care issue. MINI International Neuropsychiatric Interview is proper standard screening tool to evaluate mood, anxiety disorders and suicidal ideation in primary care settings. HADS could be used as a screening tool for mental disorders in primary care. 2. PC physicians should be recommended to screen a patient for comorbid mental illness even one mental disorder already confirmed: comorbidity of mental disorders is very prevalent and has the significant impact on the individuals’ physical status and treatment. 3. The high prevalence and clinical consequences of the co-occurrence of mental and physical disorders, attention to their comorbidity should remain a clinical priority for primary care giver: the routine general medical examination should be complimentary with routine mental screening in primary care patients. 4. Healthy primary care attenders (“administrative reason” patients) should be evaluated for mental disorders. 5. 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Hook DLB. www.forums.ivillage.com .Common Mental Health Issues in Women 16i. www.lgs.lt. „Gydytojų Žinios“. „Ministras prof. Ž. Padaiga: kovosime už tikrą, o ne menamą prioritetą sveikatos apsaugai“. 2006 Nr.1(395), 1-2. 17i. http://www.samhsa.gov/matrix2/508suicidepreventionpaperfinal.pdf 18i. http://www.phcconnect.edu.au/defining_primary_health_care.htm 134 APPENDIXES PERMITS FROM BIOETHICS COMMITTEE (Appendix 1, 2a, 2b) Appendix 1 135 Appendix 2a LIETUVOS BIOETIKOS KOMITETAS Valstybės biudžetinė įstaiga, Didžioji g. 22, LT-01128 Vilnius, tel. (8 5) 212 4565, faks. (8 5) 260 86 40 el. p. [email protected], http://bioetika.sam.lt Duomenys kaupiami ir saugomi Juridinių asmenų registre, kodas 188710595 LEIDIMAS ATLIKTI BIOMEDICININĮ TYRIMĄ 2008-11-06 Nr.: 61 Biomedicininio tyrimo pavadinimas: „Mokslinis tyrimas, kuriuo siekiama nustatyti ryšį tarp psichikos sutrikimų, suicidinio elgesio ir autoimuninio skydliaukės susirgimo pirminės sveikatos priežiūros pacientų tarpe“ Protokolo Nr: 2008PSBPG Versijos Nr.: 3 Data: 2008 m. lapkričio 05 d. Asmens informavimo apie dalyvavimą klinikiniame tyrime forma ir informuoto asmens sutikimo forma lietuvių kalba: Versijos Nr.: 3 Data: 2008 m. lapkričio 05 d. HAD skalė lietuvių kalba: Versijos Nr.: 1 Data: 2008m. spalio 15 d. Pagrindinis tyrėjas: Prof. habil. dr. Robertas Bunevičius Biomedicininio tyrimo vieta: Įstaigos pavadinimas: VšĮ Vilniaus Universiteto ligoninės „Santariškių Klinikos“,Šeimos Medicinos Klinika Įstaigos adresas: Santariškių g. 2, Vilnius 136 Leidimas išduotas Lietuvos bioetikos komiteto posėdžio, įvykusio 2008 m. spalio 21 d., sprendimu. Lietuvos bioetikos komiteto biomedicininių tyrimų ekspertų grupės nariai Nr. Vardas, Pavardė Veiklos sritis Dalyvavo posėdyje 1 Gyd. Gintarė Breivienė pediatrija ne 2 Gyd. Vytautas Čepulis onkologija taip 3 Doc. Eugenijus Gefenas bioetika taip 4 Prof. Zita Liubarskienė filosofija taip 5 Prof. Andrius Narbekovas teologija taip 6 Prof. Algimantas Raugalė pediatrija taip 7 Doc. Krescentius Stoškus filosofija taip 8 Gyd. Vytautas Tutkus mikrochirurgija taip 9 Dalia Zeleckienė teisė ne Lietuvos bioetikos komitetas dirba vadovaudamasis Geros Klinikinės Praktikos taisyklėmis, kurias siūloma priimti Europos Sąjungos, Japonijos ir JAV valdžios struktūroms Vyriausioji specialistė, l.e. pirmininko pareigas Ingrida Narušytė-Daugėlienė 137 Appendix 2b LITHUANIAN BIOETHICS COMMITTEE Registre of Legal Entities, code 1887 10595, Didžioji 22, LT-01128 Vilnius, Lithuania, tel + (370~5) 212 45 65, fax + (370~5) 260 86 40 [email protected], www.sam.lt/bioetika APPROVAL TO CONDUCT BIOMEDICAL RESEARCH 2008-11-06 No.: 61 Title: “Mental disorders, suicidal behaviour and autoimmune thyroid disease in primary care” Protocol No.: 2008PSBPG Version No.:3 Dated: 05 November, 2008 The patient‘s briefing form about participation in clinical study and the form of informed patient‘s concent in Lithuanian: Version No.: 3 Dated: 05 November, 2008 HAD scale (lithuanian): Version No.: 1 Dated: 15 October, 2008 Principal Investigators: Robertas Bunevičius, M.D., Ph.D. Biomedical research site: Name of institution: Vilnius University Hospital „Santariškių Klinikos“, Department of Family Medicine Address of institution: Santariškių str. 2, Vilnius 138 Approval is issued according to the decision of the Lithuanian Bioethics Committee meeting of 21 October, 2008 Members of the Lithuanian Bioethics Committee’s biomedical research experts group No. Name Occupation 1 2 3 Gintarė Breivienė, M.D. Vytautas Čepulis, M.D. Eugenijus Gefenas, Assoc.Prof. Zita Liubarskienė, Prof. Andrius Narbekovas, Prof. Algimantas Raugalė, Prof. Krescentius Stoškus, Assoc.Prof. Vytautas Tutkus, M.D. Dalia Zeleckienė pediatrician oncologist bioethicist Presence in the meeting no yes yes philosopher priest pediatrician philosopher no yes yes yes micro surgeon lawyer yes no 4 5 6 7 8 9 LBEC works in compliance with the International Harmonized Good Clinical Practice Guideline, recommended for adoption to the regulatory bodies of the European Union, Japan and USA Acting Chairman Ingrida Narušytė-Daugėlienė 139 Appendix 3 140 Appendix 4 141 142 143 PUBLICATIONS ON THE DISSERTATION THEME Articles: 1. Bunevicius R, Peceliuniene J, Mickuviene N, Bunevicius A, Pop VJ, Girdler SS. Mood and thyroid immunity assessed by ultrasonographic imaging in a primary health care. J Affect Disord 2007;97:85–90. 2. Bunevicius A, Peceliuniene J, Mickuviene N, Girdler SS, Bunevicius R. The association of thyroid immunity with blood pressure and body mass index in primary care patients. Endocrine Research, 2008;33(3– 4):93–103, 3. Bunevicius A, Peceliuniene J, Mickuviene N, Valius L, Bunevicius R. Screening for depression and anxiety disorders in primary care patients. Depression and anxiety. 2007; 24:455–460 4. Peceliuniene J, Raskauskiene N, Duoneliene I, Bunevicius R. Depression, anxiety disorders and suicidal ideation in primary care patients. Manuscript Thesis: 1. Pečeliūnienė J. The body mass index (BMI), suicide ideation and mood disorders in primary care // 10th World Congress of Biological Psychiatry Congress: Prague, 29 May-02 June 2011. Abstr. Oral communication session 2. Pečeliūnienė J, Bunevičius A, Mickuvienė N, Bunevičius R,. Kūno masės indeksas, suicidiniai ketinimai ir nuotaikos sutrikimai tarp pirminės sveikatos priežiūros pacientų // Biologinė psichiatrija ir psichofarmakologija=Biological Psychiatry and Psychopharmacology : LSMU MA Psichofiziologijos ir reabilitacijos instituto X-oji metinė tarptautinė konferencija "Kardiologijos aktualijos: nuo pažeistos ląstelės iki reabilitacijos" : 2011 m. balandžio 29-30 d, Palanga / Lietuvos sveikatos mokslų universiteto Medicinos akademija (LSMU MA). Kaunas : Sveikatingumo ir medicinos reklamos centras. (Tezės.). ISSN 1648-293X. 2011, t. 13, Nr. 1, balandis, p. 51. Internet access: http://www.pri.kmu.lt/Biologine%20psichiatrija(zurnalas)/2011_T13_Nr1/B PP_2011_1_tezes.pdf. 144 3. Pečeliūnienė J, Bunevičius R, Karvela A. Alcohol Use, Mental Disorders and Suicidal Ideation in Primary Care Patients // Αρχεία Ε.Ψ.Ψ.Ε.Π.=Archives A.P.P.A.C. : 3rd World Congress of the A.P.P.A.C. (Association of Psychology & Psychiatry for adults & children) " Neuropsychiatric, Psychological and Social Developments in a Globalised World". 14th International conference of the A.P.P.A.C. 1st International Multicentric Symposium in Penteli : Book of Abstracts : May 5-8, 2009, Athens, Greece / Εταιρεία Ψυχολογικής Ψυχιατρικής Ενηλίκου & Παιδιού=Association of Psychology and Psychiatry for Adults & Children. Αθήνα/Athens : Γραφεία ΕΨΨΕΠ/Office A.P.P.A.C. (Poster Presentations. Group B.). ISSN 1106-2827. 2009, τόμ./vol. 16, τχ./no. 2, p. 43, no. 4. Internet access: http://www.epsep.org.gr/. 4. Bunevičius A, Pečeliūnienė J, Mickuvienė N, Bunevičius R. Depression and body mass index in primary care patients: Impact of gender // 9th World Congress of Biological Psychiatry : 28 June - 2 July 2009, Paris, France : abstracts / World Federation of Societies of Biological Psychiatry (WFSBP) Paris : WFSBP, 2009. (Poster Presentation. Session title: Affective Disorders (Unipolar) II.). p. 222, no. P-14-001. Internet access: https://www1.wfsbp-congress.org/guest/AbstractView?ABSID= 7907. 5. Pečeliūnienė J, Mickuvienė N, Bunevičius R. Mental disorders and suicidal ideation in primary care patients,// 9th World Congress of Biological Psychiatry : 28 June - 2 July 2009, Paris, France : abstracts / World Federation of Societies of Biological Psychiatry (WFSBP) Paris : WFSBP, 2009. (YS - Young Scientists Award Session . Session title: Other.). p. 110, no. YS-04-002. Internet access: https://www1.wfsbpcongress.org/guest/AbstractView?ABSID=8262. 6. Pečeliūnienė J, Bunevičius A, Mickuvienė N, Bunevičius R. Psichikos sutrikimai, suicidiniai ketinimai ir kūno masės indeksas tarp pirminės sveikatos priežiūros pacientų // Biologinė psichiatrija ir psichofarmakologija=Biological Psychiatry and Psychopharmacology : KMU Psichofiziologijos ir reabilitacijos instituto IX-oji metinė konferencija. Kaunas : Sveikatingumo ir medicinos reklamos centras. (Tezės.). ISSN 1648-293X. 2009, t. 11, Nr. 2, gruodis, p. 102. Internet access ą: http://www.pri.kmu.lt/Biologine%20psichiatrija(zurnalas)/2009 _T12%20N2/N2_%20CS4%20su%20turiniu_galutinis.pdf. 7. Bunevičius A, Pečeliūnienė J, Girdler S, Bunevičius R. The association of thyroid immunity with blood pressure and body mass index in primary care patients // Biologinė psichiatrija ir psichofarmakologija = Biological psychiatry and psychopharmacology : Kauno medicinos universiteto Psichologijos ir reabilitacijos instituto VIII-osios metinės 145 konferencijos tezės. Kaunas : Sveikatingumo ir medicinos reklamos centras. ISSN 1648-293X. 2008, t. 10, Nr. 2, p. 36. 8. Bunevičius R, Pečeliūnienė J, Mickuvienė N. Anxiety symptoms and hypo-echoic thyroid pattern in primary care patients // Biologinė psichiatrija ir psichofarmakologija=Biological psychiatry and psychopharmacology : 4th ISPNE Regional Congress for Eastern and Central Europe "Stress and psychoendocrine changes across the life cycles" : program and abstracts : June 15-17, 2006 Vilnius, Lithuania / International Society of Psychoneuroendocrinology (ISPNE), Host society: Lithuanian Society of Biological Psychiatry (LSBP), In collaboration with: The World Federation of Societies of Biological Psychiatry (WFSBP). Kaunas : Lietuvos biologinės psichiatrijos draugija. (Poster sessions. Endocrine responses to stress (P1)). ISSN 1648-293X. 2006, t. 8, Nr. 1, birželis, p. 26-27, poster no. P1-06. Internet access: http://www.biological-psychiatry.lt/ispne/ programme.php. 9. Bunevičius A, Pečeliūnienė J, Mickuvienė N, Bunevičius R. Validation of the hospital anxiety and depression scale against the mini international neuropsychiatric interview in population of primary care patients // 64th Annual Scientific Meeting : March 1 - 4, 2006, Hyatt Denver Convention Center Denver, CO : Dedicated to the Integration of Biological, Psychological and Social Factors in Medicine / American Psychosomatic Society. Denver, 2006. p. A-87, abstract 1640. Internet access: http://www.psychosomatic.org/events/2006Abstracts.pdf. Other 1. 2. 3. J. Pečeliūnienė took the 2nd place in the competition “Metų doktorantas 2007” (“the PhD student of the Year 2007”) ; Young scientist, travel grant award for the 9th World Congress of Biological Psychiatry 2009, Paris; The State Studies Foundation Grant in 2008, 2009, 2010. 146