The economic costs of mental disorders: Do our societies react appropriately to the burden of mental disorders?

Abstract

In the EU, about 165 million people are affected each year by mental disorders, mostly anxiety, mood, and substance use disorders [1], [2]. Overall, more than 50% of the general population in middle‐ and high‐income countries will suffer from at least one mental disorder at some point in their lives. Mental disorders are therefore by no means limited to a small group of predisposed individuals but are a major public health problem with marked consequences for society. They are related to severe distress and functional impairment—these features are in fact mandatory diagnostic criteria—that can have dramatic consequences not only for those affected but also for their families and their social‐ and work‐related environments [3]. In 2010, mental and substance use disorders constituted 10.4% of the global burden of disease and were the leading cause of years lived with disability among all disease groups [2], [4]. Moreover, owing to demographic changes and longer life expectancy, the long‐term burden of mental disorders is even expected to increase [3].

> In 2010, mental and substance use disorders constituted 10.4% of the global burden of disease and were the leading cause of years lived with disability among all disease groups.

These consequences are not limited to patients and their social environment—they affect the entire social fabric, particularly through economic costs. An adequate estimation of these costs is complex and, owing to incomplete data, difficult to undertake. Moreover, studies on economic costs vary considerably due to deficiencies in the definitions of disorders; populations or samples studied; sources of costs and service utilization; analytical framework; and incomplete cost categories because of lack of data and definitions [5]. However, improved epidemiological and economic methods and models together with more complete epidemiological data during the past …

Full text

Low investments despite high costs:
Do our societies react appropriately to the burden of mental disorders?
Sebastian Trautmann, PhD1, Jürgen Rehm, PhD1,2 & Hans-Ulrich Wittchen, PhD1
1Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden,
Dresden, Germany
2Centre for Addiction and Mental Health, Toronto, Canada
Address of corresponding author
Dr. Sebastian Trautmann
Institute of Clinical Psychology and Psychotherapy
Chemnitzer Str. 46, 01187 Dresden, Germany
Phone: ++49-351-463-42464; Fax: ++49-351-463-36984
E-mail: Sebastian.Trautmann1@tu-dresden.de
In the EU, about 165 million people are affected each year by mental disorders, mostly
anxiety, mood and substance use disorders [1, 2]. Overall, more than 50% of the general
population in middle- and high-income countries will suffer from at least one mental disorder
at some point in their lives. Mental disorders are therefore by no means limited to a small
group of predisposed individuals but are a major public health problem with marked
consequences for society. They are related to severe distress and functional impairment –
these features are in fact mandatory diagnostic criteria – that can have dramatic consequences
not only for those affected but also for their families and their social- and work-related
environments [3]. In 2010, mental and substance use disorders constituted 10.4% of the global
burden of disease and were the leading cause of years lived with disability among all disease

groups [2, 4]. Moreover, owing to demographic changes and longer life expectancy, the long-
term burden of mental disorders is even expected to increase [3].
These consequences are not limited to patients and their social environment – they affect the
entire social fabric, particularly through economic costs. An adequate estimation of these
costs is complex and, owing to incomplete data, difficult to undertake. Moreover, studies on
economic costs vary considerably due to deficiencies in the definitions of disorders;
populations or samples studied; sources of costs and service utilization; analytical
framework; and incomplete cost categories because of lack of data and definitions [5].
However, improved epidemiological and economic methods and models together with more
complete epidemiological data during the past 20 years now allow the accumulation of
comprehensive and increasingly reliable data that give us a good idea about the magnitude of
the economic impact of mental disorders.
While most people think that medication, visits to a clinic or hospitalization are the true
economic burden of diseases, in reality the burden of disease – and mental disorders in
particular – goes far beyond these “direct” diagnostic and treatment costs. In the 2011 report
on the global economic burden of non-communicable diseases [6], the World Economic
Forum (WEF) described three different approaches used to quantify economic disease
burden, which do not only acknowledge the “hidden costs” of diseases, but also their impact
on economic growth at a macroeconomic level (Figure 1).
SUBHEADER: Human capital costs
The human capital approach, which is most commonly used to quantify the economic costs
of mental disorders and disease in general, distinguishes between direct and indirect costs.
Direct costs most often refer to the “visible costs” associated with diagnosis and treatment in
the health care system: medication, physician visits, psychotherapy sessions, hospitalization,
and so on. Indirect costs refer to the “invisible costs” associated with income losses due to
mortality, disability and care seeking, including lost production due to work absence or early
retirement [6, 7]. Two kinds of data are needed to calculate the direct and indirect cost of a
disorder: epidemiological data on the prevalence of the disorder, health care seeking,
associated mortality, disability, and in some cases imprisonment; and the per patient costs of
the disorder (economic data). The epidemiological data typically is based on representative

samples that report prevalence estimates in a defined population, and cohort studies, which
link the outcomes described above. Cost data are usually derived from routine statistics such
as the average cost of a hospital bed per night for acute or psychiatric hospitals, which are
then multiplied with the corresponding epidemiological data.
Based on data from 2010, the global direct and indirect economic costs of mental disorders
were estimated at US$2.5 trillion. Importantly, the indirect costs (US$1.7 trillion) are much
higher than the direct costs (US$0.8 trillion), which contrasts with other key disease groups,
such as cardiovascular diseases and cancer. For the EU, a region with highly developed
health care systems, the direct and indirect costs were estimated at €798 billion [7], with both
the direct and indirect costs of mental disorders expected to more than double by 2030
(Figure 2a). It should be noted that these calculations did not include costs associated with
mental disorders from outside the health care system, such as legal costs caused by illicit
drug abuse.
SUBHEADER: Lost economic growth
From a macroeconomic perspective, the cost of mental disorders in a defined population can
be quantified as lost economic output by estimating the projected impact of mental disorders
on the gross domestic product (GDP) (see Further Reading Box). The major idea behind this
approach is that economic growth depends on labor and capital, both of which can be
negatively influenced by disease. Capital is depleted by health care expenditures and labor is
depleted by disability and mortality [6]. Capital depletion is calculated from information on
saving rates, costs of treatment and the proportion of treatment costs that are funded from
savings. Impact on labor is estimated by comparing the GDP to a counterfactual scenario that
assumes no deaths from a disease against the projected deaths caused by the respective
disease. Such estimates of lost economic output are mostly calculated for somatic diseases,
and rarely for mental disorders. However, the impact of mental disorders on economic growth
can be estimated only indirectly [6]: the lost economic output is first calculated with somatic
diseases related to their associated number of disability-adjusted life years (DALYs). In a
second step, the lost economic output for mental disorders is projected using the relative size
of the corresponding DALYs for other diseases [6].
Between 2011 and 2030, the cumulative economic output loss associated with mental
disorders is thereby projected to total US$ 16.3 trillion worldwide, making the economic

output loss related to mental disorders comparable to that of cardiovascular diseases, and
higher than that of cancer, chronic respiratory diseases and diabetes (Figure 2b).
SUBHEADER: Value of statistical life
The broadest approach used for calculating the economic impact of mental disorders is the
value of statistical life (VSL) method (see Further Reading Box). This method assumes that
tradeoffs between risks and money can be used to quantify the risk of disability or death
associated with mental disorders. This quantification analyzes observed tradeoffs or
hypothetical preferences, such as data acquired from surveys that ask people how much they
would be willing to pay to avoid a particular risk, or how much money they would need to
take on that risk [6]. The VSL is then calculated from these subjective risk-value ratios. For
example, suppose that the average lifetime risk of dying from a depressive disorder is 15 in
1,000. Suppose further that there are measures that could reduce that risk to 5 in 1,000. If
people of a certain population are willing to spend on average US$50,000 for these measures,
VLS in that population would be US$5 million ($50,000$/[(15-5)/1,000]). The same logic
can also be applied when evaluating the willingness to monetarily pay in order to avoid
living with a certain disease. As a result, the VSL approach not only accounts for lost income
and out-of-pocket spending on information, medications and care, but also for costs that
people associate with disability and suffering.
Using the VSL, the global economic burden of mental disorders was estimated at US$8.5
trillion $ in 2010. Similar to the impact on economic growth, this estimate is comparable to
that of cardiovascular diseases and higher than that of cancer, chronic respiratory diseases
and diabetes. This economic burden is also expected to almost double until 2030 (Figure 2c).
In summary, mental disorders cause tremendous economic costs, directly via relatively low
costs in the health care system, and indirectly via proportionally high productivity losses and
impact on economic growth. This pattern of relatively low direct versus comparatively high
indirect costs is different from almost all other disease groups even though the full range of
mental disorders has barely been taken into account. Although the estimated size of economic
costs depend on the analytic approach, the available data from 2009 show that: the costs of
mental disorders can be estimated at US$2.5 trillion using a traditional human capital
approach, or US$ 8.5 trillion using a willingness to pay approach, making the total global
health spending in 2009 was approx. US$5 trillion [6]. Mental disorders therefore account for

more economic costs than chronic somatic diseases such as cancer or diabetes; and their costs
are expected to increase exponentially over the next 15 years.
SUBHEADER: Lack of action
The above summary on the global economic costs of mental disorders is corroborated by
numerous national studies and an EU-wide study by the European Brain Council [7]. How
were these studies received and did policy change the level of funding for prevention,
diagnosis and treatment? In the EU and globally, we do not see much of a response. Mental
and substance use disorders are often not part of current health coverage schemes [8]: even
though some of these schemes are labelled as “universal health care”, they exclude mental
and/or substance use disorders. This situation persists even though the respective health care
interventions on the population level, for instance, the availability of alcohol; the community
level, such as life skills training in schools; and the health care level are effective and can be
appropriately implemented (see Further Reading Box). Moreover, their implementation is
often cost-effective: the benefit to cost ratio of investments to increase treatment rates for
common mental disorders is between 2.3 and 5.7 to 1 (see Further Reading Box). However,
the treatment gap for mental and substance use disorders is higher than for any other health
sector. Access to mental health care is generally restricted owing to a lack of personnel and
infrastructure, and effective evidence-based treatments are not provided. Importantly, specific
prevention is almost completely lacking, with many high-income countries being no
exception (see Further Reading Box).
What are the reasons for these remarkable deficits and this evident lack of political
commitment to address the problem? First we have to acknowledge that the development and
implementation of sound and effective diagnostic and treatment measures for mental health is
still in its relative infancy; many evidence-based treatments and interventions have only
become available during the past 30 years. Thus, capacity building in terms of personnel,
infrastructure and other resources is still far behind other disease areas.
Beyond this, we speculate that stigmatization and misconceptions of both mental and
addictive disorders seem to play a major role. It is not only lay people who seem to believe
that mental and substance use disorders are not “real diseases”, that they cannot be treated
effectively and that people affected are at least partly responsible (see Further Reading Box).
As a consequence, societies are willing to spend much more on somatic diseases than on

mental disorders, even though both disability and economic costs caused by mental disorders
are at least as high as those caused by somatic conditions. An impressive example that
illustrates the current public opinion about the allocation of resources is a study by Schomerus
et al. [9]. Using a sample from Germany’s general population, adults were asked to name
three out of nine medical conditions for which they would prefer resources not to be cut
should general cutbacks within the health care budget become necessary (Figure 3). About
two thirds of respondents named cancer as the medical condition that should be spared from
cutbacks, followed by myocardial infarction, AIDS and diabetes. Only a small minority of
respondents named mental disorders, such as depression and schizophrenia.
Beyond the effects of public opinion, funding decisions in many societies are still based on
mortality and life expectancy, and while mental disorders indirectly contribute to a high level
of mortality (see Further Reading Box), they rarely appear on death certificates. Finally, it
does not seem to be well known that mental disorders disproportionally contribute to so called
high-cost users in our health care system (see Further Reading Box).
SUBHEADER: The need for change
For these reasons, without reconsideration of the cost of mental disorders, cost-benefits of
treatment and preventive interventions, and the need for a comprehensive change in
stigmatization, the current underfunding of mental health care is likely to persist. Although
examples of large-scale initiatives to improve this situation have started emerging [10], there
is still a very long way to go. Society, politicians and stakeholders have to be consistently and
persistently informed about the true burden of mental disorders, including the individual
burden, the full range of potential economic costs, and the effectiveness, the feasibility and
affordability of measures to reduce that burden in order for society to be more willing to come
to accept that spending money for preventing and treating mental disorders is a sustainable
investment.
CONFLICT OF INTEREST:
The authors declare that they have no conflict of interest.

REFERENCES
1. Kessler RC, Petukhova M, Sampson NA, Zaslavsky AM, Wittchen H-U (2012) Twelve-
month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in
the United States. Int J Methods Psychiatr Res 21: 169–184.
2. Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jonsson B, Olesen J,
Allgulander C, Alonso J, Faravelli C, et al. (2011) The size and burden of mental
disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol
21: 655–679.
3. Patel V, Chisholm D, Parikh R, Charlson FJ, Degenhardt L, Dua T, Ferrari AJ, Hyman SE,
Laxminarayan R, Levin C, et al. (2016) Global Priorities for Addressing the Burden of
Mental, Neurological, and Substance Use Disorders. In Patel V, Chisholm D, Dua T,
Laxminarayan R, Medina-Mora ME (eds.), Mental, Neurological, and Substance Use
Disorders pp 1–27. The World Bank, Washington, DC.
4. Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, Charlson FJ,
Norman RE, Flaxman AD, Johns N, et al. (2013) Global burden of disease attributable to
mental and substance use disorders: findings from the Global Burden of Disease Study
2010. Lancet 382: 1575–1586.
5. Hu T (2004) An International Review of the Economic Costs of Mental Illness. World
Bank Working Paper 31.
6. Bloom DE, Cafiero ET, Jané-Llopis E, Abrahams-Gessel S, Bloom LR, Fathima, S, Feigl
AB, Gaziano T, Mowafi M, Pandya A, et al. (2011) The Global Economic Burden of
Noncommunicable Diseases. World Economic Forum, Geneva.
7. Gustavsson A, Svensson M, Jacobi F, Allgulander C, Alonso J, Beghi E, Dodel R, Ekman
M, Faravelli C, Fratiglioni L, et al. (2011) Cost of disorders of the brain in Europe 2010.
Eur Neuropsychopharmacol 21: 718–779.
8. Chisholm D, Johansson KA, Reykar N, Megiddo I, Nigam A, Strand KB, Colson A,
Fekadu A, Verguet S (2016) Universal Health Coverage for Mental, Neurological, and
Substance Use Disorders: An Extended Cost-Effectiveness Analysis. In Patel V, Chisholm
D, Dua T, Laxminarayan R, Medina-Mora ME (eds.), Mental, Neurological, and
Substance Use Disorders pp 237–251. The World Bank, Washington, DC.
9. Schomerus G, Matschinger H, Angermeyer MC (2006) Alcoholism: Illness beliefs and
resource allocation preferences of the public. Drug Alcohol Depend 82: 204–210.

10. Haro JM, Luis Ayuso-Mateos J, Bitter I, Demotes-Mainard J, Leboyer M, Lewis SW,
Linszen D, Maj M, Mcdaid D, Meyer-Lindenberg A, et al. (2014) ROAMER: roadmap for
mental health research in Europe. Int J Methods Psychiatr Res 23: 1–14.

Further reading Box
Burden of diseases
Murray CJ, Barber RM, Foreman KJ, Ozgoren AA, Abd-Allah F, Abera SF, Aboyans V,
Abraham JP, Abubakar I, Abu-Raddad LJ, et al. (2015) Global, regional, and national
disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life
expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological
transition. The Lancet 386: 2145–2191.
Global Burden of Disease Study 2013 Collaborators (2015) Global, regional, and national
incidence, prevalence, and years lived with disability for 301 acute and chronic diseases
and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of
Disease Study 2013. The Lancet 386: 743–800.
Direct and indirect costs
Knapp M (2003) Hidden costs of mental illness. Br J Psychiatry 183: 477–478.
Impact on economic growth
Abegunde D, Stanciole A (2006) An estimation of the economic impact of chronic
noncommunicable diseases in selected countries. WHO Working Paper. World Health
Organization Department of Chronic Diseases and Health Promotion. Geneva.
The value of statistical life
Johansson P-O (2001) Is there a meaningful definition of the value of a statistical life? J
Health Econ 20: 131–139.
Treatment coverage
Kohn R, Saxena S, Levav I, Saraceno B (2004) The treatment gap in mental health care. Bull
World Health Organ 82: 858–866.
Stigmatization

Angermeyer MC, Matschinger H, Schomerus G (2013) Attitudes towards psychiatric
treatment and people with mental illness: changes over two decades. Br J Psychiatry 203:
146–151.
High costs users
Oliveira C de, Cheng J, Vigod S, Rehm J, Kurdyak P (2016) Patients With High Mental
Health Costs Incur Over 30 Percent More Costs Than Other High-Cost Patients. Health
Aff 35: 36–43.
Mortality
Nordentoft M, Wahlbeck K, Hällgren J, Westman J, Osby U, Alinaghizadeh H, Gissler M,
Laursen TM (2013) Excess mortality, causes of death and life expectancy in 270,770
patients with recent onset of mental disorders in Denmark, Finland and Sweden. PloS One
8: e55176.
Effective Interventions
Petersen I, Evans-Lacko S, Semrau M, et al. (2016) Population and Community Platform
Interventions. In Patel V, Chisholm D, Dua T, Laxminarayan R, Medina-Mora ME (eds.),
Mental, Neurological, and Substance Use Disorders pp 183-200. The World Bank,
Washington, DC.
Shidhaye R, Lund C, Chisholm D. (2016) Health Care Platform Interventions. In: Patel V,
Chisholm D, Dua T, Laxminarayan R, Medina-Mora ME (eds.) Mental, Neurological,
and Substance Use Disorders pp 201-18. The World Bank; Washington, DC.
Cost-benefit of treatment
Chisholm D, Sweeny K, Sheehan P, Rasmussen B, Smit F, Cuijpers P, Saxena S (2016)
Scaling-up treatment of depression and anxiety: a global return on investment analysis.
Lancet Psychiatry.

EU initiatives and recommendations
Wykes T, Haro JM, Belli SR, Obradors-Tarragó C, Arango C, Ayuso-Mateos JL, Bitter I,
Brunn M, Chevreul K, Demotes-Mainard J, et al. (2015) Mental health research priorities for
Europe. Lancet Psychiatry 2: 1036–1042.

Figure 1: Different approaches used to estimate economic costs of mental disorders

Figure 2a-c: Economic costs of mental disorders in trillion US$ using three different
approaches: Direct and indirect costs (a), impact on economic growth (b) and value of
statistical life (c). Based on data from [6].
(c)
(b)
(a)

Figure 3: Medical conditions for which resources should not to be cut in case of general
cutbacks within the health care budget (in %, multiple answers were possible). Based on data
from [9].