HEALTH BEHAVIOR AND HEALTH-RELATED QUALITY OF LIFE IN PATIENTS 
WITH A HIGH RISK OF CARDIOVASCULAR DISEASE
Davorina PETEK1*, Marija PETEK-STER1, Ksenija TUSEK-BUNC2
1University of Ljubljana, Faculty of Medicine, Department of Family Medicine, 
Poljanski nasip 58, 1000 Ljubljana, Slovenia
2University of Maribor, Faculty of Medicine, Department of Family Medicine, Taborska 8, 2000 Maribor, Slovenia
Received: Jun 20, 2017
Accepted: Dec 1, 2017
Original scientific article
Background: Health-related quality of life (HRQoL) is measuring a patient’s experience of his health status and 
represents an outcome of medical interventions. Existing data proves that a healthy lifestyle is positively associated 
with HRQoL in all age groups. Patients with a high risk for cardiovascular disease typically led an unhealthy lifestyle 
combined with risk diseases. We aimed to analyse these characteristics and their reflection in HRQoL.
Methods: A cross-sectional study in 36 family practices, stratified by location and size. Each practice invited 30 
high-risk patients from the register. Data were obtained from medical records and patient questionnaire. The 
EQ-5D questionnaire and the VAS scale were used for measuring the patient’s HRQoL as an independent variable. 
Results: 871 patients (80.6% response rate) were included in the analysis. 60.0% had 3-4 uncontrolled risk factors 
for CVD. The average VAS scale was 63.2 (SD 19.4). The correlation of EQ-5D was found in the number of visits in 
the practice (r=-0.31, p<0.001), the socioeconomic status (r=-0.25, p=0.001), age (r=-0.27, p=0.001) and healthy 
diet (r=0.20, p=0.006). In a multivariate model, only physical activity among lifestyle characteristics was an 
independent predictor of HRQoL (p=0.001, t=3.3), along with the frequency of visits (p<0.001, t=-5.3) and age 
(p=0.025, t=-2.2). 
Conclusion: This study has been performed on a specific group of patients, not being “really sick”, but having less 
optimal lifestyle in many cases. Encouragement to improve or keep healthy lifestyle, especially physical activity, 
is important, not only to lower the risk for CVD, but also to improve HRQoL.
Izhodišča: Z zdravjem povezana kakovost življenja (HRQoL) meri bolnikovo lastno izkušnjo njegovega zdravstvenega 
stanja in je eden od izidov zdravstvenih intervencij. Številne raziskave potrjujejo, da je zdrav življenjski slog v 
vseh starostnih skupinah povezan z boljšo kakovostjo življenja. Značilno je, da imajo bolniki z visoko ogroženostjo 
za nastanek bolezni srca in ožilja nezdrav življenjski slog, ob prisotnih sočasnih tako imenovanih boleznih 
tveganja, kot je npr. arterijska hipertenzija. V predstavljeni raziskavi so analizirane značilnosti življenjskega 
sloga, z namenom ugotoviti, ali se te odražajo v bolnikovi kakovosti življenja.
Metode: Presečna raziskava je bila izvedena v 36 ambulantah družinske medicine, stratificiranih glede na 
lokacijo (mesto, podeželje) in velikost (do dva oz. več polno zaposlenih zdravnikov na lokaciji). Vsaka ambulanta 
je k sodelovanju povabila 30 bolnikov iz registra visoko ogroženih za nastanek bolezni srca in ožilja (BSO) po 
Framinghamski tabeli ogroženosti. Ustrezni podatki so bili pridobljeni iz zdravstvenih kartotek in s pomočjo 
vprašalnikov za bolnike. Z zdravjem povezana kakovost življenja je bila merjena s petdimenzionalnim EQ-5D 
vprašalnikom in z VAS lestvico kakovosti življenja, ki sta predstavljala neodvisni spremenljivki.
Rezultati: V analizo je bilo vključenih 871 bolnikov (80,6 % vseh vabljenih). Od teh je 60,0 % imelo 3–4 prisotne 
dejavnike tveganja za nastanek BSO. Povprečna vrednost VAS lestvice je bila 63,2 (SE 0,72). Ugotovljena je bila 
korelacija med EQ-5D in pogostostjo obiskov bolnika v enem letu v ambulanti (r=-0,31, p<0,001), socialnoekonomskim 
statusom bolnika (r=-0,25, p=0,001), starostjo bolnika (r=-0,27, p=0,001) in zdravim načinom prehranjevanja 
(r=0,20, p=0,006). Med vsemi spremenljivkami so bili v multivariatnem modelu neodvisni napovedni dejavniki 
HRQoL telesna aktivnost (p=0,001, t=3,3), pogostost obiskov bolnika v ambulanti (p<0,001, t=-5,3) in starost 
bolnika (p=0,025, t=-2,2).
Zaključek: Raziskava o kakovosti življenja je bila opravljena v specifični skupini oseb z visokim tveganjem za 
nastanek BSO, ki niso »pravi« bolniki, pogosto pa imajo neustrezen življenjski slog. Spodbujanje k zdravemu 
življenjskemu slogu, posebej k telesni aktivnosti, je pomembno ne le za zniževanje tveganja za nastanek BSO, 
ampak tudi za izboljšanje z zdravjem povezane kakovosti življenja.
ABSTRACT
Keywords: 
high risk, 
cardiovascular 
diseases, HRQoL, 
risk factors
IZVLEČEK
Ključne besede: 
visoko tveganje, 
bolezni srca 
in ožilja, 
z zdravjem 
povezana kakovost  
življenja, 
dejavniki tveganja
*Corresponding author: Tel: + 386 1 436 82 17; E-mail: davorina.petek@gmail.com
10.2478/sjph-2018-0006 Zdr Varst. 2018;57(1):39-46
39
ZDRAVSTVENE NAVADE IN Z ZDRAVJEM POVEZANA KAKOVOST ŽIVLJENJA 
PRI BOLNIKIH Z VISOKIM TVEGANJEM ZA NASTANEK BOLEZNI SRCA 
IN OŽILJA
Petek D, Petek-Ster M, Tusek-Bunc K. Health behavior and health-related quality of life in patients with a high risk of cardiovascular disease. Zdr Varst. 2018;57(1):39-46.
doi: 10.2478/sjph-2018-0006.
© Nacionalni inštitut za javno zdravje, Slovenija. 
1 INTRODUCTION
Health-related quality of life (HRQoL) is the 
multidimensional concept of measuring patients’ unique 
experience of their health and the outcomes of health 
interventions. It covers a variety of domains, including 
physical and mental health, symptoms, functional status 
and the overall perception of health (1-3). It represents a 
clinical indicator of the patient’s wellbeing, as reflected 
by patients’ perceived health, effects of the disease 
and treatment consequences (4). It is also influenced by 
organisational care-delivery models, such as structured 
chronic care (4). 
We can find studies proving that lifestyle positively 
influences QoL in healthy patients of all age groups. 
Physically more active older patients have higher QoL in 
the physical and mental domain, compared to patients 
who are less physically active (5,6). The same is shown in 
younger age groups (7) and also in chronic patients (6). 
Physical activity improves HRQoL in cancer patients (8, 9) 
and patients with diabetes mellitus. Even patients with a 
high risk of diabetes have a better HRQoL if their lifestyle 
is improved (10).
High-risk patients for cardiovascular disease (CVD) 
typically have risk factors, which include so called 
“risk diseases”, such as arterial hypertension and 
hyperlipidaemia, in combination with a poor lifestyle. 
Medical intervention is directed toward the treatment 
of risk diseases and the improvement of lifestyle. HRQoL 
in patients with isolated risk diseases, such as obesity, 
also profit from interventions directed toward the 
improvement of lifestyle (11). Even arterial hypertension, 
a silent disease, showed an influence on the quality of life 
in some studies (12).
In our survey, patients with a high risk for CVD were 
defined by the criteria of the Framingham score system, 
which provides scores from 0->40, the high-risk group 
having ≥20 % of absolute risk for a cardiovascular event 
in the next 10 years due to modifiable risk factors (the 
level of systolic blood pressure, cholesterol, fasting blood 
glucose level, smoking) and non-modifiable risk factors – 
gender and age of the patient (13). In these patients, risk-
lowering strategies include lifestyle advice and treatment 
of risk diseases. 
In our study of patients with a high risk of CVD, we 
aimed to research the relationship between demographic 
characteristics, health behaviour, lifestyle features and 
high-risk CVD patients’ quality of life, as his/her own 
perception.
2 METHODS
We present national results, which are part of the 
observational cross-sectional study: EPA-Cardio (European 
practice assessment for cardiovascular patients). The 
detailed protocol is described elsewhere (14). The ethical 
approval was obtained from the National Committee 
for Medical Ethics (No. 87/11/07). All the necessary 
permissions for the questionnaires used in the study were 
obtained within the international part of the study.
2.1 Participants
36 out of 56 (response rate 64%) randomly selected 
practices in the country, stratified by the size of the 
practice (small practices with 1-2 full-time (FTE) working 
GPs at the same location and large ones with more than 
two FTE physicians) and location of the practice (urban 
- 30 000 inhabitants or more, rural - less than 30 000 
inhabitants); each practice invited 30 high-risk patients 
to participate in the study. High-risk was defined by 
the Framingham risk score and patients were selected 
randomly from the register of high-risk patients for 
CVD, mandatorily kept by each practice. The patients 
with already established CVD and patients with diabetes 
mellitus type 2 were not eligible for participation. The 
patients were contacted by the practice nurse by phone, 
in person or in writing, and received the questionnaire 
after giving the informed consent for cooperation. 
2.2 The Questionnaire
2.2.1 Independent Variables
The data for this analysis were gathered by a questionnaire 
filled out by the patients and by an AUDIT for data 
extraction from the patients’ medical records. The 
questionnaire consisted of several parts. In this analysis, 
we used the following: demographic characteristics of the 
patients, health services using behaviour (the frequency 
of practice attendance on the scale 0-3, 4-7, >7 per 
year). The data on their lifestyle was collected by the 
two validated questionnaires: on the diet REAP-S (15) and 
on physical activity RAPA 2 (16). REAP-S questionnaire 
contained 12 questions on healthy diet habits, where 
each question is worth 1 point if the diet habit is bad, 
2 points for occasional inappropriate behaviour and 3 
points for healthy eating. The RAPA questionnaire asks 
patients about several levels of their physical activity. 
We defined adequate aerobic physical activity by the 
requirements of healthy lifestyle, i.e. at least 30 minutes 
of moderate or heavy physical activity at least 5 times per 
week. For the smoking status we asked if the patient is a 
current smoker or not. The number of additional chronic 
illnesses was obtained from the check-list of the diseases 
that each patient could choose from (AH, depression, 
hypercholesterolemia).
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10.2478/sjph-2018-0006 Zdr Varst. 2018;57(1):39-46
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We also obtained data on the regularity of taking 
medication - Morisky questionnaire (17) - and the patients’ 
evaluation of the practice by the Europep questionnaire 
(18). 
From the AUDIT of the medical record, we obtained 
information on the level of cholesterol, fasting blood 
glucose and average blood pressure of the last three 
measures (all data from the last 15 months).
2.2.2 The Outcome
Quality of life was measured by the EQ-visual analogue 
scale (0-100) and self-assessed EQ-5D questionnaire, which 
is a widely used tool to measure HRQoL and contains five 
dimensions, namely: mobility, self-care, usual activities, 
pain/discomfort and anxiety/depression. Every dimension 
has three levels of severity: no problems, some/moderate 
problems and severe problems (19-21). The questionnaire 
is evaluated through the single summary index by applying 
a formula that attaches weights to every level in every 
dimension and is country validated (22). This common 
index shows the patient’s perceived HRQoL.
2.3 Statistical Analysis
We used the statistical package IBM SPSS Statistics version 
21 for Windows (IBM Corp., Armonk, NY). Demographic 
data and risk factors for CVD were presented by 
frequencies and percentages. To explain the effect of 
lifestyle and other characteristics of the patients on their 
HRQoL, we calculated the multivariate linear model with 
the statistical significance at p<0.05. Some independent 
variables were dichotomized according to the goal – if the 
goal was attained, the variable received 1 point, if it was 
not attained, it received 0 points (blood pressure <140/80 
mm Hg, fasting blood glucose –<6.0 mmol/L, BMI<30kg/
m2). We constructed the composite variable of regulated 
risk factors by the sum of the attained goal for a specific 
risk factor/disease (regulated blood pressure, value of 
cholesterol, smoking, physical activity and BMI). 
3 RESULTS
871 patients were included (80.6% of the aimed sample). 
The average age was 63.3 years (SD 8.8). Other patient 
characteristics are presented in Table 1.
Nutritional habits: The average value of the questionnaire 
below, 1.5 points (bad habits), was received only by 2.8% 
of the patients; from 1.5-2.0 points (occasional errors 
in healthy diet, medium habits) were received by 29.9% 
of the patients; >2.0-2.5 points were received by 62.6% 
(good habits) of the patients; very good diet habits with 
the average answers worth ≥2.5 points were received by 
4.7% of the participants.
Table 1. Demographic characteristics of patients with a high 
risk for CVD.
Legend:
1 the predominant ethnical group (Slovenian) vs. ethnical 
minorities 
2 secondary school or more vs. primary school
3 any form of regular income (salary, pension)
4 self-assessed social class: low, medium, high
539 (64.4)
610 (70.0)
707 (81.2)
478 (63.1)
724 (92.3)
164 (21.9)
559 (74.5)
27   (3.6 )
266 (34.0)
413 (52.8)
103 (13.2)
Gender (men) (N=837)
Marital status (married or cohabitating) 
(N=871)
Ethnical group (predominant) (N=871)1
Education (secondary school or more) 
(N=757)2
Income (yes) (N=784)3
Social class (N=750)4     lower 
         middle
         high
Frequency of attendance  
of the practice/year (N=782)     0-3
               4-7
               8 or more
Characteristics (N of 
the sample)
N (%)
Physical activity: In the questionnaire, 305 (N=712) (42.8%) 
patients answered that they perform an adequate level of 
physical activity (exercising at least 5 times/week for at 
least 30 minutes with moderate or heavier exercise).
659 (84.9%) patients have prescribed regular medication 
(N=776). Adherence to medication was measured by the 
Morisky questionnaire. On the scale of 4 points (low 
adherence) to 8 points (high adherence), 4-5 points were 
received by 39 (5.9%) participants, 6-7 points by 356 
(54.0%) and 8 points by 264 (40.1%) of participants.
The practice evaluation by the Europep questionnaire 
showed the average value of 4.52 (SD 0.52) on the scale of 
1-5 (1=poor, 5=excellent). The part of the questionnaire 
evaluating the quality of the practice showed the mean 
value of 4.8 (SD 0.69), whereas the evaluation of its 
organisation showed the mean value of 4.43 (SD 0.60).
The percentage of patients with regulated risk factors for 
CVD is shown in Table 2.
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Table 2.
Table 3.
Risk factors for CVD, dichotomised according 
to target level.
Descriptive results on HRQoL for each dimension and each level.
Legend:
1 according to the REAP-S questionnaire
2 body mass index
3 the adequate physical activity according to RAPA questionnaire
4 blood pressure, value of cholesterol, smoking, BMI, physical 
activity
202 (27.1)
19 (2.7)
350 (58.6)
612 (80.7)
303 (34.8)
604 (N=77.6)
305 (42.8)
168 (34.5)
292 (60.0)
27 (5.5)
503 (65.8)
353 (33.1)
8 (1.0)
250 (32.5)
476 (61.9)
43 (5.6)
500 (64.9)
254(32.9)
17 (2.2)
734 (95.0)
36 (4.7)
3 (0.4)
460 (59.1)
318 (40.9)
0
Cholesterol <5 mmol/L (N=745)
Healthy diet1 (>18 points)1 (N=691)
BMI2 <30 kg/m2 (N=597)
Glu <6 mmol/L (6 or less) (N=758)
RR <140/90 mm Hg (N=871)
Non-smoker (N=778)
Physical activity3 (N=712)
Uncontrolled risk factors (N=487)4 1-2
    3-4
    5
Without problems
Moderate problems
Severe problems 
N (%)Risk factor
Anxiety/
depression 
(N, %) N=764
Pain- discomfort 
(N, %) N=769
Usual activities 
(N, %) N=771
Self care (N, %)  
N=773
Mobility (N, %) 
N=778
72.4% of the participants had arterial hypertension, 61.1% 
of the participants had hypercholesterolemia and 15.2% 
stated that they have depression. 320 (50.7%) patients 
stated that they have at least two chronic diseases from 
the list.
The results of measuring the Quality of life on the VAS 
scale (range 1-100) showed the mean value of 63.2 (SD 
19.4), while the composite index of HRQoL was 0.72 (SD 
0.19).
Pearson correlation showed significant correlations of 
HRQoL with: males (r=0.14, p=0.042), the number of visits 
in the practice (r=-0.31, p<0.001), socioeconomic status 
(r=-0.25, p=0.001), age (r=-0.27, p=0.001), healthy diet 
(r=0.20, p=0.006). The correlation of HRQoL and patients’ 
evaluation of the practice and quality of care were 
both significant, but weak (p=0.001, r=0.18; p<0.001, 
r=0.12). There were other weak positive correlations with 
education and having regular income.
In the multivariate linear analysis, we included the 
following independent predictors of HRQoL: demographic 
characteristics of the patients (age, sex, education, 
marital status, regular income), lifestyle (physical activity, 
diet habits), physical health represented by the number of 
chronic diseases from the list, the number of non-regulated 
risk factors for CVD, the number of visits of the practice 
per year, the regularity of taking medication and patient 
evaluation of the practice from the organizational and 
clinical aspects. The multivariate model is represented in 
Table 4.
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Table 4. Predictors of HRQoL in patients with a high risk for CVD. 
R2 adj=0.107, F=5.49, p=<0.001
Dependent Variable: Summary index of HRQoL questionnaire
Legend
1 secondary school or more vs. primary school
2 any form of regular income (salary, pension)
3 healthy diet according to the REAP-S questionnaire
4 the adequate physical activity according to RAPA questionnaire
5 blood pressure, value of cholesterol, smoking, BMI, physical activity
6 the frequency of visits in the practice per year
(42.776, 84.815)
(-1.209, -0.081)
(-3.827, 0.438)
(-0.769, 3.570)
(-1.905, 2.904)
(-3.356, 4.092)
(-4.347, 2.720)
(1.354, 5.229)
(-2.243, 2.811)
(-1.316, 0.645)
(-5.807, -2.682)
(-0.277, 1.989)
(-1.432, 3.313)
(-1.303, 3.176)
<0.001
0.025
0.119
0.205
0.683
0.846
0.651
0.001
0.825
0.502
<0.001
0.138
0.436
0.412
10.697
0.287
1.085
1.140
1.224
1.895
1.798
0.986
0.221
0.499
0.795
0.577
1.207
1.140
63.795
-0.645
-1.694
1.401
0.499
0.368
-0.813
3.292
0.284
-0.335
-4.245
0.856
0.940
0.936
(Constant)
Age
Sex (male)
Education1
Marital status (married)
Income2
Healthy diet3
Physical activity4 
N0 of chronic diseases
N0 non-regulated risk factors (diseases)5 
Freq visits6
Regular medication
Europep (organization)
Europep (clinical care)
95.0% CI for Bp valueSE for BBModel
The multivariate model for HRQoL explained 10.7% of 
the variation. Independent predictors for higher HRQoL 
in high-risk patients for CVD were lower age, less visits 
to the practice and adequate, regular physical activity, 
among lifestyle determinants. 
4 DISCUSSION
In the group of high-risk patients for CVD, we looked 
for HRQoL as an outcome measure. The first important 
result of our study is somehow surprisingly a low average 
HRQoL in this group of patients. Secondly, among lifestyle 
characteristics, only adequate physical activity was 
associated with better HRQoL. A positive predictor was 
also a lower frequency of visits in the practice, while a 
higher age of the patient was expected negative predictor 
of HRQoL. 
In our sample, men prevailed, which was not surprising, 
as the participants were chosen in the group of high-risk 
patients, where gender represents one determinant of 
the CVD risk. In our sample, most of the patients made 
occasional errors in their diet, and less than half of them 
were adequately physically active. Most of the patients 
were average practice attendees according to their 
frequency of visits; they had an average socioeconomic 
status and gave their practice a high evaluation. A 
substantial number of risk factors was not controlled (3-4 
uncontrolled risk factors in 60% of the participants). 
Typical patient characteristics, associated with worse 
HRQoL in other studies, are older patients, women, less 
educated and living alone, and being frequent attenders. 
The average age of participants in our study was over 60 
years, when the association between age and HRQoL is 
even more expected. We found a correlation between 
lower HRQoL and women, and a weak correlation with 
higher education and income. 
The composite index of EQ-5D was 0.72 (SD 0.19), which 
is lower than in the international analysis of high-risk 
patients in the EPA-Cardio study, where it was found to 
be 0.78 (SD 0.19) (23) and lower than in other studies, 
even for CVD patients (24). On the other hand, coronary 
patients in the national analysis of Epa-Cardio data showed 
lower HRQoL in coronary patients, measured by EQ-5D VAS 
scale (58.6±19.9) (25), compared to high risk patients in 
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our study (63.2±19.4) . It is also lower than in the sample 
of patients from the general practice of the Wang study 
(69.2) (26). We cannot explain what the reason for this 
difference could be, as the sampling of these studies was 
different from ours. 
The association of isolated risk diseases, such as 
hypertension, is conflicting and shows no relationship 
with HRQoL (26, 27) or contributes to a lower HRQoL 
(28). In the cited literature, obesity has been shown to 
influence HRQoL in specific categories of HRQoL (29-
31), and associated with the socioeconomic status (32). 
The relationship between cardio-metabolic risk factors/
diseases and HRQoL is controversial and not found in some 
of the other studies (33). Our results could not prove 
these associations with the overall HRQoL either.
In testing lifestyle characteristics, we found a weak 
bivariate correlation of HRQoL with a healthy diet and 
a significant association with physical activity in the 
multivariate model. Randomised trials of patients with 
metabolic syndrome showed that an improved lifestyle 
with a healthy diet and regular physical activity improved 
HRQoL (34-35) and self-rated health (36). The results 
of Imayama on postmenopausal women showed the 
same (37). Physical activity has several positive effects 
on similar outcomes, such as lowering the stress and 
improving satisfaction with life (38). Adequate physical 
activity has been shown to be a positive predictor of 
HRQoL for middle-aged and older people in several other 
studies (31, 37-39), specifically pointing out that not 
only aerobic activity is important, but also building body 
strength and flexibility (39-41). We described the level of 
physical activity only by aerobic exercise, which is also 
the most advised in patient counselling. In the future, 
we have to address all aspects of physical activity, since 
it has been shown that they are all needed, not only 
for a better HRQoL, but also to prevent falls and help 
keep balance in the older population. Studies show that 
even suboptimal physical fitness is important for HRQoL 
in older persons with mild hypertension (42). Increased 
fitness is even more important than normal body weight 
(43). Fewer studies can be found directed to the influence 
of the physical programme on HRQoL for high-risk CVD 
patients. Gidlow showed some evidence that programmes 
are specifically effective for high-risk groups. But although 
he found that reducing risk factors and the risk score were 
both significant, the differences in HRQoL were small (44). 
We could not prove the association between HRQoL and 
patients’ evaluation of the practice in the multivariate 
model, but we found correlations in the bivariate model 
for patient’s evaluation of the practice and clinical care. 
Other studies support the fact that there probably is an 
association (23, 45-46). 
Moreover, we could not prove the importance of 
multimorbidity in our sample. We believe that the 
reason could be the fact that we included only “risk 
diseases” for CVD and depression as an important mental 
disorder which influences HRQoL. Multimorbidity was 
shown to be a strongly associated factor for HRQoL, 
especially in combination with specific diseases, 
such as gastrointestinal, neurological, psychiatrical, 
musculoskeletal, nephrological and cardiovascular 
diseases (47-49). Furthermore, the inclusion of the 
severity of the disease according to the multimorbidity 
index shows a stronger association with HRQoL than 
simply counting the number of diseases (50).
4.1 Limitations of the Study
The variables included in the model showed weak 
prediction of HRQoL. Some variables, such as 
multimorbidity (42), should be better specified by the 
stage and functional limitations of the diseases and by 
more chronic diseases that can affect HRQoL, such as 
chronic pain, gastrointestinal disease, lung disease, etc., 
and should be included in the list. We also noticed that 
the validated questionnaires for healthy diet and physical 
activity might have been cognitively demanding for 
the participants, resulting in more missing values than 
expected.
Also, we believe that the frequency of visits is probably 
not a “pure” independent variable but potentially a 
confounding variable. Logically thinking, the correlation 
of frequency of visits and HRQoL needs to be interpreted 
as a reverse causality, as low HRQoL may predict high 
frequency of patients’ visits in the practice and not the 
opposite.
5 CONCLUSION
Among lifestyle characteristics, regular exercise seems 
to be the most important independent predictor for a 
patient’s perceived overall HRQoL, Healthy diet was 
correlated to HRQoL, too. Encouragement of high-risk 
patients for CVD to improve or keep healthy lifestyle is 
important, not only to lower the risk for CVD, but also to 
improve quality of life. Specific aspects of HRQoL need to 
be tested in defined categories of patients. 
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CONFLICTS OF INTEREST
The authors declare that no conflicts of interest exist.
FUNDING
The study was financed by the Slovenian Institute for the 
Development of Family Medicine and the Bertelsmann 
Foundation, which had no influence on the study design, 
analysis or interpretation of the results.
ETHICAL APPROVAL
The study was approved by the Republic of Slovenia 
National Medical Ethics Committee at the Ministry of 
Health, No. 87/01/11.
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