Trends and patterns of antidepressant use in children and adolescents from five western countries, 2005–2012

Abstract

Following the FDA black box warning in 2004, substantial reductions in antidepressant (ATD) use were observed within 2 years in children and adolescents in several countries. However, whether these reductions were sustained is not known. The objective of this study was to assess more recent trends in ATD use in youth (019 years) for the calendar years 2005/6–2012 using data extracted from regional or national databases of Denmark, Germany, the Netherlands, the United Kingdom (UK), and the United States (US). In a repeated cross-sectional design, the annual prevalence of ATD use was calculated and stratified by age, sex, and according to subclass and specific drug. Across the years, the prevalence of ATD use increased from 1.3% to 1.6% in the US data (+26.1%); 0.7% to 1.1% in the UK data (+54.4%); 0.6% to 1.0% in Denmark data (+60.5%); 0.5% to 0.6% in the Netherlands data (+17.6%); and 0.3% to 0.5% in Germany data (+49.2%). The relative growth was greatest for 1519 year olds in Denmark, Germany and UK cohorts, and for 1014 year olds in Netherlands and US cohorts. While SSRIs were the most commonly used ATDs, particularly in Denmark (81.8% of all ATDs), Germany and the UK still displayed notable proportions of tricyclic antidepressant use (23.0% and 19.5%, respectively). Despite the sudden decline in ATD use in the wake of government warnings, this trend did not persist, and by contrast, in recent years, ATD use in children and adolescents has increased substantially in youth cohorts from five Western countries. http://authors.elsevier.com/a/1Sgjf,L21DWJPv

Full text

Trends and patterns of antidepressant
use in children and adolescents from five
western countries, 2005–2012
Christian J. Bachmann
a,
n
, Lise Aagaard
b
, Mehmet Burcu
c
,
Gerd Glaeske
d
, Luuk J. Kalverdijk
e
, Irene Petersen
f
,
Catharina C.M. Schuiling-Veninga
g
, Linda Wijlaars
f,h
,
Julie M. Zito
c,i
, Falk Hoffmann
j
a
Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience,
King’s College London, London, United Kingdom
b
Institute of Public Health, Clinical Pharmacology, Faculty of Health Sciences, University of Southern
Denmark, Denmark
c
Department of Pharmaceutical Health Services Research, University of Maryland, Baltimore, MD, USA
d
Division of Health Economics, Health Policy and Health Services Research, Ce ntre for Social Po licy Research,
University of Bremen, Ge rmany
e
Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
f
Department of Primary Care and Population Health, University College London Medical School,
London, United Kingdom
g
Department of Pharmacoepidemiology and Pharmacoeconomics, University Centre of Pharmacy,
University Groningen, The Netherlands
h
Population, Policy and Practice, University College London Institute of Child Health, London,
United Kingdom
i
Department of Psychiatry, University of Maryland, Baltimore, MD, USA
j
Department of Health Services Research, Carl von Ossietzky University Oldenburg, Germany
Received 20 September 2015; received in revised form 15 January 2016; accepted 1 February 2016
KEYWORDS
Antidepressant
agents;
Adolescent;
Black box warning;
Child;
Multinational;
Prevalence trends
Abstract
Following the FDA black box warning in 2004, substantial reductions in antidepressant (ATD) use
were observed within 2 years in children and adolescents in several countries. However,
whether these reductions were sustained is not known. The objective of this study was to assess
more recent trends in ATD use in youth (0 19 years) for the calendar years 2005/6–2012 using
data extracted from regional or national databases of Denmark, Germany, the Netherlands, the
United Kingdom (UK), and the United States (US). In a repeated cross-sectional design, the
www.elsevier.com/locate/euroneuro
http://dx.doi.org/10.1016/j.euroneuro.2016.02.001
0924-977X/& 2016 Elsevier B.V. and ECNP. All rights reserved.
n
Correspondence to: Department of Child and Adolescent Psychiatry Institute of Psychiatry, Psychology & Neuroscience, King’s College
London, 16 De Crespigny Park, London SE5 8AF, United Kingdom.
E-mail address: chrstn.bchmnn@gmail.com (C.J. Bachmann).
European Neuropsychopharmacology (2016) 26, 411–419

annual prevalence of ATD use was calculated and stratified by age, sex, and according to
subclass and specific drug. Across the years, the prevalence of ATD use increased from 1.3% to
1.6% in the US data ( + 26.1%); 0.7% to 1.1% in the UK data (+ 54.4%); 0.6% to 1.0% in Denmark
data (+ 60.5%); 0.5% to 0.6% in the Netherlands data ( + 17.6%); and 0.3% to 0.5% in Germany
data (+ 49.2%). The relative growth was greatest for 15 19 year olds in Denmark, Germany and
UK cohorts, and for 10 14 year olds in Netherlands and US cohorts. While SSRIs were the most
commonly used ATDs, particularly in Denmark (81.8% of all ATDs), Germany and the UK still
displayed notable proportions of tricyclic antidepressant use (23.0% and 19.5%, respectively).
Despite the sudden decline in ATD use in the wake of government warnings, this trend did not
persist, and by contrast, in recent years, ATD use in children and adolescents has increased
substantially in youth cohorts from five Western countries.
& 2016 Elsevier B.V. and ECNP. All rights reserved.
1. Introduction
The safety of selective serotonin reuptake inhibitors (SSRIs)
for the treatment of depression in children and adolescents
has been a subject of much concern and debate (Brent,
2004; Friedman, 2014). In October 2004, the U.S. Food and
Drug Administration (FDA) issued a “black-box”, now
termed “boxed” warning, indicating an increased risk of
suicidal ideation/suicidal behavior in children and adoles-
cents treated with SSRIs (Friedman, 2014). This followed
similar action in the United Kingdom by the Medicines and
Healthcare Products Regulatory Agency (MHRA), and was
soon followed by similar warnings by other regulatory bodies
(e.g. European Medicines Agency (EMA) warning against the
use of SSRIs in youthso18 years, August 2005). Within
2 years after these warnings, the use of antidepressants
(ATDs) decreased markedly in children and adolescents in
Canada, the UK and the USA (Bergen et al., 2009; Busch and
Barry, 2009; Katz et al., 2008; Kurian et al., 2007 ; Olfson
et al., 2008). However, such decreases occurred mostly for
youth diagnosed with less severe depression while psy-
chotherapy use increased substantially (Valluri et al.,
2010). Whether diminished ATD use has persisted is
not known.
A decade after government warnings, the controversy
continues on the evidence for the risk of suicidal events
associated with ATD use in children and adolescents.
Notably, the majority of ATDs are not licensed in youth less
than 18 years of age, and thus are commonly prescribed
“off-label”. Considering the broader international context
in which there is a significant influence of cultural and
health system factors on psychotropic medication use in
general (Schomerus et al., 2014; Steinhausen, 2013), infor-
mation on how ATD use has evolved over recent years in
different countries is needed. While there are a few studies
assessing multinational patterns of psychotropic medication
use in youth (Zito et al., 2006 ), to date, there is no recent
multinational epidemiological data on trends in ATD use in
children and adolescents. Single country comparisons (Dörks
et al., 2013; Hoffmann et al., 2014; Pottegard et al., 2014;
Wijlaars et al., 2012; Zoega et al., 2009) are often
hampered by dissimilar study methods (e.g. different time-
spans or age groups). The objective of this study is to assess
more recent trends in ATD use in youth (0 19 years) using
data extracted from regional or national databases of
Denmark, Germany, the Netherlands, the United Kingdom
(UK), and the United States (US). We also assess patterns of
antidepressant use according to age group, sex, ATD sub-
class and entity.
2. Experimental procedures
2.1. Data sources
2.1.1. Denmark
To perform this study we used the Danish Registry of Medicinal
Products Statistics (RMPS). The registry is a national prescription
database on all outpatient pharmacy-dispensed prescription med-
ications in Denmark (5.53 million inhabitants) and is updated
monthly. Each prescription record contains detailed information
on the drug dispensed (incl. ATC code). With the use of an
estimation of the underlying population (denominator), the pre-
valence can be calculated.
2.1.2. Germany
We used claims data of the single largest German health insurance
company, the BARMER GEK (insuring about 9.1 million persons,
representing more than 10% of the German population). Although
there are several differences between the statutory insurance
system and private insurances, both provide full-coverage health
insurance. As compared to the entire German population, the
BARMER GEK insures a higher proportion of females, but there are
no differences regarding socioeconomic status (as measured by
education level) (Hoffmann and Bachmann, 2014). For each year, all
insurees who were insured at least 1 day in all four quarters were
included. Each prescription record contains detailed information on
the drugs dispensed including ATC code.
2.1.3. The Netherlands
This study was performed with pharmacy dispensing data from
IADB.nl (Visser et al., 2013). Dutch patients usually register at a
single community pharmacy, so a single pharmacy provides an
almost complete listing of each subject's prescribed drugs. The
database comprises all prescription drug dispensing data from 59
pharmacies since 1994 for about 600,000 persons in the northern
and eastern parts of the Netherlands. It includes all prescriptions,
regardless of prescriber, reimbursement status, or insurance. Over-
the-counter drugs and in-hospital prescriptions are not included.
The population in the database is representative of the whole Dutch
population (Visser et al., 2013).
C.J. Bachmann et al.412

2.1.4. United Kingdom
We used The Health Improvement Network (THIN) primary care
database, which contains information on prescriptions issued in
primary care in all four UK countries. Approximately 98% of the
population in the UK is registered with a general practitioner (GP),
with GPs issuing 93.4% of all ATD prescriptions dispensed by
community pharmacies in the UK (Health and Social Care
Information Centre, 2015). THIN is broadly representative of the
UK population in terms of demographics and consultation behavior
(Blak et al., 2011). We included only practices with good quality
data recording (Horsfall et al., 2013; Maguire et al., 2009). We
analyzed data from 2005 to 2012 and included 552 practices,
covering 6% of the UK population. Prescribing data in THIN has
been shown to reflect dispensed prescriptions with a mean practice
redemption rate for all prescribing of 98.5% in 2008 (NHS National
Information Centre, 2011). The redemption rate for antidepressants
was slightly lower (96.7%), although still high.
2.1.5. United States
For the United States (US) data, computerized Medicaid adminis-
trative claims for the calendar years 2006 through 2012 were
analyzed for a narrowly-defined population of youth (0–19 years)
enrolled in Children's Health Insurance Program (CHIP) in a mid-
Atlantic state. Such youth are eligible for Medicaid coverage due to
family income (upper limit is three-times the federal poverty level;
The Henry J Kaiser Family Foundation (2015)) and are similar to
privately-insured youth in the US with respect to age distribution,
race and family composition, and general health status, with
moderately lower parental education, employment, and income
(Byck, 2000). Each youth was assigned an encrypted identification
number, which was then used to link the enrollment data files to
prescription drug claim files. Youth who were not continuously
enrolled in the CHIP program in a given year were excluded from
the analyses in that year.
2.2. Data analysis
Annual prevalence was defined as the percent of youth (0–19 years)
with one or more dispensings for antidepressant medication among
continuously enrolled youths in a given calendar year in the 2005/6–
2012 period. The data extracted from the above-mentioned data-
bases are presented as total prevalence per 100 youths and
stratified according to age groups [0 4, 5 9, 10  14, 15 19
years (Zito et al., 2006)], and gender. In addition, among
antidepressant-treated youths, we compared the proportional dis-
tribution of antidepressant subclasses [SSRI (e.g. fluoxetine, parox-
etine), TCA (e.g. imipramine, amitriptyline), other (e.g. mirta-
zapine, duloxetine, St John's wort)] between 2005/6 and 2012
separately for each country.
2.3. Ethical approval
2.3.1. United Kingdom
The CSD Medical Research Scientific Review Committee approved
this study in February 2015 (reference number 14-086). The scheme
for THIN to obtain and provide anonymous patient data to
researchers was approved by the National Health Service South-
East Multicentre Research Ethics Committee in 2002.
2.3.2. USA
The study related to the US data was reviewed and approved by the
Institutional Review Board of the University of Maryland, Baltimore.
2.3.3. Denmark, Germany and The Netherlands
According to the respective national regulations, ethical approval
was not necessary for this study.
3. Results
In 2012, the number of youths receiving ATD per studied
population of youths between 0  19 years were as follows:
Germany: 6849/1,414,623, Denmark: 11,774/1,203,817,
Netherlands: 790/131,954, United Kingdom: 8680/827,906,
and United States: 1667/105,188.
Across seven years from 2005/6 through 2012 (Figure 1), the
annual prevalence of ATD use for children and adolescents
increased in all studied cohorts as follows: USA cohort: 1.3% to
1.6% (+ 26.1%), UK cohort: 0.7% to 1.1% ( + 54.4%), Denmark
cohort: 0.6% to 1.0% ( + 60.5%), Netherlands cohort: 0.5% to
0.6% (+ 17.6%), and Germany cohort: 0.3% to 0.5% ( + 49.2%).
Cross-national differences in ATD use were up to 2.1-fold in
2005 and up to 3.3-fold in 2012.
The prevalence of ATD use stratified by sex is provided in
Table 1, showing a female preponderance in ATD use
throughout all years and all countries, with the exception
of the USA in 2006. Across countries, female/male ratios in
ATD use ranged from 1.7 to 2.3 in 2005 and from 1.1 to
2.4 in 2012.
The ATD use was most common among 15–19 year olds,
ranging from 0.8% to 2.4% in 2005/6, and from 1.4% to 6.2%
in 2012 (Table 2). There was a consistent linear relation
between age and the prevalence of ATD medication use.
When looking at the trends in ATD use by age group from
2005/6–2012, ATD use increased most markedly in 15–19
year olds and in 10–14 year olds (Table 2). Time trends in the
age group 0–4 years were not calculated, as the number of
children in this age group was very small (Nr 10 in most
databases in 2012).
Concerning subclasses, both in 2005 and 2012, in most
countries, the majority of ATD use was for SSRIs, with
Denmark leading in SSRI use (81.8% of all ATD prescriptions
in 2012) (Figure 2). The only exception was Germany, where
in 2005 tricyclic antidepressant (TCA) prescriptions margin-
ally outnumbered SSRI prescriptions (39.6% vs. 37.7%). In
2012, this trend had inverted, but the percentage of TCA
prescriptions to children and adolescents in Germany
(23.0%) and also in the UK (19.5%) was still notable.
The entities most frequently prescribed differed mark-
edly between countries (Table 3). While citalopram was first
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2005 2006 2007 2008 2009 2010 2011 2012
Prevalence in percent
DK
DE
NL
UK
USA
Figure 1 Percent prevalence of antidepressant use in children
and adolescents (0–19 years) in youth cohorts from five
countries, 2005–2012.
Annotation: DE= Germany, DK= Denmark, NL= Netherlands, UK=
United Kingdom, USA= United States of America.
413Trends and patterns of antidepressant use in children and adolescents

Table 1 Percent prevalence of antidepressant medication use for children and adolescents (0–19 years) in youth cohorts from five countries, by sex, 2005– 2012 (numbers in brackets = 95%
confidence interval).
2005
a
2006 2007 2008 2009 2010 2011 2012 Difference
2005–2012
M F F/M
ratio
TMFTMFTMFTMFTMFTMFTMFF/M
ratio
T Trend p-
Value
Denmark 0.40
[0.38–
0.41]
0.83
[0.81–
0.86]
2.11 0.61
[0.60–
0.62]
0.45
[0.44–
0.47]
0.95
[0.92–
0.97]
0.69
[0.68–
0.71]
0.51
[0.49–
0.52]
1.07
[1.05–
1.10]
0.78
[0.77–
0.80]
0.55
[0.53–
0.57]
1.19
[1.17–
1.22]
0.86
[0.85–
0.88]
0.62
[0.60–
0.64]
1.31
[1.28–
1.34]
0.96
[0.94–
0.98]
0.69
[0.67–
0.72]
1.51
[1.48–
1.54]
1.09
[1.07–
1.11]
0.67
[0.65–
0.70]
1.42
[1.39–
1.46]
1.04
[1.02–
1.06]
0.62
[0.60–
0.64]
1.35
[1.32–
1.38]
2.17 0.98
[0.96–
1.00]
+ 60.5% o.0001
Germany 0.24
[0.23–
0.25]
0.41
[0.39–
0.42]
1.65 0.32
[0.32–
0.33]
0.23
[0.22–
0.24]
0.39
[0.37–
0.40]
0.31
[0.30–
0.32]
0.26
[0.25–
0.27]
0.43
[0.42–
0.45]
0.35
[0.34–
0.36]
0.28
[0.27–
0.30]
0.47
[0.45–
0.49]
0.37
[0.36–
0.38]
0.30
[0.29–
0.32]
0.49
[0.48–
0.51]
0.40
[0.39–
0.41]
0.33
[0.32–
0.35]
0.55
[0.53–
0.57]
0.44
[0.43–
0.45]
0.35
[0.34–
0.36]
0.61
[0.59–
0.63]
0.48
[0.46–
0.49]
0.35
[0.34–
0.36]
0.63
[0.61–
0.64]
1.79 0.48
[0.47–
0.50]
+ 49.2% o.0001
Netherlands 0.37
[0.33–
0.42]
0.65
[0.59–
0.72]
1.76 0.51
[0.47–
0.55]
0.32
[0.28–
0.36]
0.64
[0.58–
0.71]
0.48
[0.44–
0.52]
0.33
[0.29–
0.38]
0.64
[0.58–
0.70]
0.48
[0.45–
0.52]
0.37
[0.33–
0.42]
0.69
[0.63–
0.76]
0.53
[0.49–
0.57]
0.36
[0.32–
0.41]
0.60
[0.54–
0.66]
0.48
[0.44–
0.52]
0.34
[0.30–
0.39]
0.64
[0.59–
0.71]
0.49
[0.46–
0.53]
0.41
[0.36–
0.46]
0.73
[0.66–
0.80]
0.57
[0.53–
0.61]
0.46
[0.41–
0.52]
0.74
[0.67–
0.81]
1.59 0.60
[0.56–
0.64]
+ 17.6% o.0001
UK 0.41
[0.39–
0.43]
0.96
[0.93–
0.99]
2.34 0.68
[0.66–
0.70]
0.40
[0.38–
0.42]
0.94
[0.91–
0.97]
0.66
[0.64–
0.68]
0.42
[0.40–
0.44]
1.02
[0.99–
1.05]
0.71
[0.69–
0.73]
0.43
[0.41–
0.45]
1.04
[1.01–
1.07]
0.73
[0.71–
0.75]
0.47
[0.45–
0.49]
1.14
[1.11–
1.17]
0.80
[0.78–
0.82]
0.54
[0.52–
0.57]
1.32
[1.28–
1.35]
0.93
[0.91–
0.95]
0.59
[0.57–
0.61]
1.42
[1.38–
1.45]
1.00
[0.98–
1.02]
0.63
[0.60–
0.65]
1.47
[1.43–
1.51]
2.35 1.05
[1.03–
1.07]
+ 54.4% o.0001
US N/A N/A 0.90
b
N/A 1.32
[1.23–
1.41]
1.19
[1.11–
1.28]
1.26
[1.20–
1.32]
1.34
[1.26–
1.43]
1.19
[1.11–
1.27]
1.27
[1.21–
1.33]
1.26
[1.18–
1.35]
1.28
[1.19–
1.37]
1.27
[1.21–
1.33]
1.41
[1.32–
1.51]
1.38
[1.28–
1.48]
1.40
[1.33–
1.46]
1.40
[1.30–
1.50]
1.45
[1.35–
1.55]
1.42
[1.35–
1.50]
1.52
[1.42–
1.63]
1.54
[1.44–
1.65]
1.53
[1.46–
1.61]
1.52
[1.42–
1.62]
1.65
[1.55–
1.77]
1.09 1.58
[1.51–
1.66]
+ 26.1% o.0001
Annotation: F= Females, M= Males, T = Total.
a
For the US, only data from 2006–2012 were available.
b
Ratio from 2006 data.
C.J. Bachmann et al.414

Table 2 Percent prevalence of antidepressant medication use from 2005–2012, by age group in youth cohorts from five countries (numbers in brackets= 95% confidence
interval).
2005 2006 2007 2008 2009 2010 2011 2012 Difference
2005
a
–2012
Denmark
0–4 years 0.01 [0.00–0.01] 0.00 [0.00–0.01] 0.01 [0.00–0.01] 0.01 [0.00–0.01] 0.01 [0.00–0.01] 0.01 [0.00–0.01] 0.01 [0.00–0.01] 0.01 [0.01–0.01] N/A
b
5–9 years 0.05 [0.04–0.05] 0.05 [0.04–0.06] 0.05 [0.04–0.06] 0.05 [0.05–0.06] 0.06 [0.05–0.07] 0.06 [0.05–0.07] 0.06 [0.05–0.07] 0.05 [0.04–0.06] + 4.6%
10–14 years 0.34 [0.32–0.36] 0.38 [0.35–0.40] 0.39 [0.37–0.41] 0.41 [0.39–0.44] 0.44 [0.42–0.46] 0.49 [0.47–0.52] 0.46 [0.44–0.49] 0.46 [0.44–0.49] + 34.9%
15–19 years 2.20 [2.15–2.26] 2.47 [2.41–2.53] 2.77 [2.71–2.83] 2.99 [2.93–3.05] 3.28 [3.21–3.34] 3.67 [3.60–3.73] 3.46 [3.39–3.52] 3.19 [3.13–3.26] + 45.1%
Germany
0–4 years 0.02 [0.01–0.02] 0.01 [0.01–0.02] 0.01 [0.01–0.01] 0.01 [0.01–0.01] 0.01 [0.00–0.01] 0.01 [0.00–0.01] 0.00 [0.00–0.01] 0.00 [0.00–0.01] N/A
b
5–9 years 0.10 [0.09–0.11] 0.10 [0.09–0.11] 0.10 [0.09–0.11] 0.07 [0.06–0.08] 0.07 [0.06–0.07] 0.06 [0.06–0.07] 0.05 [0.04–0.06] 0.04 [0.03–0.05]  60.6%
10–14 years 0.20 [0.18–0.21] 0.18 [0.17–0.20] 0.20 [0.19–0.22] 0.20 [0.19–0.22] 0.20 [0.19–0.22] 0.19 [0.18–0.21] 0.20 [0.18–0.21] 0.21 [0.19–0.22] + 5.3%
15–19 years 0.83 [0.80–0.85] 0.78 [0.76–0.81] 0.89 [0.87–0.92] 1.01 [0.98–1.04] 1.10 [1.07–1.14] 1.28 [1.24–1.31] 1.40 [1.36–1.41] 1.41 [1.38–1.45] + 71.0%
Netherlands
0–4 years 0.01 [0.00–0.03] 0.01 [0.00–0.03] 0.01 [0.00–0.03] 0.01 [0.00–0.02] 0.01 [0.00–0.03] 0.02 [0.01–0.04] 0.02 [0.01–0.04] 0.01 [0.00–0.03] N/A
b
5–9 years 0.07 [0.05–0.11] 0.05 [0.03–0.08] 0.07 [0.05–0.11] 0.07 [0.04–0.10] 0.05 [0.03–0.08] 0.09 [0.06–0.13] 0.11 [0.08–0.15] 0.09 [0.06–0.13] + 22.8%
10–14 years 0.34 [0.28–0.41] 0.34 [0.28–0.41] 0.26 [0.21–0.32] 0.30 [0.24–0.37] 0.32 [0.26–0.39] 0.33 [0.27–0.40] 0.40 [0.33–0.47] 0.48 [0.41–0.56] + 41.5%
15–19 years 1.59 [1.46–1.72] 1.53 [1.41–1.67] 1.52 [1.40–1.65] 1.65 [1.53–1.79] 1.43 [1.32–1.56] 1.43 [1.32–1.56] 1.62 [1.49–1.75] 1.68 [1.55–1.82] + 5.8%
UK
0–4 years 0.00 [0.00–0.01] 0.00 [0.00–0.01] 0.00 [0.00–0.01] 0.00 [0.00–0.00] 0.00 [0.00–0.00] 0.00 [0.00–0.00] 0.00 [0.00–0.00] 0.00 [0.00–0.01] N/A
b
5–9 years 0.06 [0.05–0.07] 0.05 [0.04–0.06] 0.04 [0.04–0.05] 0.04 [0.04–0.05] 0.05 [0.04–0.06] 0.04 [0.03–0.05] 0.04 [0.03–0.05] 0.03 [0.03–0.04]  40.5%
10–14 years 0.21 [0.19–0.23] 0.18 [0.16–0.20] 0.19 [0.17–0.21] 0.22 [0.21–0.24] 0.22 [0.20–0.24] 0.22 [0.20–0.24] 0.27 [0.25–0.29] 0.31 [0.29–0.33] + 46.3%
15–19 years 2.37 [2.31–2.44] 2.33 [2.27–2.40] 2.45 [2.38–2.51] 2.45 [2.39–2.51] 2.66 [2.60–2.72] 3.03 [2.96–3.10] 3.19 [3.12–3.26] 3.19 [3.12–3.26] + 34.8%
US
a
0–4 years N/A 0.04 [0.03–0.06] 0.05 [0.04–0.07] 0.04 [0.02–0.05] 0.03 [0.02–0.05] 0.03 [0.02–0.05] 0.01 [0.01–0.03] 0.02 [0.01–0.04] N/A
b
5–9 years N/A 1.20 [1.07–1.35] 1.17 [1.04–1.31] 0.99 [0.87–1.12] 1.05 [0.92–1.19] 0.96 [0.84–1.10] 0.90 [0.78–1.03] 0.88 [0.76–1.01]  27.1%
10–14 years N/A 3.49 [3.25–3.75] 3.48 [3.24–3.74] 3.39 [3.15–3.64] 3.57 [3.32–3.84] 3.45 [3.20–3.72] 3.55 [3.30–3.81] 3.50 [3.25–3.75] + 0,0%
15–19 years N/A 5.35 [4.94–5.79] 5.36 [4.96–5.78] 5.86 [5.44–6.29] 5.93 [5.50–6.38] 5.82 [5.38–6.28] 6.08 [5.64–6.54] 6.24 [5.81–6.70] + 16.7%
a
For the US, only data from 2006–2012 were available.
b
Because of the small numbers of patients, difference in antidepressant use across time was not computed.
415Trends and patterns of antidepressant use in children and adolescents

choice in Denmark and in the Netherlands, fluoxetine was
most frequently prescribed in Germany and in the UK, and
sertraline was the top ranking ATD in the US. In 2012, in the
UK, Germany and the Netherlands, TCAs (amitriptyline,
opipramol) were still among the top five prescribed entities.
4. Discussion
The major findings of this study are as follows: 1) From
2005/6 through 2012, the prevalence of ATD use in children
and adolescents increased substantially in cohorts from five
Western countries, with both absolute and relative
increases being most pronounced in the UK and in Denmark.
2) Regarding age groups, the relative growth was greatest
for 15  19 year olds in Denmark, Germany and UK cohorts,
and for 10 14 year olds in Netherlands and US cohorts. 3)
While SSRIs were the most commonly used antidepressant
subclass, youth cohorts from Germany and the UK still
displayed notable proportions of tricyclic antidepressant
use (23.0% and 19.5%, respectively).
The current trend in ATD use is in line with international
prescription trends for other psychotropic classes in chil-
dren and adolescents, e.g. antipsychotics or ADHD drugs,
which show even greater increased rates (Bachmann et al.,
2014; Dalsgaard et al., 2013; Olfson et al., 2012; Rapoport,
2013; Ronsley et al., 2013). The reasons for this increase in
antidepressant use are not completely clear. An increase of
depressive disorders or other conditions demanding treat-
ment with ATDs as a reason for the increase in ATD
prescriptions can be largely ruled out, as there is substantial
evidence that there has been no significant increase in the
rates of children's mental health conditions in Western
countries over recent years in studies of German and British
youth (Hölling et al., 2014; Sellers et al., 2015). Never-
theless, there is some evidence of an increase in child and
adolescent mental health service use, potentially indicating
under-treatment in previous years (Breland et al., 2014;
Steinhausen and Bisgaard, 2014).
Although there have been no substantial changes in
clinical guidelines that would have extended indications
for ATD prescriptions, in day-to-day practice there has been
a marked trend towards a broadening of indications by
prescribers. In terms of psychiatric and behavioral treat-
ments, the growth of comorbidities (Kessler et al., 2009)as
well as the increased trend for “not otherwise specified”
diagnostic categories, may contribute to expanded medica-
tion use (Safer et al., 2015). In the study of Dörks et al.
(2013) on ATD utilization in German children and adoles-
cents, more than one third of ATDs were prescribed off-
label for indications such as migraine, somatoform disor-
ders, personality disorders, sleeping problems and develop-
mental disorders, and in the US study of Lee et al. (2012),
only 9.2% of ATDs were prescribed according to indication.
Another potential reason for the increase in ATD use may be
the preference for pharmacotherapy because of the limited
availability of psychotherapy services or because of
patients' and clinicians' expectations of reaching treatment
goals faster with ATD use (Correll et al., 2013). Moreover,
the increased ATD use may also be related to an increased
marketing of ATD by pharmaceutical companies (Kesselheim
et al., 2011; Kondro and Sibbald, 2004). Such marketing
strategies have been demonstrated to be effective in
influencing prescribers' preferences (Larkin et al., 2014).
Finally, as Taylor, (2013) argues, the rise in ATD use may be
addressing previous under-treatment of child psychiatric
disorders. Nevertheless, the findings from this study cannot
address questions of overuse or underuse of ATDs in children
and adolescents. Further research is warranted on outcomes
of community treatment populations to assure effective,
appropriate, and quality care.
The greater proportion of ATD use in females compared
with males is consistent with prior
findings (Zito et al.,
2006) and with the gender-specific incidence of depression
in youth (Merikangas et al., 2009). Concerning age groups,
the current findings show that the proportional growth in
ATD use occurred mostly for older youth (10  19 year olds),
whereas younger aged children showed minimal changes or
sustained drops in ATD use. The marked rise of ATD use in
adolescents is a finding consistent with the majority of
recent studies on other psychotropic medication use in
children and adolescents (Acquaviva et al., 2009;
Bachmann et al., 2014; Kalverdijk et al., 2008; Meng
et al., 2014; Pottegard et al., 2014; Steinhausen, 2015;
Steinhausen and Bisgaard, 2014). In the current study, SSRIs
were the most commonly used antidepressant subclass in all
five Western countries. However, Germany and the UK
displayed notable proportions of tricyclic antidepressant
use in 2012. The continuing use of tricyclic antidepressants
in youth contrasts with the long-standing negative findings
on effectiveness (Hazell and Mirzaie, 2013). Regarding the
most commonly prescribed substances, there were several
antidepressants among the “top five” which have no
approval for use in children or adolescents in the respective
country (e.g. amitriptyline in Germany and the Netherlands,
bupropion in the UK) or for which no trial evidence on safety
or effectiveness in minors is available (e.g. opipramol, St
John's worth). These “off-label” prescription practices in
minors might reflect an extrapolation of ATD prescription
patterns in adults. The true rates of off-label use might
even be higher, as our data did not contain information
whether licensed ATDs were prescribed for the correspond-
ing indications.
0
10
20
30
40
50
60
70
80
90
DK DE NL UK USA
Percentage of total antidepresant use
TCA 2005
TCA 2012
SSRI 2005
SSRI 2012
Figure 2 Trends in antidepressant medication use in children
and adolescents (0–19 years) in youth cohorts from five
countries for tricyclic antidepressants and selective serotonin
reuptake inhibitors (2005 vs. 2012).
Annotation: DE = Germany, DK= Denmark, NL = The Nether-
lands, SSRI= Selective Serotonin Reuptake Inhibitors, TCA= Tri-
cyclic antidepressants, UK= United Kingdom, USA = United
States of America.
C.J. Bachmann et al.416

Among factors that may vary by country are formulary
differences, differences in reimbursement, availability of
alternative non-pharmacological treatments for emotional
and behavioral disorders, clinical guidelines and indications
for use, e.g. imipramine for nocturnal enuresis. Cultural
attitudes toward the use of psychotropic drugs vary by
country. For example, Schomerus et al. (2014) found that US
patients embrace psychotropic medications more readily
than Germans.
The main limitation of this study is the diversity of the
underlying databases in terms of several factors, e.g.
representativeness of the full population, prescribing phy-
sician specialty (GPs vs. specialists) and socio-economic
status (von Soest et al., 2012). These differences in data
sources also hamper the inter-country comparability of
data. An example for this is the UK database, which
contains only GPs' prescriptions. Thus, it lacks prescriptions
issued by (child and adolescent) psychiatrists, which might
lead to an underestimation of ATD prescription rates.
However, as prescriptions are often initiated by psychia-
trists and then continued by GPs, GPs' prescribing patterns
probably reflect fairly completely ATD prescription trends in
children and adolescents originally seen by psychiatrists.
Nevertheless, as the databases also reflect the differ-
ences of the respective national health systems (including
e.g. prescribing restrictions), the comparability of prescrip-
tion data between countries will never be completely
harmonized. Therefore, the individual countries' relative
prescription trends reported in our study are probably a
more robust feature than absolute prescription rates.
Moreover, we did not have information on factors that
may influence ATD prescribing to children and adolescents
such as the underlying indication, co-medication, ethnic
background (Wittkampf et al., 2010), foster care status
(Fontanella et al., 2011, 2014), adequacy of dosage, dura-
tion of pharmacotherapy, adherence, symptom severity and
symptom duration. Also, we did not consider medication
bought over-the-counter (mainly St John's wort).
In conclusion, despite the sudden decline in ATD use in
the wake of government warnings, the trend did not persist,
and by contrast, across recent years, ATD use in children
and adolescents has increased substantially in youth cohorts
in five Western countries. While it is not clear whether this
trend reflects overuse or underuse of ATDs in youth, further
assessment is warranted. The findings support the need for
outcomes research in community-treated populations, and,
in the policy arena, for the development of harmonized
international clinical guidelines.
Role of funding source
No funding was secured for this study.
Contributors
Dr. Bachmann conceptualized and designed the study, drafted the
initial manuscript, and approved the final manuscript as submitted.
Prof. Aagard acquired, analyzed and interpreted data, revised the
manuscript critically, and approved the final manuscript as sub-
mitted. Mehmet Burcu acquired, analyzed and interpreted data,
revised the manuscript critically, and approved the final manuscript
as submitted. Prof. Glaeske acquired, analyzed and interpre-
Table 3 The top 5 antidepressant entities in children and adolescents (0–19 years) in youth cohorts from five countries (2005 vs. 2012), as a percentage of total
antidepressant use.
Rank Denmark Germany Netherlands UK US
2005 % 2012 % 2005 % 2012 % 2005 % 2012 % 2005 % 2012 % 2006
a
% 2012 %
1 CIT 33.5 CIT 40.9 FLX 12.2 FLX 24.3 CIT 28.8 CIT 33.8 FLX 35.2 FLX 31.7 SER 20.6 SER 27.5
2 VEN 11.2 SER 16.8 SJW 11.0 CIT 15.7 PAR 15.6 FLX 16.6 CIT 19.3 CIT 29.2 FLX 20.5 FLX 21.9
3 SER 11.1 VEN 14.7 OPI 10.0 OPI 7.6 VEN 14.6 AMI 8.2 AMI 14.5 AMI 16.4 ESC 14.5 ESC 10.9
4 MIR 10.0 MIR 10.0 CIT 9.4 MIR 7.3 FLX 13.2 ESC 7.1 SER 7.2 SER 14.0 BUP 10.0 CIT 8.9
5 ESC 9.5 ESC 7.9 IMI 8.1 AMI 5.5 FLV 7.0 MIR 6.4 ESC 6.6 MIR 3.1 TRA 9.0 TRA 8.2
Annotation: AMI= Amitriptyline, BUP= Bupropion, CIT= Citalopram, ESC = Escitalopram, FLX= Fluoxetine, FLV = Fluvoxamine, IMI= Imipramine, MIR= Mirtazapine, OPI = Opipramol,
PAR = Paroxetine, SER= Sertraline, SJW= St John's Wort, TRA= Trazodone, VEN= Venlafaxine.
a
For the US, only data from 2006–2012 were available.
417Trends and patterns of antidepressant use in children and adolescents

ted data, revised the manuscript critically, and approved the final
manuscript as submitted. Dr. Kalverdijk acquired, analyzed
and interpreted data, revised the manuscript critically, and
approved the final manuscript as submitted. Dr. Petersen acquired,
analyzed and interpreted data, revised the manuscript critically,
and approved the final manuscript as submitted. Dr. Schuiling-
Veninga acquired, analyzed and interpreted data, revised the
manuscript critically, and approved the final manuscript as sub-
mitted. Dr. Wijlaars acquired, analyzed and interpreted data,
revised the manuscript critically, and approved the final manuscript
as submitted. Prof. Zito acquired, analyzed and interpreted data,
revised the manuscript critically, and approved the final manuscript
as submitted. Prof. Hoffmann conceptualized and designed the
study, undertook the statistical analysis, drafted the initial manu-
script, and approved the final manuscript as submitted. All authors
mentioned above agree to be accountable for all aspects of
the work.
Conflict of interest
Christian Bachmann has received lecture fees from Actelion,
Novartis, and Ferring as well as payment from BARMER GEK and
from AOK for writing book chapters. He has served as a study
physician in clinical trials for Shire and Novartis. Gerd Glaeske and
Falk Hoffmann are active on behalf of a number of statutory health-
insurance companies (BARMER GEK, DAK, TK, and various corporate
health-insurance funds) in the setting of contracts for third-party
payment. Lise Aagaard has received traveling grants from Pfizer and
Swedish Orphan BioVitrum. Luuk J. Kalverdijk has received lecture
fees from Eli-Lilly, Janssen-Cilag and Shire and has served as a study
physician in clinical trials of Eli-Lilly. Catharina Schuiling-Veninga,
Irene Petersen, Linda Wijlaars, Julie M. Zito and Mehmet Burcu
declare no conflict of interest.
Acknowledgments
The authors are grateful to the insurance funds, databases and
government agencies that provided the data on antidepressant use.
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