Trends in multimorbidity and polypharmacy in the Flemish-Belgian population between 2000 and 2015
Trends in multimorbidity and polypharmacy in the Flemish-Belgian population between 2000 and 2015
Marjan van den AkkerID 0 1 3
Bert VaesID 1 3
Geert Goderis 1 3
Gijs Van Pottelbergh 1 3
Tine De Burghgraeve 1 3
S e?verine Henrard 1 2 3
0 Department of Family Medicine, School Caphri, Maastricht University , Maastricht , the Netherlands
1 Department of Public Health and Primary Care, University of Leuven (KU Leuven) , Leuven , Belgium
2 Louvain Drug Research Institute and Institute of Health and Society (IRSS), Universite ? catholique de Louvain (UCL) , Brussels , Belgium
3 Editor: Brecht Devleesschauwer , Sciensano , BELGIUM
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Funding: The authors received no specific funding
for this work.
Competing interests: The authors have declared
that no competing interests exist.
The aim of this paper was to describe the time trends in the prevalence of multimorbidity and
polypharmacy in Flanders (Belgium) between 2000 and 2015, while controlling for age and
Data were available from Intego, a Flemish-Belgian general practice-based morbidity
registration network. The practice population between 2000 and 2015 was used as the
denominator, representing a mean of 159,946 people per year. Age and gender-standardised
prevalence rates were used for the trends of multimorbidity and polypharmacy in the total
population and for subgroups. Joinpoint regression analyses were used to analyse the time
trends and breaks in trends, for the entire population as well as for specific age and sex
Overall, in 2015, 22.7% of the population had multimorbidity, while the overall prevalence of
polypharmacy was 20%. Throughout the study period the standardised prevalence rate of
multimorbidity rose for both sexes and in all age groups. The largest relative increase in
multimorbidity was observed in the younger age groups (up to the age of 50 years). The
prevalence of polypharmacy showed a significant increase between 2000 and 2015 for all age
groups except the youngest (0?25 years).
For all adult age groups multimorbidity and polypharmacy are frequent, dynamic over time
and increasing. This asks for both epidemiological and interventional studies to improve the
management of the resulting complex care.
Multimorbidity?the co-occurrence of two or more chronic diseases in a patient [
polypharmacy?the prescription of five or more medications in one year [
] are broadly
recognized as important and interrelated phenomena [
The consequences of multimorbidity have often been studied and have been reported on an
aggregated level, with even a recent overview of systematic reviews [
]. In his review McPhail
reported a curvilinear, near exponential association between additional chronic diseases and
health care costs [
]. Fortin and colleagues reviewed original studies of the quality of life in
patients with multimorbidity; despite methodological shortcomings and the diversity of the
studies, they reported a clear inverse relation [
]. There was also a diverse picture for mortality,
but an overall increased risk of death among patients with multimorbidity was reported [
Traditionally, multimorbidity research has focussed on older people and predicts an
alarming picture of future developments [
]. However, in absolute numbers, the majority of people
with multimorbidity are still under 65 years of age [
Polypharmacy is frequently found among people with multimorbidity: the disease number
is a stronger predictor for the number of medications prescribed than age is [
multimorbidity, polypharmacy is famous for its negative consequences, such as diminished
adherence and more frequent adverse events. Approximately 6.5% of all emergency hospital
admissions are attributable to adverse drug events, and at least half of these are judged to have
been preventable [
Estimating the additional health care costs of multimorbidity and polypharmacy is not
straightforward, as some combinations result in a synergetic cost effect and some have shown
a disproportionate impact on health care utilization far beyond the simple addition of costs
]. A recent overview revealed that multimorbidity is related to higher health care costs, not
only for emergency hospital admissions, but also for more frequent visits to primary care and
hospital specialists, more hospital admissions and a higher number of bed days in hospital,
and more medication use [
Multimorbidity and polypharmacy are obviously closely related. The prescription of
appropriate medication, balancing harm and benefit and following medical guidelines, becomes
increasingly difficult with a growing number of chronic medical conditions [
]. Among older
patients with multimorbidity and polypharmacy, this balance is even more fragile, due to
ageing-related changes such as decreased liver and kidney function, more sensitive receptors and
decreased homeostatic reserves.
It is often reported that the number of people suffering from chronic diseases,
multimorbidity and polypharmacy has increased in the past decades. This is mainly based on
cross-sectional studies over time, in different populations [
]. Time trends in the prevalence of
multimorbidity and polypharmacy are scarce [
]. The Flemish primary care-based Intego
network offers an excellent opportunity to evaluate those trends.
The aim of this paper is to describe the time trends in the prevalence of multimorbidity and
polypharmacy between 2000 and 2015 in Flanders (Belgium) while controlling for age and sex.
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Materials and methods
Data were available from Intego, a Flemish-Belgian general practice-based morbidity
registration network at the Academic Centre of General Practice of the KU Leuven [
]. Around 100
general practitioners (GPs) provide annual information about all their patients through a
trusted third party. Collaborating GP practices are spread over Flanders (Belgium). Before GPs
are accepted as a participant in Intego, they have to fulfil three quality criteria. First, the
average number of new diagnoses per patient per year should be higher than one. Second,
diagnoses have to be entered in the practice software using keywords. Diagnoses are automatically
classified using an extensive thesaurus, which translates keywords into the International
Classification of Primary Care (ICPC-2) in the process of data extraction. The percentage of
diagnoses recorded without using keywords should be less than 5%. Finally, these parameters must
remain stable for at least three years [
]. Data are collected in a routine manner as part of
daily practice and contain all new diagnoses together with new drug prescriptions, as well as
laboratory test results and some background information (including gender and year of birth).
Registered data are continuously updated and historically accumulated for each patient. For
medication, the Anatomical Therapeutic Chemical (ATC) classification system is used.
In the present study, data available from 31 December 2015 were used. The practice
population, as calculated from all people in the yearly contact groups in Intego between 2000 and
2015, was used as the denominator [
]. This represented a mean of 159,946 people in the
practice population per year, varying between 115,328 and 186,829 people (see S1 Table for the
exact numbers per year). Throughout the study period 79 practices provided their data, with
73% contributing for 13 or more years (see S1 Fig for more detailed information).
For this study, multimorbidity was defined as the co-occurrence of two or more chronic
diseases in a patient [
]. For the assessment of multimorbidity the year-prevalence of the
diseases was used. An overview of the chronic diseases considered in this study is presented in S2
Table . Polypharmacy was defined as the prescription of five or more different medications
in one year [
]. To count medication, the first five characters of the ATC codes were used
(ATC level 4).
Age- and gender-standardised prevalence rates were used for the trends of multimorbidity and
polypharmacy in the total population and for subgroups. Standardised rates were computed
using 5-year age groups based on the distribution of the Flemish-Belgian population in 2015.
There were four age groups: 0?24 years, 25?49 years, 50?74 years, and 75 years and older.
Joinpoint regression analyses were used to analyse the time trends in multimorbidity and
polypharmacy and breaks in trends, for the entire population, as well as for specific age and
sex groups [
]. Joinpoint regression allows identifying periods with a significant change in
the trend, and in addition annual percentage change (APC) per time period and average APC
over the whole period are computed. Our analyses covered the time window between 2000
and 2015, with the dependent variable being the proportion of people with multimorbidity or
polypharmacy, respectively. Trends over a specific period of time were described by the annual
percent change (APC), while trends over the whole 2000?2015 period were summarised using
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the average annual percent change (AAPC). Joinpoint regression models were performed
using the Joinpoint Regression Program, Version 18.104.22.168 (Statistical Research and Applications
Branch, National Cancer Institute). All other analyses were performed using R Software
version 3.1.3 [
]. A p-value <0.05 was considered statistically significant.
The Intego procedures were approved by the ethical review board of the Medical School of
the Catholic University of Leuven (no ML 1723) and by the Belgian Privacy Commission (no
Population characteristics in 2015
The practice population totalled 152,270 people in 2015. Of those, 61.5% did not have any
chronic disease, ranging from 82.6% in the 0?24 year old group to 25.5% in those aged 75
years and older. Overall, 15.9% had one chronic disease, and 22.7% had multimorbidity. The
proportion of both males and females with multimorbidity increased strongly with age, with
females having statistically significantly larger proportions with multimorbidity in all age
groups (Fig 1 and S3 Table). The absolute number of people with multimorbidity was the
highest among those aged 50?74 years (N = 16,945), followed by those aged 75 years and older
(N = 7,836) and 25?49 years (N = 7,529).
Overall, the prevalence of polypharmacy was 20%. The number of medication prescriptions
was also strongly age-related, with just over half of the people aged below 25 years having any
medication prescribed to around 3 out of 10 in people aged 75 years and older having no
medication prescriptions (28.1%, n = 3565/12,700) (Table 1). The prevalence of polypharmacy
ranged from 11.2% in the youngest females to 49.5% in females aged 75 years and older; in males,
rates from 8.3% in the youngest to 50.9% in the oldest were found. Here again, we found the
highest absolute number in the age group 50?74 (N = 7,008), followed by those aged 25?49
years (N = 3,565), with people of 75+ in third place (N = 2,727).
Trends in multimorbidity and polypharmacy over time
Throughout the study period, the standardised prevalence rate of multimorbidity rose for both
sexes and in all age groups. The largest relative increase was observed in the younger age
groups (up to the age of 50 years), with the standardised prevalence rate of multimorbidity
doubling between 2000 and 2015 (Fig 2a). Similar trends were found looking at the crude
figures (Fig 2b). Trend analysis showed a stable increase in the standardised prevalence rate of
multimorbidity for both males and females above the age of 50 and above 75 years (AAPC of
2.4% and 1.8% per year for females, and 2.9% and 2.3% per year for males, respectively)
(Table 2). Young (0?25 years) females and males showed a modest but significant annual
increase in the first period (APC of 2.0% per year between 2000?2006 and of 2.1% between
2000?2009, respectively) and a stronger significant increase afterwards (APC of 7.7% per year
between 2006?2015 and 9.2% between 2009?2015, respectively). For females and males aged
25?49 years, there was an insignificant increase in the first period, but a significant increase of
5.7% per year between 2004?2015 and of 6.0% per year between 2005?2015, respectively.
The prevalence of polypharmacy showed a significant increase?both crude and
standardized?between 2000 and 2015 for people aged 75 years or older, with an 89% and 80% relative
increase for males and females, respectively (Fig 3a and 3b). The AAPC was 3.5% and 4.2% per
year, respectively, with the highest increase for females of 75 years and older in the period
2013?2015 with an APC of 8.3%. Far more modest but still significant relative increases, of
50% for males and 42% for females, were found for people aged 50?74 years. In this age group,
the AAPC was 1.8% for females; for males a significant increase (APC 4.0%) was found in the
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Fig 1. Age trends in the proportions of multimorbidity for males and females (point prevalence, 95% CI).
Number of chronic diseases
Number of medications
Fig 2. Evolution of the age- and sex-standardised prevalence rate of multimorbidity from 2000?2015.
period 2000?2009 only (Table 3). Males and females aged 25?49 years had an AAPC of 1.6%
and 1.9%, respectively, whereas no significant changes in polypharmacy were found for people
aged below 25 years.
This study reports on the evolution of multimorbidity and polypharmacy in Flemish-Belgian
primary care covering a 15-year period. In 2015 we found an overall prevalence of 22.7% for
multimorbidity and 20% for polypharmacy. Both multimorbidity and polypharmacy were
strongly related to higher age, although the absolute number for both multimorbidity and
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polypharmacy was the highest in the age group 50?74 years. For multimorbidity, we observed
an increasing prevalence through the years for all age groups, with an even steeper slope for
the younger age groups during the recent past. For polypharmacy, we observed a more
moderate evolution for people aged less than 50 years as compared to those aged 75 and older.
Context with previous findings
Multimorbidity rates are always difficult to compare, due to the large variation of
methodological choices and populations studied [
]. Nevertheless, the prevalence pattern in age and
sex groups in 2015 in our study seems to be similar to that found in the UK . Our results
regarding the evolution of multimorbidity are more pronounced than those in other studies.
Uijen et al. found a modest standardized increase of people with two or three chronic
conditions, but a more pronounced increase of people with four or more chronic diseases in the
Dutch population between 1995 and 2005 [
]. Another Dutch study [
] showed a modest
standardized increase of 2.7% over a 7-year period for people aged 75 years and older, while a
Swedish study [
] found stable prevalence rates of multiple severe symptoms/diseases among
older people (over 77 years of age) between 2002 and 2011. However, these latter numbers
were generated using self-reported diseases.
The rising prevalence of multimorbidity can be considered in the light of several factors.
They include medical developments, such as improved diagnostics and better treatments,
resulting in more frequent cures of acute diseases and less frequent or less serious adverse
events, and hence longer survival after both acute and chronic illness. Other relevant global
factors include the end of large-scale wars and the extreme improvement of living conditions
The more pronounced increase of multimorbidity among people aged under 50 years in the
second half of the study might be the result of increasingly efficient coding of diseases. For
patients aged over 50 this effect would be smaller and hence not result in a significantly
different trend, because many of them already were over the threshold of two chronic conditions.
The prevalence rates of polypharmacy found in our study were comparable to other studies
from Western societies. The latter reported prevalence rates of polypharmacy between 27%
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Fig 3. Evolution of the age- and sex-standardised and crude prevalence rates of polypharmacy ( 5 drugs) from 2000?2015.
and 59% in primary care patients aged 65 years and older [
] or community-dwelling elderly
of the same age living in the USA [
]. A recent study from the UK reported the proportion of
adults with polypharmacy had doubled to 20.8% between 1995 and 2000 [
]. We know that
our database might have an under-registration of prescribed medication: medication
prescribed by medical hospital specialists as well as medication prescribed during home visits
might be incomplete [
The plateau in the polypharmacy trend for females 75 years, might be related to a relative
increase in new young GPs in this period, who do less home consultations which compared to
their older GP-colleagues.
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Strengths and limitations
The analyses for this study were performed using a large database; for 2015, we had
information on over 150,000 individual patients. In 2014, the estimated practice population in the
Intego database represented 2.3% of the Flemish-Belgian population. Moreover, the Intego
population is representative of the Flemish-Belgian population in terms of age and sex [
General practices have to pass three quality criteria before being accepted as participants in
]. This results in a reliable morbidity database containing routinely collected data in
primary care, representing daily clinical practice. External validation of the Intego database
has been examined by means of national and international comparisons [
previous analyses have shown that the registration of medication is not always complete [
may result in an underestimation of polypharmacy rates, but we do not expect this to affect the
Implications for clinical practice
Primary care for patients with multimorbidity and polypharmacy is complex?both for patients
and health care professionals?and patients are prone to safety incidents [
]. It can be expected
that the trend will continue of an increasing number of patients having to deal with
multimorbidity and polypharmacy. This underlines the need for care innovations for this group of
complex patients. It is increasingly accepted that understanding and including patients? preferences
is of the utmost importance in optimising care for patients with multimorbidity [
to meet the patients? needs in case of multimorbidity are e.g. minimally disruptive medicine
] and the Ariadne principles, which offer guidance on how to handle multimorbidity in
primary care consultations . Both models acknowledge the importance of the patient?s role
as well as patient-physician communication in care. Taking care of patients with
multimorbidity requires GPs and other caregivers who are capable of delivering goal-oriented care for those
patients and proactive care for the prevention of chronic diseases.
Implications for future research and health policy
The epidemiology of chronic disease, multimorbidity and polypharmacy is dynamic. Reliable
and up-to-date analyses are necessary to guide health policy, physicians and medical guideline
9 / 12
development. Furthermore, the authors of care models focusing on patients with
multimorbidity give indications of how to use disease models or principles in daily practice, but the
training of doctors in the management of patients with multimorbidity seems to be hardly
]. The current evidence of interventions developed for the care of people with
multimorbidity and polypharmacy is ambiguous [
]. It is clear, however, that both
patients and health care professionals feel an urgent need for care coordination and
harmonization of treatments and other medical procedures, using interdisciplinary expertise and
patients? preferences and goal setting [
]. In order to reach better care for patients with
multimorbidity and polypharmacy, both concepts should be part of the educational
programmes for physicians, pharmacists and other health care workers to train interprofessional
For all adult age groups, multimorbidity and polypharmacy are frequent, dynamic over time
and increasing. This situation demands both epidemiological and interventional studies to
improve the management of the resulting complex care.
S1 Fig. Participation of practices during study period.
S1 Table. Number of people in the yearly contact group and the practice population in
Intego between 2000 and 2015.
S2 Table. list of chronic diseases.
S3 Table. Logistic regression (age groups considered as a continuous variable to test for
the trend), with multimorbidity in 2015 as the outcome.
Conceptualization: Marjan van den Akker, Bert Vaes, Geert Goderis, Gijs Van Pottelbergh.
Formal analysis: Se?verine Henrard.
Investigation: Marjan van den Akker, Gijs Van Pottelbergh.
Methodology: Marjan van den Akker, Bert Vaes, Se?verine Henrard.
Project administration: Tine De Burghgraeve.
Software: Se?verine Henrard.
Supervision: Bert Vaes.
Visualization: Tine De Burghgraeve, Se?verine Henrard.
Writing ? original draft: Marjan van den Akker.
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Writing ? review & editing: Bert Vaes, Geert Goderis, Gijs Van Pottelbergh, Tine De
Burghgraeve, Se?verine Henrard.
11 / 12
BMC medical informatics and decision making. 2014; 14:48. Epub 2014/06/08. https://doi.org/10.1186/
1472-6947-14-48 PMID: 24906941.
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