Scandinavian Journal of Public Health, 2008; 36: 850–856
ORIGINAL ARTICLE
Costs of heart disease and risk behaviour: Implications for expenditure
on prevention
MARIE KRUSE1, MICHAEL DAVIDSEN1, METTE MADSEN2, DORTE GYRD-HANSEN3 &
JAN SØRENSEN4
1
National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark, 2Institute of Public Health,
University of Copenhagen, Copenhagen, Denmark, 3Institute of Public Health, University of Southern Denmark, Odense
Denmark and Danish Institute for Health Services Research, Copenhagen, Denmark, and 4Centre for Applied Health Services
Research and Technology Assessment, University of Southern Denmark, Odense, Denmark
Abstract
Aims: The objective of this paper is firstly to estimate the healthcare costs attributable to heart disease in Denmark using
recently available data for 2002–05. Secondly, to estimate the attributable healthcare costs of lifestyle risk factors among
heart patients, in order to inform decision making about prevention programmes specifically targeting patients with heart
disease. Methods: For a cohort consisting of participants in a national representative health interview survey, register-based
information about hospital diagnosis was used to identify patients with heart disease. Healthcare consumption during 2002–
05 among individuals developing heart disease during 2002–05 was compared with individuals free of heart disease.
Healthcare costs attributable to heart disease were estimated by linear regression with adjustment for confounding factors.
The attributable costs of excess drinking, physical inactivity and smoking among future heart patients were estimated with
the same method. Results: Individuals with heart disease cost the healthcare system on average J3195 (pv0.0001) per
person-year more than individuals without heart disease. The attributable cost of unhealthy lifestyle factors among
individuals at risk of heart disease was about 11%–16% of the attributable cost of heart disease. Conclusions: Heart
disease incurs significant additional costs to the healthcare sector, and more so if heart patients have a history
of leading an unhealthy life. Consequently, strategies to prevent or cease unhealthy lifestyle may not only result
in cost savings due to avoided heart disease. Additional cost savings may be obtained because heart patients
who prior to the disease led a more healthy life consume fewer healthcare resources.
Key Words: Attributable costs, excess drinking, heart disease, physical inactivity, prospective cohort analysis, smoking
Background
Heart disease is a major cause of death and hospitalization throughout the world. With expensive treatment procedures and high prevalence, the disease
incurs high costs to the healthcare sector [1–5].
The costs of heart disease represent potential
savings to the healthcare sector if successful preventive programmes targeting lifestyle changes can
be implemented. However, improving the lifestyle
of individuals at risk of heart disease may also
affect the course of the heart disease should it occur.
Consequently, there may be an economic effect of
prevention in addition to the cost savings associated
with avoiding heart disease in terms of less expensive
treatments being needed among heart patients who
have a history of a more healthy lifestyle.
In order to quantify this effect, it is necessary to
assess the costs of heart disease and the impact of
lifestyle risk behaviour before disease debut on
healthcare costs of heart disease.
A few European studies have assessed the attributable costs of heart disease in terms of the average
additional cost of heart patients in comparison with
Correspondence: Marie Kruse, National Institute of Public Health, University of Southern Denmark, Øster Farimagsgade 5A, DK-1399 Copenhagen,
Denmark. Tel: +45 3920 7777. Fax: +45 3920 8010. E-mail: [email protected]
(Accepted 1 July 2008)
# 2008 the Nordic Societies of Public Health
DOI: 10.1177/1403494808095955
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Costs of heart disease
non-heart patients. Taylor et al. (2007) estimated
the attributable healthcare costs for patients suffering from acute coronary syndrome in 2004 in a
number of European countries. They found the
average annual attributable healthcare costs to be
J7000 in the UK and J8000–10,000 in France,
Germany and Spain [6]. For Sweden, Zethraeus et al.
(1999) estimated the attributable cost of coronary
heart disease to be J4400 per patient per year [7].
A number of studies have quantified population
attributable fractions (PAF), that is, the share of the
disease burden attributable to a certain risk factor,
for example physical inactivity in relation to heart
disease [8–10]. A few studies assessed PAF for
excess drinking in relation to heart disease [11–13].
However no studies were found to analyse the cost
attributable fraction to lifestyle risk factors, that is,
the healthcare costs attributable to physical inactivity
or excess drinking in patients with heart disease.
However, it has been shown that smoking has an
unambiguous negative impact on health as well as on
healthcare costs [14–16].
The smoking attributable fraction (SAF) of
healthcare costs, defined as the fraction of healthcare
costs due to heart disease, which is attributable to
smoking, was found to be 6%–8% in a general
population [15,16]. Higher cost estimates were
found in studies that focus on heart patients
specifically, although there is great variation across
studies. Lightwood (2003) found the cost SAF for
heart disease to be about 20% [17], while ReynalesShigematsu et al. (2006) estimated the cost SAF for
myocardial infarction to be 56% [18] and Martiniuk
et al. (2006) found in a comparative study for the
Asia-Pacific region the cost SAF to be 13%–33% for
male heart patients and v1%–28% for female heart
patients [19].
Aim
With the aim of informing decision making about
prevention programmes specifically targeted towards
patients at risk of heart disease, the objective of this
paper is firstly to estimate the healthcare costs
attributable to heart disease in Denmark using
recently available data for 2002–05, and secondly,
to estimate the attributable healthcare costs of
lifestyle risk factors amongst future heart patients.
In a register-based cohort, we identified a sample of
patients aged over 50 years who were diagnosed with
heart disease for the first time during 2002–05 and
compared their annual healthcare cost with a similar
population of individuals without heart disease. For
the heart patients we estimated attributable costs of
851
their excess drinking, physical inactivity and smoking before disease debut. To adjust for differences in
social factors and lifestyle we employed multiple
regression analysis.
Data and methods
We used data from the Danish National Cohort
Study (DANCOS) [20]. DANCOS includes individuals who participated in the Danish nationally
representative health interview surveys (NHIS). In
addition to the survey data, DANCOS holds data on
the participants’ use of healthcare resources obtained
through linkage to several national registers.
In this study we included the cohort who completed the personal interview in the 2000 NHIS. The
2000 cohort was based on a geographical stratified
sample of 22,486 individuals aged 16 and older of
which 74.2%, or 16,688 individuals, agreed to
participate [21].
In Table I the cohort used for this study is
described. From the sample of 16,688 individuals,
we excluded respondents under 50 years of age
(n59,559), respondents with missing information
relating to social or lifestyle variables (n515) and
individuals who prior to 2002 had been admitted to
hospitals with a diagnosis of heart disease (n5958).
The final cohort comprised 6171 individuals aged
50+ years and no hospital contact with a heart disease
diagnosis at the start of 2002. Three hundred and
eight, or 5%, of those individuals were diagnosed with
heart disease during the study period 2002-05.
For each individual in the cohort we obtained selfreported data on length of education and lifestyle
(smoking, alcohol consumption, physical activity,
body mass index, stress) from the 2000 NHIS; and
date of death or migration (if any) from the
Centralised Civil Register. The survey questions on
lifestyle are displayed in Table II. The survey was
completed in 2000, i.e. the lifestyle factors relate to
the period before the disease debut.
Table I. Characteristics of participants in the national representative health survey.
Heart Non-heart
patients* patients
Population before exclusion
Excluded due to age under 50
Excluded due to heart disease before 2002
Excluded due to missing information
Study population
1483
216
958
1
308
15,205
9343
–
14
5848
*Defined as individuals with a hospital contact with a primary
diagnosis of heart disease during 2002-05
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852
M. Kruse et al.
Table II. Characteristics of heart patients before disease debut, and non-heart patients, in the 2000 NHIS.
Definition in the analysis
Mean age
Percentage men
Percentage smokers
Percentage without
education or
training
Percentage
physical inactive
Percentage with
body mass
index w30
Percentage who often
or occasionally
feel stressed
Percentage alcohol
abstainers
Age at the interview was divided into 10-year intervals
Gender, male/female
Based on the survey question: Do you smoke? (‘‘Yes’’, ‘‘Yes but
on some days I don’t smoke’’, ‘‘No’’). In this study, respondents
who smoke occasionally are considered smokers. Smoking
therefore has two categories.
Based on the survey question: ‘‘Have you completed any kind of
vocational training or education? If yes, which?’’ (The survey
question has nine categories, here divided into three: no education,
short or vocational training, tertiary education.)
Based on the survey question ‘‘If we look back on the past year,
what would you say best describes your spare time activities?
(1: Heavy training and competitive sports regularly and several
times a week; 2: Exercise or heavy gardening at least 4 hours
a week; 3: Walk, bike or other easy exercise at least 4 hours
a week (include Sunday excursions, light gardening and biking/
walking to work); 4: Read, watch TV or other sedentary occupation)’’
BMI was based on self-reported height and weight and divided into
three categories: less than 25 (underweight or normal), 25–30
(overweight), more than 30 (obese).
Based on the survey question: ‘Do you suffer from stress in your everyday
life?’ (The response has three categories: ‘‘often’’, ‘‘sometimes’’, ‘‘rarely
or never’’)
Based on the survey question: ‘‘How many alcoholic drinks did you have
each day last week? We’ll start with yesterday and take one day at a time
(1 drink512 grams of alcohol).’’ The respondent is asked to state a
number of drinks for each of the 7 previous days. In this study we divided
alcohol consumption into three categories: abstainers (one drink or less
per week), moderate drinkers (two to 14 drinks per week for women and
two to 21 drinks per week for men); and excess drinkers (15 or more
drinks per week for women and 22 or more drinks per week for men)
Data on the utilization of healthcare services were
obtained for each individual through the National
Patient Register (hospital services) and the National
Health Insurance Register (primary healthcare services). The cost of hospital services was defined
through the Danish system of diagnostic related
groups (DRG) that includes an average cost per
inpatient admission or outpatient visit. For primary
healthcare services the cost was defined as the
activity-based remunerations. Per capita payment
to general practitioners was disregarded, as were all
non-variable costs in the hospital sector.
We conducted a prospective cohort analysis where
cases were identified as heart patients and compared
with similar individuals without heart disease.
Heart patients were identified through inspection
of the hospital records during 2002–05. The first
hospital contact (inpatient or outpatient) with a
heart disease diagnosis identified the time of disease
debut and the individual was thereafter classified as a
patient with heart disease. Prior to the disease debut,
Heart
patients
n5308
Non-heart
patients
n55,848
t-test for
equality
of means
69.1
59.6
36.4
62.8
45.9
34.4
pv0.0001
pv0.0001
NS
42.1
34.1
p50.002
27.5
19.6
p50.0002
15.2
11.1
pv0.001
20.1
28.1
p50.001
43.8
35.2
P50.005
the individual was categorized as a non-heart
patient. The relevant ICD-10 diagnostic codes
were: DI00–DI25 and DI30–DI52 (thus including
acquired heart disease and excluding congenital
heart disease). Patients with other diseases who
had heart disease as a secondary diagnosis as well as
individuals taking prescription medicines for heart
disease but who had never been admitted to hospital
with a heart disease diagnosis, were considered nonheart patients, in order to maintain operational
definitions.
The healthcare cost per individual was calculated
as the total costs registered in the observation period
divided by the number of 6-month periods the
individual was observed (i.e. adjusting for death and
migration during the observation period). For
patients who were diagnosed with heart disease,
the costs were estimated separately for the period
without and with heart disease.
We tested whether there were significant differences between heart patients and non-heart patients
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Costs of heart disease
in social and lifestyle characteristics using t-test for
equality of means. On the basis of these results we
chose to adjust the cost analysis for differences in
age, gender, socioeconomic grouping, education,
smoking, excess drinking, physical activity, body
mass index and perceived stress.
Costs attributable to heart disease were obtained by a
multiple linear regression analysis. The log-transformation of total costs was considered the dependent
variable. Unadjusted attributable costs were
obtained as the parameter estimate of heart disease
(yes/no) in a regression analysis that included this
single variable.
Similarly, adjusted estimates were obtained using
multiple regression controlling for age, gender,
socioeconomic grouping, education, smoking, excess
drinking, physical activity, body mass index and
perceived stress.
Costs attributable to not adhering to lifestyle recommendations prior to heart disease were obtained as
the parameter estimate for each lifestyle variable in a
multiple regression conducted for heart patients
only.
The resulting parameter estimate is interpreted as
the costs attributable to a history of smoking among
heart patients. For the group of heart patients who
smoked, were physically inactive and excess drinkers
simultaneously, we computed attributable costs of
their risk behaviour, compared with all other heart
patients.
The average costs per 6 months were logtransformed because preliminary examination
showed a skewed distribution with a long right hand
tail, as is frequently observed for healthcare cost
data. Before log-transformation, observations with
zero costs were assigned a value of J0.1. The
transformation normalized the distribution of residuals. The logged costs were transformed to
nominal costs using a smearing technique [22,23]
where the logged cost means were exponentiated
853
and multiplied by a smearing factor, compiled as the
difference between the parameter estimate and the
mean. SASH v. 9.1 was used for all computations.
All costs were adjusted to 2007 price level using
the net price index. 2007 costs were converted from
Danish Kroner to Euros using the exchange rate
J157.50 DKK. Net present values were estimated
using a discount rate of 3%.
Results
Table II shows the characteristics of included heart
patients in 2000. The cohort with heart disease
included more men and was older than the cohort
without heart disease. There were more heart
patients with no or short education, they were more
likely to be overweight and less likely to be stressed
compared to non-heart patients. There was no
significant difference between the two groups in
smoking behaviour.
In Table III, total and attributable cost estimates
are shown. The total mean healthcare cost for heart
patients was J4285 and J876 for the control group.
The unadjusted regression result for attributable
cost was J3409 per person year – almost five times
the cost of the control group. When adjusting for
age, gender, socioeconomic group, education and
lifestyle, the average cost attributable to heart disease
reduced to J3195 per person year.
Table III also reports the regression results for the
attributable costs of an unhealthy lifestyle. High
intake of alcohol among heart patients was associated with an attributable cost of J503 per person
year, or 15.7% of costs attributable to heart disease.
Physical inactivity was associated with an attributable cost of J362 or 11.3 %, and smoking was
associated with an attributable cost of J474 or
14.8%. A lifestyle including all three risk factors
simultaneously was associated with an attributable
cost of J890 or 27.9%.
Table III. Estimated attributable costs (NPV 2007-EURO)
Costs per person year
95 % CI
4285
876
3409
3223
3195
585
503
503
362
384
474
890
4109–4461
859–893
3326–3492
3139–3307
3112–3670
406–765
309–697
334–671
185–541
256–512
338–609
47–1734
Total healthcare costs, heart patients
Total healthcare costs, non-heart patients
Costs attributable to heart disease, unadjusted
Costs attributable to heart disease, adjusted for age and gender
Costs attributable to heart disease, adjusted for sociodemographic variables and lifestyle
Costs attributable to excess drinking among heart patients, not adjusted
Costs attributable to excess drinking among heart patients, adjusted
Costs attributable to lack of physical exercise among heart patients, not adjusted
Costs attributable to lack of physical exercise among heart patients, adjusted
Costs attributable to smoking among heart patients, not adjusted
Costs attributable to smoking among heart patients, adjusted
Costs attributable to excess drinking, physical inactivity and smoking among heart patients
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854
M. Kruse et al.
The attributable cost of unhealthy lifestyles was
higher when no adjustment was made for age,
gender, socioeconomic group, education, body mass
index and perceived stress, although the cost
associated with smoking was lower.
Discussion
The linkage of survey data and administrative
registers at individual level provided a data set with
an accurate description of the resource use and
enabled us to analyse usage of health services in
relation to self-reported lifestyle. As the cohort is
based on a nationally representative sample the
external validity of the results is high.
All healthcare costs were related to the heart
patients’ group or the non-heart patients’ group by
half person years. This may potentially cause a
minor bias as some non-heart disease related costs
could be wrongly categorized as heart disease related
costs.
Healthcare costs were estimated on basis of
register-based information on DRG prices, and
charges. These may not accurately reflect the
opportunity costs that ideally should be used.
However DRG prices and charges are the best
available proxies for opportunity costs.
The present study included healthcare costs for a
maximum period of 4 years subsequent to heart
disease diagnosis. The short follow-up period was
chosen since a longer-term analysis of costs of
lifestyle in relation to heart disease has some caveats.
In particular, non-smokers live longer than smokers
[24–26] and are thus likely to incur more healthcare
costs during their lifetime than smokers. The same
applies, to a lesser extent, to other lifestyle components [26]. Also, applying a long run perspective
would have required more information on lifestyle
changes over time in order to adjust for changes
relative to the status in the year 2000. With the available information it was considered inappropriate to
extrapolate the results to a lifetime perspective.
Adherers to lifestyle recommendations and nonadherers are likely to differ on other characteristics
than their adherence to prevention. Although we
have made an effort at controlling for confounders
such as age, gender, education and other lifestyle
components, we cannot exclude the possibility that
other explanatory factors may to some extent drive
the cost difference we observed.
Our results confirm earlier observations that
individuals with heart disease impose higher costs
on the healthcare system than individuals without
heart disease. The level of the estimated attributable
costs correspond to about three quarters of the
Zethraeus et al. (1999) result of J4400 per coronary
heart disease patient per year [7]. Compared to the
findings of Taylor et al. (2007), our estimate is even
less, about half of the estimated attributable costs of
acute coronary syndrome in the UK [6].
We applied a broader definition of heart disease
than these earlier studies, as we also included nonacute admissions, e.g. those due to heart failure or
heart valve disease. This may, to some extent,
explain our results being lower than other studies.
Smoking and excess drinking are associated with
additional healthcare costs for patients with heart
disease. We also found higher costs attributable to
physical inactivity in relation to heart disease.
The share of attributable costs for a given risk
factor is not related to the population attributable
fraction. The population attributable fraction for
excess drinking and physical inactivity [9,11–13]
pertains to the higher risk of developing the disease,
whereas the higher costs might arise from higher
treatment costs for excess drinkers and physical
inactivity. Thus, risks and treatment costs are
unrelated.
In the field of smoking, cost attributable fractions
have been estimated [17–19].
The estimated costs of smoking is less than the
cost SAF of 20% estimated by Lightwood (2003)
[17]. The result, however, falls within the cost SAF
range of 13%–33% for men and v1%–28% for
women established by Martiniuk et al. (2006) [19].
It is likely that the differences between our results
and Lightwood’s have methodological grounds,
as Lightwood’s estimate is based on a top-down
analysis and not on individual data.
The estimate for attributable costs of all three risk
factors together is rather uncertain as only about 3%
of heart patients adopted all three risk factors
simultaneously.
The attributable costs of three risk factors in
combination were not much less than the sum of
attributable costs for the individual risk factors. This
relates to the other risk factors being adjusted for in
the analysis of the individual risk factor attributable
cost figures.
Unadjusted attributable costs of heart disease
were not substantially higher than adjusted attributable costs. Adjusting for age, gender, education and
lifestyle seems to somewhat reduce the cost difference between heart patients and non-heart patients
while not considerably altering the overall result.
While sociodemographic variables differ between
heart patients and non-heart patients, they only have
a minor impact on costs of heart disease.
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Costs of heart disease
Estimates of costs due to heart disease – or other
diseases – may be interpreted as potential savings
that could be harvested if heart disease was
eradicated. While it remains unrealistic for heart
disease to be eradicated, some interventions may
succeed in bringing down the incidence. A feasible
interpretation of the result is that a potential saving
to society might emerge if the incidence of heart
disease can be reduced through a targeted prevention effort.
Prevention of heart disease may take many forms.
In this study we chose to assess the impact on
healthcare costs of preventing heart disease and of
preventing risk behaviour before disease debut
among heart patients. We considered the costs of
heart disease and analysed the share of these costs
attributable to patients’ lifestyle prior to disease
debut. We found that about one sixth of the
attributable costs of heart disease could be attributed
to these lifestyle components, after adjusting for
covariates. The benefit of prevention of lifestyle risk
factors would be of equal magnitude. This result,
which focuses on the longer-term consequences of
lifestyle, points to the relevance and importance of
prevention programmes aimed at patients who are at
risk of heart disease. Moreover, a healthy lifestyle is
likely to yield savings for other diseases in a similar
manner as described for heart disease in this paper.
Non-adherence to lifestyle recommendations renders heart disease more costly. More healthcare
expenditure is channelled towards treatment of these
patients; these resources could be used elsewhere in
the healthcare sector, if non-adherers change their
behaviour.
Conclusion
We found that heart disease is associated with
attributable healthcare costs of J3195 per person
year; these costs are higher for individuals not
adhering to lifestyle recommendations. An unhealthy lifestyle increases healthcare costs associated
with heart disease significantly, which impacts
negatively on the entire budget for health care, and
consequently on expenditure on other patient
groups. Therefore an increased spending on effective
prevention programmes could have wide-ranging
beneficial effects.
Acknowledgments
We wish to thank the NHIS respondents for
taking part in the survey. There are no competing
interests. The source of funding for this work is an
855
unrestricted PhD grant from the Danish Heart
Foundation.
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