Download 1.4. Mental disorders and general medical conditions in

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. Data obtained in the present study could serve for the development of
new mental health strategies, including primary and secondary prevention in
primary care.
6. Periodic trainings are needed to improve the recognition and
management of mental disorders, suicide ideation and other mental
disorders in primary care. Data from the present study could be used in the
trainings of medical students, family physicians and any primary care
givers.
7. There is a clear need for further randomized controlled trials in
patients with comorbid mood, anxiety disorders, alcohol use and suicidality
as this group comprises a probable majority of depressed individuals seen
within routine primary clinical practice setting and carries a high risk of
suicide. The present study could have plausible interest for the future
researchers.
106
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13i. Ciaran Mulholland, www.netdoctor.co.uk (alcohol and depression)
14i. Shepphird SF. Body mass index and suicide. March 13, 2009. Blog:
http:// www.drshepp.com
15i. 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