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RESEARCH ARTICLE
Association of psychotropic drug use with
falls among older adults in Germany.
Results of the German Health Interview and
Examination Survey for Adults 2008-2011
(DEGS1)
Yong Du*, Ingrid-Katharina Wolf, Hildtraud Knopf
Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin Germany
Abstract
Purpose
To investigate the association of psychotropic drug use with falls among older adults in Ger-
many based on data from the National Health Interview and Examination Survey for Adults
2008–2011 (DEGS1).
Methods
DEGS1 collected data on drug use in the past 7 days and on falls occurred in the last 12
months. Study participants were older adults aged 65–79 years with complete data on drug
use and falls (N = 1,833). Odds ratio (OR) and 95% confidence intervals (95% CI) were
derived from logistic regression models adjusting for potential confounders including socio-
demographic characteristics, health-related behaviors (alcohol drinking), body mass index
and health conditions (frailty, vision impairment, disability, polypharmacy, blood pressure)
as well as use of potential falls-risk-increasing drugs. SPSS complex sample methods were
used for statistical analysis.
Results
Compared to people without falls, people with falls (n = 370) had a higher psychotropic drug
use (33.1% vs. 20.7%, p < .001). After adjusting for potential confounders, use of psychotro- pic drugs overall was associated with a higher risk of falls (OR 1.64, 95% CI 1.14–2.37).
This was particularly true for the use of synthetic psychotropic drugs (1.57, 1.08–2.28), anti-
depressants overall (2.88, 1.63–5.09) or synthetic antidepressants (2.66, 1.50–4.73), spe-
cifically, selective serotonin reuptake inhibitors (SSRIs) (6.22, 2.28–17.0). Similar results
were found for recurrent falls.
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 1 / 15
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OPEN ACCESS
Citation: Du Y, Wolf I-K, Knopf H (2017)
Association of psychotropic drug use with
falls among older adults in Germany. Results of the
German Health Interview and Examination Survey
for Adults 2008-2011 (DEGS1). PLoS ONE 12(8):
e0182432. https://doi.org/10.1371/journal.
pone.0182432
Editor: Alessandra Marengoni, University of
Brescia, ITALY
Received: February 27, 2017
Accepted: July 18, 2017
Published: August 8, 2017
Copyright: © 2017 Du et al. This is an open access article distributed under the terms of the Creative
Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in
any medium, provided the original author and
source are credited.
Data Availability Statement: The authors confirm
that some access restrictions apply to the data
underlying the findings. The data set cannot be
made publicly available because informed consent
from study participants did not cover public
deposition of data. However, the minimal data set
underlying the findings is archived in the ’Health
Monitoring’ Research Data Centre at the Robert
Koch Institute (RKI) and can be accessed by all
interested researchers. On-site access to the data
set is possible at the Secure Data Center of the
Conclusions
Use of psychotropic drugs overall, especially synthetic antidepressants like SSRIs, is asso-
ciated with higher risks of falls and recurrent falls among community dwelling older adults
aged 65–79 years in Germany.
Introduction
As one of the major health problems, falls occur commonly and frequently among older adults
with one third of adults aged > = 65 years falling at least once in a given year [1, 2]. Major con-
sequences of falls for individuals include physical injuries and fractures leading to functional
decline, disability and decreased quality of life. To society, falls impose high financial burdens
and healthcare costs due to fall-caused hospitalization and mortality [3, 4]. In the EU approxi-
mately 2.3 million and in the US 2.8 million fall-related injuries are admitted to emergencies
while 36,000 adults in the EU and 27,000 older adults in the US are reported to have died from
falls each year [2, 5]. The health care expenditure for treating fall-related injuries is estimated
to be €25 billion in the EU [5] and $31 billion in the US [6]. In addition, many older adults are afraid of falling, which may result in psychological consequences such as mental stress, depres-
sion or anxiety [7].
Falls among older adults are largely preventable by identifying and controlling particularly
modifiable risk factors [4, 8, 9]. Use of psychotropic drugs has been identified as an indepen-
dent risk factor for falls in various studies including systematic reviews and meta-analyses
[10–14]. Yet, most of previous studies on psychotropic drug use and falls considered only some
of the important health conditions associated with falls such as vision impairment [15, 16],
frailty [17], polypharmacy [18], use of potential fall risk-increasing drugs [12, 19] and disability
[20]. Results of these studies may be confounded by unmeasured factors. So far, few studies
investigating the association between falls and psychotropic drug use have controlled for these
factors.
Fall-related injuries among older adults increase along with an aging population [21, 22].
Germany is currently the second oldest population in the world, with 20.9% of the population
aged 65 years or over (n = 16.9 million) [23]. About 40% of women and 30% of men aged
65–90 years in Germany report any falls in the past 12 months [24]. Every one in five German
adults aged 60–79 years used at least one psychotropic drug in the last 7 days [25]. Since psy-
chotropic drug use is potentially a modifiable factor, further exploring the association of the
use of psychotropic drugs, particularly specific subgroups of interest, with falls may provide
insight into the prevention strategies of falls among older adults.
Population-based epidemiological studies on the association between psychotropic drug
use and falls are lacking in Germany. Based on data of the most recent German Health Inter-
view and Examination Survey for Adults (DEGS1) conducted in 2008–2011, we investigate the
use of overall psychotropic drugs, major subgroups of psychotropic drugs as well as specific
drugs of interest in relation to any falls and repeated falls after controlling for important health
conditions and other factors that are likely to be associated with falls.
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 2 / 15
RKI’s ’Health Monitoring’ Research Data Centre.
Requests should be submitted to the ’Health
Monitoring’ Research Data Centre, Robert Koch
Institute, Berlin, Germany (e-mail: [email protected]).
Funding: This work was supported by the Federal
Ministry of Health (https://www.
bundesgesundheitsministerium.de/) and the
Robert Koch Institute (www.rki.de/). The German
Health Interview and Examination Survey for Adults
2008-2011 was funded by the Federal Ministry of
Health. The funders had no role in study design,
data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
Methods
Data source: German Health Interview and Examination Survey for
Adults 2008–2011 (DEGS1)
The German Health Interview and Examination Survey for Adults, wave 1 (DEGS1) was car-
ried out by the Robert Koch Institute from November 2008 to December 2011 with the aim
to provide representative data on the health of adults aged 18–79 years living in Germany
[26, 27]. Details of study design, sampling strategy and protocol have been published previ-
ously [26, 27]. In Brief, DEGS1 used a two-stage random sampling procedure. First, 180 repre-
sentative communities (primary sample units, PSU) were randomly sampled from a complete
list of German communities proportional to community size. Second, age and sex stratified
random samples were drawn within PSUs from local population registries. DEGS1 had a com-
plex design. On one side, DEGS1 invited all surviving participants of the German National
Health Interview and Examination Survey 1998 (GNHIES98) in order to establish a survey
panel component. On the other side, DEGS1 also recruited new participants in order to main-
tain a nationally representative sample at the population level [26]. The response rate was 64%
for 28–79 year-old re-participants from GNHIES98 (n = 3795) and 42% for newly recruited
18–79 year-old participants (n = 4,192) [26, 27]. Of 3,795 re-participants, 2,923 persons,
together with all newly recruited (n = 4,192), completed both the interview and examination
survey parts, amounting to a nationally population-representative sample of adults aged 18–79
years (N = 7,115) [26, 27].
DEGS1 was approved by the Federal and State Commissioners for Data Protection and the
Charité-Universitätsmedizin Berlin ethics committee (No. EA2/047/08). Survey participants
provided written informed consent prior to interviews and examinations.
Data collection, study population and definition of study variables
Data collection in DEGS1 included self-administered questionnaires, standardized health pro-
fessional administered computer-assisted personal interviews (CAPI), physiological measure-
ments and laboratory tests [26].
Primary outcome: Falls and recurrent falls. In DEGS1, data of falls were collected only
among participants 65 years and older. We asked: “Within the past 12 months, have you fallen, stumbled or slipped, so that you became unbalanced and, as a result, rested on the floor or lower surface?” Those who answered with ‘Yes’ were defined as people with falls. Among people with falls, we further asked how many times the falls occurred. Those who answered 2 times or
more were defined as people with recurrent falls [24].
Primary independent variable: Psychotropic drug use. As part of CAPI, detailed infor-
mation on drug use (such as daily doses, routes of application and duration of use) in the past
7 days prior to the medical interview was recorded by trained health professionals [28]. In the
invitation letter, participants were asked to bring the original packages of all medications used
during the past seven days–prescribed and Over-The-Counter (OTC) products- to the exami-
nation site for the purpose of documentation and verification. This permitted automated
recording of unique product identifiers and drug coding according to the WHO “Anatomical
Therapeutic Chemical” (ATC) classification system [28]. Definition of psychotropic drugs has
been published previously [25, 29]. Briefly, we included drugs belonging to the nervous system
class (ATC code N00) as well as opiates used as antitussives (ATC code R05DA) and aspirin-
caffeine combination preparations (ATC code N02BA71) [25, 29] (Appendix Table 1a). We
excluded other analgesics and antipyretics such as aspirin and paracetamol (ATC code N02B),
local anesthetics (ATC code N01B), homeopathic drugs, and drugs with indistinct active
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 3 / 15
Table 1. Descriptive characteristics of study population. German national health interview and examination survey 2008–2011 (DEGS1).
Total (N = 1833) People with falls (n = 370) People without falls (n = 1463) p
%* 95% CI* n %* 95% CI* n %* 95% CI* n
Sex Men 46.0 43.5 48.4 911 34.2 28.6 40.3 142 49.0 46.1 52.0 769 .000
Women 54.0 51.6 56.5 922 65.8 59.7 71.4 228 51.0 48.0 53.9 694
Age group 65–69 34.8 32.3 37.5 736 31.4 25.9 37.4 139 35.7 32.9 38.7 597 .212
70–74 42.8 39.9 45.9 744 42.4 35.8 49.2 146 43.0 39.7 46.3 598
75–79 22.3 19.8 25.1 353 26.2 21.0 32.3 85 21.3 18.6 24.3 268
Living alone Yes 23.0 20.4 25.9 395 32.0 25.5 39.3 98 20.7 18.1 23.5 297 .001
No 77.0 74.1 79.6 1434 68.0 60.7 74.5 271 79.3 76.5 81.9 1163
Community size Rural towns 15.6 10.4 22.6 301 14.3 8.7 22.6 55 15.9 10.7 23.0 246 .404
Small cities 26.4 19.6 34.5 430 24.4 17.1 33.6 73 26.9 19.9 35.3 357
Middle cities 27.8 21.2 35.5 546 27.0 19.6 36.0 113 28.0 21.2 36.0 433
Large cities 30.3 23.3 38.3 556 34.3 25.9 43.7 129 29.2 22.2 37.4 427
Region of residence Eastern 23.0 17.3 30.0 621 23.1 16.4 31.6 119 23.0 17.2 30.1 502 .138
Northern 15.8 10.4 23.3 236 14.3 8.9 22.3 47 16.2 10.6 23.9 189
Central 34.5 27.1 42.8 567 39.7 30.8 49.4 123 33.2 25.8 41.5 444
Southern 26.7 19.9 34.7 409 22.8 15.8 31.8 81 27.7 20.5 36.2 328
Social status Lower 26.0 22.6 29.8 345 24.4 18.1 32.0 66 26.5 22.8 30.5 279 .767
Middle 59.4 55.8 62.9 1105 61.4 54.2 68.1 221 58.9 54.7 62.9 884
Upper 14.6 12.5 16.9 376 14.2 10.7 18.7 80 14.7 12.4 17.3 296
Body mass index, kg/m 2 <25 20.3 18.2 22.6 400 20.0 15.3 25.8 83 20.4 17.9 23.0 317 .215
25–30 44.0 41.2 46.9 823 39.5 33.6 45.8 146 45.2 41.9 48.5 677
> = 30 35.7 32.7 38.8 592 40.5 34.2 47.1 139 34.4 31.0 38.0 453 Recognized disability Yes 28.3 25.2 31.6 463 40.6 33.9 47.7 127 25.0 21.8 28.6 336 .000
No 71.7 68.4 74.8 1322 59.4 52.3 66.1 238 75.0 71.4 78.2 1084
Polypharmacy Yes 35.0 32.4 37.7 641 39.2 33.2 45.5 152 33.9 31.0 36.9 489 .115
No 65.0 62.3 67.6 1192 60.8 54.5 66.8 218 66.1 63.1 69.0 974
Daily drinking Yes 18.1 15.7 20.8 348 14.9 10.6 20.4 63 19.0 16.3 22.0 285 .163
No 81.9 79.2 84.3 1381 85.1 79.6 89.4 287 81.0 78.0 83.7 1094
Vision impairment No 77.9 75.2 80.5 1393 75.2 68.4 81.0 269 78.6 75.3 81.6 1124 .179
Slight 18.2 15.8 20.9 290 18.5 13.5 24.8 61 18.1 15.4 21.2 229
Severe 3.9 2.8 5.3 66 6.3 3.4 11.2 19 3.3 2.2 4.7 47
Frailty No 58.6 55.7 61.5 1129 52.8 45.8 59.6 201 60.2 56.7 63.5 928 .019
Pre-Frailty 38.9 36.0 41.9 649 42.5 35.7 49.6 149 38.0 34.7 41.4 500
Frailty 2.5 1.7 3.5 43 4.7 2.7 8.1 17 1.9 1.2 3.0 26
Continuous variables Mean* 95% CI* n Mean* 95% CI* n Mean* 95% CI* n
SBP, mm Hg 130.3 129.2 131.5 1828 128.1 125.9 130.3 367 130.9 129.7 132.1 1461 .015
DBP, mm Hg 72.8 72.2 73.5 1828 71.2 70.0 72.4 367 73.3 72.5 74.0 1461 .003
*Weighted and standardized to the population of 31.12.2010. P values: Comparison between people with falls and without falls.
Community size: Rural towns (<5,000 inhabitants), small cities (5,000-<20,000 inhabitants), middle-sized cities (20,000-<100,000 inhabitants) and large cities (100,000 inhabitants or more)
Region of residence: Eastern Germany (Berlin, Brandenburg, Mecklenburg-Vorpommern, Sachsen, Sachsen-Anhalt and Thüringen); Northern Germany
(federal states: Bremen, Hamburg, Niedersachsen and Schleswig-Holstein); Central Germany (Hessen, Nordrhein-Westfalen, Rheinland-Pfalz and
Saarland); Southern Germany (Baden-Württemberg and Bayern).
Missing values: Living alone (n = 4), social status (n = 7), recognized disability (n = 48), vision impairment (n = 84), daily drinking (n = 104), frailty (n = 12).
https://doi.org/10.1371/journal.pone.0182432.t001
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 4 / 15
ingredients under the ATC class N00 [25, 29]. Psychotropic drugs with herbal active ingredi-
ents were considered and coded separately under specific subgroups (S1 Table).
For the present analyses, individuals aged 65–79 years with complete data on falls and psy-
chotropic drug use were included as the study population (N = 1,833) (Table 1).
Covariables. A number of covariables that are likely to be associated with falls were inves-
tigated in this study. This included socio-demographic characteristics (age, sex, community
size, region of residence, individual information on household size–namely number of persons
living in a household-, income, profession and educational attainment), health-related behav-
iors, and dietary habits such as alcohol consumption. Information on socio-demographic char-
acteristics, health-related behavior and dietary habits were collected by self-administered
questionnaires. Community size was classified as rural towns, small cities, middle-sized cities
and large cities based on population density according to an established German classification
system. Regions of residence were grouped into 4 commonly described geographical areas:
Northern Germany (federal states: Bremen, Hamburg, Niedersachsen and Schleswig-Holstein); Central Germany (Hessen, Nordrhein-Westfalen, Rheinland-Pfalz and Saarland); Southern Germany (Baden-Württemberg and Bayern); Eastern Germany (Berlin, Brandenburg, Mecklen- burg-Vorpommern, Sachsen, Sachsen-Anhalt and Thüringen). According to the number of per- sons living in a household, living alone was defined if only one single person was reported in a
household. Socio-economic status (SES) was classified as ‘lower’, ‘middle’ and ‘upper’ using an
established index including information on education, professional status and household
income [30].
Daily alcohol drinking was assumed if survey participants reported drinking any alcohol-
containing beverages at least once a day in the past 12 months [25]. Body mass index (BMI)
was calculated as the ratio of body weight (kg) and body height (m) squared and categorized
into <25 kg/m 2 , 25–29.9 kg/m
2 and > = 30 kg/m
2 . Several health conditions were considered
in the present analysis based on findings of previous studies: Frailty [17], vision impairment
[15, 16], disability [20], polypharmacy [14, 18, 31] and systolic blood pressure (SBP) [32].
Frailty was defined as having 3 and more of the following criteria: Exhaustion, low weight, low
physical activity, low walking speed and low grip strength while pre-frailty was defined as hav-
ing 1–2 of these components [33]. Survey participants were asked if they had any difficulties
either in reading printed newspaper or in identifying the face of a person 4 meters away, using
glasses or any other reading aid if necessary. Possible answer choices for the question were: (1)
can read without difficulty, (2) can read with some difficulty, (3) can read with great difficulty
and (4) unable to read at all. Participants in categories ‘3’ or ‘4’ were defined as experiencing
‘severe vision impairment’ and ‘2’ as experiencing ‘some vision impairment’. People were also
asked if they had an officially certified disability (yes/no). Further, polypharmacy was assumed
if five or more prescription medicines were used in the past 7 days. Three standardized blood
pressure (BP) measurements were taken at three minutes intervals in upright sitting with an
oscillometric device (Datascope Accutorr Plus). The mean of the second and third measures
for systolic BP (SBP) and diastolic BP (DBP) was adopted [34].
A number of drugs have been reported to have the potential to increase the risks of falls
(potential fall risk-increasing drugs) [19, 35]. Based on drug use data collected in DEGS1, we
considered the major groups of potential falls risk-increasing drugs, namely antihypertensive
medications (ATC code C02 antihypertensive, C03 diuretics, C07 beta-adrenergic antagonists,
C08 calcium channel blockers and C09 agents acting on the renin-angiotensin system) [36],
anti-diabetes medications (ATC code: A10) [19], nonsteroidal anti-inflammatory drugs
(NSAIDS) (M01A, M02AA and N02BA) such as aspirin, ibuprofen and naproxen etc. [12, 37],
statins (C10AA & C10BA) [38] and thyroid therapy medications (H03) [19].
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 5 / 15
Statistical analyses
All statistical analyses were performed using SPSS statistical software (version 20.0, SPSS Inc.
Chicago, IL). In order to adjust for sample clustering effects, the SPSS complex samples mod-
ule was used. Sampling weights were used to correct deviations in the sample from the struc-
ture of the German general population of the 31st December 2010 [27].
Participants’ characteristics were summarized by people with falls and without falls in the
past 12 months. Differences between people with and without falls were examined using sec-
ond-order Rao-Scott chi-square tests for categorical variables and using General Linear Mod-
els (CSGLM) for continuous variables.
We fitted several logistic models with falls or recurrent fall events in the past 12 months as
dependent variables and use of psychotropic drugs as the primary independent variable adjust-
ing risk factors of falls. Model 1 was adjusted for sex and age group. Model 2 was additionally
adjusted for social status, community size, region of residence and living alone. Based on
model 2, model 3 was further adjusted for health behaviors including daily alcohol drinking,
BMI and health conditions including frailty, polypharmacy, disability, vision impairment and
SBP. Based on model 3, model 4 was further adjusted for the use of potential falls-risk-increas-
ing dugs including antihypertensives, antidiabetic medications, NSAIDS, statins and thyroid
therapy medications. For each of these models, we first looked at the use of overall psychotro-
pic drugs, all synthetic psychotropic drugs and phyto-medicines, and then the use of major
subgroups of psychotropic drugs as well as specific drugs or drug classes of interest.
A total of 246 or 13.4% of study participants had missing observations in some variables
with a range of 0.2% for living alone, 2.6% for recognized disability, 4.6% for vision
impairment, to 5.7% for daily drinking. The numbers of persons with missing values were
explicitly stated for each variable (Table 1). Persons with missing values were excluded from
the analyses, with pairwise deletion for descriptive and listwise deletion for multivariable anal-
yses (i.e. multivariable models were restricted to participants with valid data on all model cov-
ariables). Statistical significance was defined at p<0.05 based on two-sided tests.
Results
Table 1 shows the descriptive characteristics of the study population stratified by people with
and without falls in the past 12 months. Of 1,833 older adults, approximately 20% lived alone
or drank daily; more than one third had a BMI > = 30 kg/m 2
or used polypharmacy; about
40% had frailty or pre-frailty and 22% had a severe or slight vision impairment. 370 older
adults reported any falls with a weighted prevalence of 20.7% (95% CI 18.7–23.0%). Of 370
people with falls, 149 (40.3%) reported repeated falls (data not shown in Table 1). Compared
to people without falls, people with falls were more likely to be female, to live alone, and to
have a recognized disability and a lower average SBP/DBP (Table 1). In addition, they had a
higher proportion of frailty and pre-frailty (Table 1). No difference was found between people
with and without falls in regard to the distribution of age group, community size, region of res-
idence, social status, BMI, using polypharmacy, daily drinking and vision impairment
(Table 1).
Table 2 shows the prevalence for the use of psychotropic drugs as well as potential falls risk-
increasing drugs among people with and without falls. People with falls had overall a higher
psychotropic drug use compared to people without falls (33.1% vs. 20.7%, p < .001). The same
is true for the use of any synthetics (25.1% vs. 16.2%) and phyto-medicines (12.1% vs. 6.3%) as
well as the subgroups of anti-depressants, -both synthetic antidepressants (Non-Selective
Monoamino Reuptake Inhibitors, NSMRIs and Selective Serotonin Reuptake Inhibitors,
SSRIs) and St. John’s wort-, and antidementia drugs (mainly Ginkgo biloba) (Table 2). No
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 6 / 15
difference was found between people with and without falls concerning the use of antihyper-
tensives, anti-diabetes medications and statins. Yet, people with falls had a higher use for
NSAIDs and thyroid therapy medicines (Table 2).
In logistic regression models adjusting for age and sex, use of overall psychotropic drugs
and of synthetic psychotropic drugs was associated with falls, but this did not apply to the use
of phytomedicines (Table 3). Further adjusting for confounders included in model 2, model 3
and model 4, the association remains robust (Table 3). The risk of any falls was 64% higher
among psychotropic drug users compared to nonusers. In terms of major subgroups of psy-
chotropic drugs, use of antidepressants overall increased the risk of falls significantly after
considering all potential confounders (OR 2.88, 95% CI 1.63–5.09). Use of synthetic
Table 2. Prevalence of psychotropic drug use and potential falls-risk-increasing drug use among older adults with and without falls. German
national health interview and examination survey 2008–2011 (DEGS1).
People with falls (n = 370) People without falls (n = 1463)
% 95%CI n % 95%CI n p
Psychotropic drugs
Any psychotropic drugs (Synthetics & phytomedicines**) 33.1 27.4 39.2 113 20.7 18.0 23.7 300 .000
Any synthetic psychotropic drugs 25.1 19.9 31.3 89 16.2 13.6 19.1 231 .001
Any phytomedicines 12.1 7.8 18.1 33 6.3 4.9 8.0 93 .016
Any anti-depressants (St. John’s wort and synthetical antidepressants) 15.3 10.8 21.2 46 6.1 4.6 8.1 77 .000
St. John’s wort (N05CP03/N06AP01/51( 2.3 .8 6.1 5 .5 .2 1.0 9 .010
Any synthetical antidepressants 13.0 8.8 18.6 41 5.8 4.3 7.7 71 .001
NSMRIs(N06AA) 7.0 3.8 12.6 21 3.1 2.1 4.8 36 .019
SSRIs (N06AB) 4.3 2.4 7.6 14 1.3 .8 2.2 19 .002
Any hypnotics & sedatives (synth., antihistamine and phytoceuticals) 4.3 2.4 7.5 19 3.7 2.7 5.1 62 .660
Any synthetics. (N05C) and antihistamine (N05CM) 2.4 1.1 5.1 11 1.7 1.1 2.6 33 .493
Any synthetics (N05C) 2.4 1.1 5.1 11 1.3 .8 2.1 25 .207
Valerian (N05CP01/51) 1.8 .7 4.4 7 1.6 1.0 2.6 27 .887
Any benzodiazepines (N05BA, N05CD, N03AE01) 4.0 1.8 8.6 12 2.9 1.9 4.4 37 .485
Benzodiazepine-related drugs (N05CF) 5.2 2.7 9.5 20 3.7 2.6 5.4 52 .366
Narcotic analgesics (N02A) 6.6 4.1 10.5 23 4.1 3.0 5.6 61 .087
Any anti-dementia drugs (N06DA and Ginkgo biloba) 8.3 4.7 14.2 24 4.2 3.1 5.7 59 .046
Ginkgo biloba (N06DP01) 8.0 4.4 14.0 21 3.9 2.9 5.3 55 .037
Anti-epileptics (N03) 2.6 1.3 5.0 13 1.9 1.0 3.3 30 .448
Antiparkinson drugs (N04) 2.5 1.1 5.5 9 1.4 .7 2.6 21 .203
Potential falls-risk-increasing dugs
Any antihypertensives (ATC-Code C02, C03, C07, C08, C09) 65.5 59.1 71.4 246 68.9 65.8 71.8 984 .307
Anti-diabetes medications (A10) 17.0 12.6 22.5 58 13.6 11.3 16.3 196 .193
NSAIDs (M01A, M02AA and N02BA) 29.1 23.9 34.9 107 19.0 16.1 22.2 260 .000
Statins (C10AA & C10BA) 25.4 20.6 30.8 106 27.0 24.3 29.8 399 .596
Thyroid therapy (H02) 24.2 18.6 30.9 86 17.6 14.9 20.6 253 .031
* Weighted and standardized to the population of 31.12.2010.
P-values: Comparison between people with falls and people without falls
**Phytomedicines: St. John’s wort (N06AP), Ginkgo biloba (N06DP01), Valerian (N05CP).
Figures in bold denote statistical significance (p < .050) NSMRIs: Non-Selective Monoamino Reuptake Inhibitors
SSRIs: Selective Serotonin Reuptake Inhibitors
NSAIDs: Nonsteroidal Anti-Inflammatory Drugs (M01A, M02AA and N02BA)
https://doi.org/10.1371/journal.pone.0182432.t002
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 7 / 15
antidepressants (2.66, 1.50–4.73), but not St. John’s wort was associated with any falls. Specifi-
cally, use of SSRIs (6.22, 2.28–17.0), but not non-selective monoamine reuptake inhibitors
(NSMRIs) increased the risk of any falls (Table 3). For the use of other psychotropic drugs, no
significantly increased risks were found (Table 3).
As with falls, use of overall psychotropic drugs was also associated with recurrent falls
(adjusted OR 1.84, 95% CI 1.02–3.31) (Table 4). The odds ratios for the relationship between
recurrent falls and the use of overall antidepressants, synthetic antidepressants, such as SSRIs,
were consistently significant (p<0.05) in all 4 models. The odds ratios for narcotic analgesics
(N02A) and anti-Parkinson drugs (N04) were found to be significant in model 1 and model 2,
but not in model 3 and model 4 (Table 4).
Sensitivity analyses involved limiting to those who had used any psychotropic drugs over 12
months and results were similar. In the fully adjusted Model 4, the OR for any psychotropic
drug use over 12 months was 1.70 (95% CI 1.10–2.63) for any falls and 2.10 (95% CI 1.04–
4.22) for recurrent falls; the OR for any synthetic drug use over 12 months was 1.89 (95% CI
1.21–2.94) for any falls and 1.92 (95% CI 1.11–3.34) for recurrent falls (data not shown in
Tables 3 and 4).
Table 3. Association of psychotropic drug use with risks of falls. German national health interview and examination survey 2008–2011 (DEGS1).
Model 1 Model 2 Model 3 Model 4
OR 95%CI OR 95%CI OR 95%CI OR 95%CI
Any psychotropic drugs (Synthetics & phytomedicines) 1.69 1.24 2.31 1.68 1.23 2.29 1.64 1.14 2.35 1.64 1.14 2.37
Any synthetic psychotropic drugs 1.58 1.12 2.24 1.61 1.14 2.29 1.52 1.05 2.21 1.57 1.08 2.28
Any phytomedicines 1.76 0.98 3.19 1.62 0.91 2.89 1.66 0.84 3.29 1.62 0.82 3.19
Any anti-depressants (St. John’s wort and synthetical antidepressants) 2.39 1.43 4.01 2.33 1.39 3.90 2.69 1.50 4.83 2.88 1.63 5.09
St. John’s wort (N05CP03/N06AP01/51( 4.36 1.30 14.6 4.66 1.21 18.0 4.22 0.62 28.9 3.71 0.64 21.6
Any synthetical antidepressants 2.10 1.21 3.62 2.01 1.16 3.47 2.43 1.36 4.34 2.66 1.50 4.73
NSMRIs(N06AA) 1.95 0.89 4.24 1.72 0.80 3.68 1.75 0.77 4.01 1.84 0.83 4.10
SSRIs (N06AB) 2.97 1.31 6.74 3.18 1.34 7.56 5.46 1.96 15.2 6.22 2.28 17.0
Any hypnotics & sedatives (synth., antihistamine and phytoceuticals) 0.99 0.49 2.00 1.05 0.52 2.13 0.88 0.42 1.83 0.79 0.37 1.71 Any synth. (N05C) and antihistamine (N05CM) 1.27 0.53 3.03 1.30 0.53 3.18 0.67 0.28 1.61 0.58 0.22 1.49
Any benzodiazepines (N05BA, N05CD, N03AE01) 1.20 0.47 3.07 1.22 0.48 3.14 0.90 0.24 3.39 0.90 0.25 3.28
Benzodiazepines and benzodiazepine-related drugs (N05CF) 1.22 0.57 2.60 1.24 0.58 2.66 0.89 0.32 2.44 0.85 0.31 2.32
Narcotic analgesics (N02A) 1.52 0.84 2.72 1.58 0.87 2.88 1.39 0.68 2.84 1.48 0.70 3.12
Any anti-dementia drugs (N06DA+ Ginkgo biloba) 1.81 0.90 3.68 1.53 0.78 3.03 1.60 0.71 3.64 1.57 0.69 3.60
Ginkgo biloba (N06DP01) 1.87 0.91 3.85 1.56 0.77 3.14 1.64 0.71 3.77 1.61 0.69 3.74
Anti-epileptics (N03) 1.58 0.62 3.98 1.76 0.75 4.17 1.36 0.51 3.61 1.47 0.58 3.73
Antiparkinson drugs (N04) 1.76 0.70 4.40 1.80 0.70 4.65 1.12 0.31 4.08 1.08 0.26 4.55
Valerian (N05CP01/51) 0.73 0.26 2.05 0.79 0.28 2.21 0.96 0.33 2.77 0.90 0.31 2.61
Odds ratio (OR) and 95% confidence intervals (95% CI) were derived from logistic regression models.
Model 1: adjusted for sex and age group (65–69, 70–74, 75–79 years)
Model 2: model 1+social status (lower, middle, upper), community size (rural area, small, middle and large city), region (East, north, central, south), living
alone (yes, no),
Model 3: Model 2+ frailty (frailty, pre-frailty, no frailty), polypharmacy (yes, no), disability (yes, no), vision impairment (severe, slight, no), daily alcohol
drinking (yes, no), BMI <25, 25–30, > = 30), SBP (continuous variables) Model 4: Model 3+antihypertensives, antidiabetics, nonsteroidal anti-inflammatory drugs (NSAIDs), statins, thyroid therapy (yes, no)
NSMRIs: non-selective monoamino reuptake inhibitors
SSRIs: Selective serotonin reuptake inhibitors
Figures in bold denote statistical significance (p < .050)
https://doi.org/10.1371/journal.pone.0182432.t003
Association of psychotropic drug use with falls among older adults in Germany
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Discussion
Main findings
In the present study, we found that the use of psychotropic drugs overall was associated with
increased risks of falls and recurrent falls in the past 12 months among community-dwelling
adults aged 65–79 years in Germany. This is particularly true for the use of synthetic psycho-
tropic drugs, mainly synthetic antidepressants, -specifically SSRIs. Our study confirms the
association between psychotropic drug use and falls and adds evidence for an increased risk
of falls following the use of psychotropic drugs overall and specific subgroups among
community-dwelling older adults.
Comparison with other studies
The association between psychotropic drug use and falls has been investigated in previous
studies and systematically reviewed or meta-analyzed [10–14]. An earlier meta-analysis cover-
ing studies published between 1966–1996 examining the association of drug use with falling in
Table 4. Association of psychotropic drug use and risk of recurrent falls. German national health interview and examination survey 2008–2011
(DEGS1).
Model 1 Model 2 Model 3 Model 4
OR 95%CI OR 95%CI OR 95%CI OR 95%CI
Any psychotropic drugs (Synthetics & phytomedicines) 1.97 1.27 3.05 1.96 1.25 3.08 1.83 0.99 3.35 1.84 1.02 3.31
Any synthetics 1.65 1.04 2.64 1.70 1.05 2.75 1.30 0.77 2.20 1.38 0.83 2.29
Any phytomedicines 1.60 0.74 3.44 1.44 0.64 3.24 1.76 0.58 5.35 1.69 0.57 5.00
Any anti-depressants (St. John’s wort and all synthetical antidepressants) 2.09 1.14 3.82 2.08 1.10 3.95 2.74 1.36 5.51 3.15 1.60 6.23
St. John’s wort (N05CP03/N06AP01/51( 1.10 0.22 5.58 1.19 0.20 7.16 3.30 0.46 23.7 2.76 0.30 25.3
Any synthetical antidepressants 2.16 1.15 4.07 2.12 1.08 4.15 2.53 1.22 5.27 3.01 1.48 6.09
NSMRIs(N06AA) 1.28 0.51 3.23 1.11 0.40 3.06 0.95 0.35 2.57 1.11 0.42 2.92
SSRIs (N06AB) 3.10 1.25 7.69 3.55 1.42 8.85 6.74 2.47 18.4 7.02 2.38 20.7
Any hypnotics & sedatives (synth., antihistamine and phytoceuticals) 0.74 0.27 2.08 0.80 0.29 2.22 0.89 0.28 2.88 0.72 0.22 2.40
Any synth. (N05C) and antihistamine (N05CM) 0.73 0.20 2.65 0.81 0.21 3.08 0.56 0.13 2.51 0.45 0.10 2.08
Benzodiazepines (N05BA, N05CD, N03AE01) 1.23 0.40 3.78 1.28 0.42 3.92 0.93 0.16 5.22 1.01 0.17 5.88
Benzodiazepines and benzodiazepine-related drugs 1.31 0.52 3.26 1.41 0.57 3.49 0.92 0.24 3.48 0.88 0.22 3.56
Narcotic analgesics (N02A) 2.64 1.30 5.38 2.66 1.30 5.43 2.21 0.97 5.05 2.27 0.97 5.34
Any anti-dementia drugs (N06DA+ Ginkgo biloba) 2.21 0.95 5.11 1.85 0.73 4.64 1.91 0.50 7.26 1.92 0.54 6.79
Ginkgo biloba (N06DP01) 2.15 0.89 5.20 1.78 0.67 4.76 1.85 0.45 7.56 1.90 0.51 7.09
Anti-epileptics (N03) 0.74 0.21 2.59 0.85 0.24 2.94 0.47 0.11 1.99 0.42 0.10 1.81
Antiparkinson drugs (N04) 3.51 1.18 10.4 3.80 1.29 11.2 1.44 0.34 6.02 1.43 0.37 5.56
Valerian (N05CP01/51) 0.71 0.16 3.23 0.76 0.17 3.35 1.10 0.21 5.78 0.89 0.16 4.80
Odds ratio (OR) and 95% confidence intervals (95% CI) were derived from logistic regression models.
Model 1: adjusted for sex and age group (65–69, 70–74, 75–79 years)
Model 2: model 1+social status (lower, middle, upper), community size (rural area, small, middle and large city), region (East, north, central, south), living
alone (yes, no),
Model 3: Model 2+ frailty (frailty, pre-frailty, no frailty), polypharmacy (yes, no), disability (yes, no), vision impairment (severe, slight, no), daily alcohol
drinking (yes, no), BMI <25, 25–30, > = 30), SBP (continuous variables) Model 4: Model 3+antihypertensives, antidiabetics, nonsteroidal anti-inflammatory drugs (NSAIDs), statins, thyroid therapy (yes, no)
NSMRIs: non selective monoamino reuptake inhibitors
SSRIs: Selective serotonin reuptake inhibitors
Figures in bold denote statistical significance (p < .050).
https://doi.org/10.1371/journal.pone.0182432.t004
Association of psychotropic drug use with falls among older adults in Germany
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people aged 60 and older found a pooled odds ratio of 1.73 (95%CI, 1.52–1.97) for any psycho-
tropic use [10]. This finding was confirmed by another meta-analysis including 71 studies pub-
lished between 1981 and 2007, which reported an odds ratio of 1.78 (1.57–2.01) [13]. Both are
well comparable to our finding of an odds ratio of 1.64 (1.14–2.37) for the association between
psychotropic drug use and falls among older adults. A recent systematical review of prospec-
tive and retrospective studies published between 2008 and 2013 on the association of medica-
tion use and falls in older people found that 29 of 36 studies reported a positive association
between the risk of falls and use of psychotropic medications including sedatives and hypnot-
ics, antidepressants, and benzodiazepines [14]. Further, a large body of evidence from prospec-
tive studies and clinical trials suggests that reduced use of psychotropic medications resulted
in reduction of falls [39], strongly supporting the associations between psychotropic drug use
and falls.
Our findings on the association between antidepressants use and falls or recurrent falls are
also in line with results of other studies. Use of antidepressants, particularly SSRIs, has been
consistently found to be associated with increased risks of falls and recurrent falls [40–43]. For
example, in a longitudinal analysis of 2948 community-dwelling older adults followed-up for 7
years, antidepressant users, compared with nonusers, were observed to have a 48% greater like-
lihood of recurrent falls (OR 1.48, 1.12–1.96), particularly those taking SSRIs with an OR of
1.62 (1.15–2.28) [40]. Alike, in a cross-sectional survey including community-dwelling older
adults from Australian general practices, antidepressants use was independently associated
with multiple falls (OR 1.46, 1.25–1.70). Amongst all psychotropic medications, SSRI use was
found to be associated with the highest risk of multiple falls (OR 1.66, 1.36–2.02) [44]. Using
data of the Swedish registers with a sample size of more than 1 million persons aged �65
years, Johnell and colleagues found that among psychotropic drugs, antidepressants had the
strongest association with fall-related injuries (adjusted OR 1.42, 1.38–1.45) [45]. These studies
suggest that use of antidepressants could result in a 40–70% greater likelihood of falls [40, 44,
45]. In the present study, we found a much higher OR of 2.88 (1.63–5.09) for the association
between use of antidepressants and falls, which, however, is comparable to the results of a pro-
spective population-based study reporting an OR of 2.8 (1.9–4.1) among older men aged 60–
75 years in Denmark [46]. Nevertheless due to small sample size in our study, the OR for
SSRIs use (Table 3) is much higher than that (3.1, 2.0–5.0) found in the Danish study [46].
Interestingly, we found that the use of psychotropic phyto-medicines, either St. Johns’ wort,
valerian or Gingko biloba, was not associated with any falls or recurrent falls. This may be due
to their weak effects compared to their synthetic counterparts. Surprisingly, we did not find an
association of falls or recurrent falls with the use of hypnotics and sedatives, antiepileptics, or
narcotic analgesics. However, some studies also found no significant association between falls
and the use of anxiolytics/hypnotics [46], or a weaker association with the use of hypnotics
and sedatives [45] or antiepilepitcs [47]. In contrast, other studies report positive associations
between falls and the use hypnotics and sedatives [12, 14, 47, 48], opioids/narcotics [46, 48]
[49] or antiepileptics [46]. There may be several reasons for the inconsistence between findings
of our study and of others. First, the sample size for users of hypnotics and sedatives, antiepi-
leptics and narcotic analgesics in our study is relatively small (for example, only 36 persons
used synthetic hypnotics and sedatives, Table 2). Second, more than half of all benzodiaze-
pines, hypnotics and sedatives were taken as needed while only a small part of them were
taken regularly more than 3 months (appendix Table 1a). Third, evidence of an association
between substantially increased risk of falls and use of benzodiazepines (particularly long-act-
ing agents) tends to be found in earlier study. Finally, because of well-known ‘after effects’ of
hypnotics and sedatives that may increase the risk of falls, older adults at high risk of falls may
have been cautioned by physicians and thus avoided taking such kind of drugs. As a result, use
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 10 / 15
of anxiolytics was found to be even associated with a slightly reduced risk of fall (OR 0.97, 95%
CI 0.94–1.00) [45]. In our study, although not statistically significant, the adjusted ORs for the
use of synthetic hypnotics & sedatives, benzodiazepine and related drugs tend to be <1
(Table 3).
Strength and limitation
The main strength of our study is that we used a nationally representative sample of commu-
nity-dwelling older adults. The weighted results can be generalized to the German older adults
aged 65–79 years. We fitted several logistic regression models to explore the associations
between psychotropic drug use and falls controlling for a number of confounding variables
including frailty, vision impairment and use of other fall risk-increasing drugs.
Findings of our study are subject to several limitations. First, DEGS1 is not specifically
designed for the study of association of psychotropic drug use and falls. Since other sources of
linked health administrative data are unavailable, data of national health surveys are a good
source that could be used for such kind of studies despite limitations. Persons aged > = 80
years and persons who were hospitalized or institutionalized in long-term care facilities were
not included in our national health surveys. In addition, community-dwelling older adults
with cognitive impairment, depression or other severe mental or physical illnesses (e.g. severe
vision impairment and fall injuries) might be less likely to take part in the survey due to the
need to travel to the examination sites. These persons might be at psychotropic drug use and
high risk of falls. Second, data on falls and drug use were self-reported; recall bias seems
unavoidable. In the invitation letter we asked all survey participants to bring the medication
packages to examination sites allowing us to verify medication use, which could reduce recall
bias greatly. Third, findings of our study might be weakened by the fact that we measured falls
in the past 12 months whereas drug use in the last 7 days. Due to this concern, we therefore
specifically examined use pattern and use durations of all psychotropic drugs. Results reveal
that more than half of all psychotropic drugs have been used for 12 months or longer. This is
particularly true for the use of major subgroups of psychotropic drugs such as synthetic antide-
pressants (72.4%) (S2 Table). Furthermore, sensitivity analyses involving drug use over 12
months demonstrate similar results, further supporting our findings. Fourth, the number of
drug users in some subgroups was quite small, which prevented us from detecting weak associ-
ations. Fifth, we investigated if any specific psychotropic drug was used in relations to falls.
Nevertheless, total daily drug dose exposure, changing doses, interactions between drugs, can
all be involved in fall risks, which we could not investigate in the present analysis. Finally and
most importantly, subject to observational design, our study did not allow a causality inference
between falls and psychotropic drug use and could not avoid indication bias. Indication bias
occurs when patients are prescribed drugs for a condition that itself is associated with the out-
come of interest [50, 51]. In this analysis, antidepressants are indicated to treat depression,
which itself, has been recognized as a key independent risk factor for falls [52–54]. Yet, there
are also studies suggesting that antidepressant use (particularly SSRIs) is strongly associated
with falls regardless of the presence of depressive symptoms [44].
Conclusions
In summary, we found that the use of psychotropic drugs overall, especially synthetic antide-
pressants like SSRIs, was associated with a higher risk of falls and recurrent falls among com-
munity dwelling older adults aged 65–79 years in Germany. Our study adds new evidence
concerning the association of use of psychotropic drugs—mainly synthetic antidepressants
like SSRIs- and falls among community-dwelling older adults. Given the severe consequence
Association of psychotropic drug use with falls among older adults in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0182432 August 8, 2017 11 / 15
of falls and the extensive use of psychotropic drugs among the elderly, a more rational use of
such kind of drugs is needed. Due to limitations of our study with small sample sizes for some
subgroups of drugs, further studies are required to investigate the associations between the use
of other commonly used psychotropic drugs such as hypnotics and sedatives and falls.
Supporting information
S1 Table. List of psychotropic drugs used among people aged 65–79 years. German national
health interview and examination survey 2008–2011 (DEGS1).
(DOCX)
S2 Table. Use pattern of psychotropic drugs among people aged 65–79 years—by use dura-
tion. German national health interview and examination survey 2008–2011 (DEGS1).
(DOCX)
Acknowledgments
We thank the survey participants for contributing towards our understanding of psychotropic
health.
Author Contributions
Conceptualization: Yong Du, Hildtraud Knopf.
Data curation: Yong Du, Hildtraud Knopf.
Formal analysis: Yong Du.
Funding acquisition: Hildtraud Knopf.
Methodology: Yong Du.
Project administration: Hildtraud Knopf.
Supervision: Hildtraud Knopf.
Writing – original draft: Yong Du.
Writing – review & editing: Yong Du, Ingrid-Katharina Wolf, Hildtraud Knopf.
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