Comijs et al. BMC Psychiatry (2015) 15:20
DOI 10.1186/s12888-015-0401-5
RESEARCH ARTICLE
Open Access
The two-year course of late-life depression; results
from the Netherlands study of depression in older
persons
Hannie C Comijs1,2*, Jasper Nieuwesteeg2, Rob Kok3, Harm W van Marwijk4, Roos C van der Mast5, Paul Naarding6,
Richard C Oude Voshaar7,8, Peter Verhaak9,10, Margot WM de Waal11 and Max L Stek2
Abstract
Background: We aimed to examine the course of depression during 2-year follow-up in a group clinically depressed
older persons. Subsequently, we studied which socio-demographic and clinical characteristics predict a depression
diagnoses at 2-year follow-up.
Methods: Data were used from the Netherlands Study of Depression in Older persons (NESDO; N = 510). Diagnoses of
depression DSM-IV-TR criteria were available from 285 patients at baseline and at 2-year follow-up. Severity of the
depressive symptoms, as assessed with the Inventory of Depressive Symptoms (IDS), was obtained from 6-monthly
postal questionnaires. Information about socio-demographic and clinical variables was obtained from the baseline
measurement.
Result: From the 285 older persons who were clinically depressed at baseline almost half (48.4%) also suffered from a
depressive disorder two years later. Patients with more severe depressive symptoms, comorbid dysthymia, younger age
of onset and more chronic diseases were more likely to be depressed at 2-year follow-up. 61% of the persons that were
depressed at baseline had a chronic course of depressive symptoms during these two years.
Conclusions: Late-life depression often has a chronic course, even when treated conform current guidelines for older
persons. Our results suggest that physical comorbidity may be candidate for adjusted and intensified treatment
strategies of older depressed patients with chronic and complex pathology.
Keywords: Late-life depression, Course, Determinants, Cohort study, Longitudinal
Background
Late-life depression is a complex mood disorder with
various etiological pathways [1] and high comorbidity
with psychiatric and physical diseases, and cognitive decline [2-5]. Late-life depression often has a chronic
course and high relapse rates [6-15], probably worse
compared to younger age groups [16]. Previous studies
were predominantly performed in community based or
primary care samples, and some of them were targeting
depressive symptoms or sub threshold depression, and
not depression diagnoses according to formal diagnostic
* Correspondence: h.comijs@ggzingeest.nl
1
Department Psychiatry/EMGO Institute for Health and Care Research VU
University Medical Center/GGZinGeest, Amsterdam, The Netherlands
2
GGZinGeest, Amsterdam, The Netherlands
Full list of author information is available at the end of the article
criteria. However, Beekman et al. [6] showed a gradient
with respect to the prognosis of late-life depression, in
which those with sub threshold disorders had the best
outcome, followed by those with major depressive disorder (MDD), dysthymia and double depression (MDD
and dysthymia). Only a few studies investigated the naturalistic course of late-life-depression in a large sample
of older persons with formal depression diagnoses.
Magnil et al. [15] observed the two-year course of depression in a cohort of primary care patients aged 60 years
and older and found that, 15 of the 51 depressed patients
(29%) had a remitting course, 25 (49%) remained depressive, and 11 (22%) had a fluctuating course. Hybels et al.
[13] were the first to study the course of severe depression
in older patients. They found that it took patients with a
double depression longer to reach partial or full remission,
© 2015 Comijs et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative
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unless otherwise stated.
Comijs et al. BMC Psychiatry (2015) 15:20
and that they had higher MADRS (Montgomery–Åsberg
Depression Rating Scale) scores after 3 years, compared to
those with major depression alone. So, the results suggest
that the course of late-life depression in patients from
mental health institutions may be as poor as in patients
from general practitioners or community based samples.
However, more studies among clinically depressed patients are necessary to confirm this assumption.
For a better scientific and clinical understanding of the
poor prognosis of late-life depression, it is important to
study the clinical determinants of its course. This may
help us to improve the treatment of late-life depression
and to develop tailor made interventions. Among younger adults, clinical characteristics of the depression such
as the severity of the depressive disorder, comorbid anxiety symptoms and age of onset are consistently found
to be important predictors of the course [16-18]. Increased time to recovery from late-life depression is previously found to be associated with severity of depressive
symptoms [19], but also with chronicity, later age of onset, cognitive decline [19,20] and medical comorbidity
[21]. To date there are few longitudinal studies that included sufficient numbers of clinically depressed older
persons enabling to study the course and determinants
of the course of late-life depression. In the Netherlands
Study on Depression in Older Persons (NESDO) depressed
patients were included from both mental health care facilities and general practitioners, thus including depressed patients in various developmental and severity stages [22].
We now have 2-year follow-up data available, which offers
us the possibility to study the two-year course of late-life
depression and its determinants in our cohort.
The aims of the present study were twofold. First, we examined the course of depression during 2-year follow-up
in a sample of clinically depressed patients, and second we
studied which socio-demographic and clinical characteristics predicted a depression diagnoses at 2-year follow-up.
Based on the literature we expected to find a high percentage of persons that are also depressed after 2-year, and that
the severity of the depression and physical comorbidity
would be important determinants of the poor outcome.
Methods
Participants
The Netherlands Study of Depression in Older persons
(NESDO) is an ongoing multi-site cohort study designed to
examine the (determinants of the) course and consequences
of depressive disorders in older persons (≥60 years). Detailed
description of the design and study sample is given in
Comijs et al. [22]. In short, NESDO included 378 depressed
patients (having MDD, dysthymia or minor depression according to DSM-IV criteria) and 132 non-depressed adults,
aged 60 through 93 years. Participants were recruited in five
regions in the Netherlands from both mental health care
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facilities and general practitioners. Participants were excluded when they had a dementia diagnosis or were suspected for dementia based on clinician’s judgement. In
addition, to be sure that participants were able to fully
understand and answer the questions, they were only included when they had a Mini Mental State Examinationscore (MMSE) [23] of 18 or higher (out of 30 points), and
when they had sufficient command of the Dutch language.
The response rate of the depressed persons from the mental
health institutions was estimated 48.7%, and from the general practices 60.3% [22]. Non-depressed comparisons were
recruited from general practitioners (response rate 66.7%),
and were included when they had no lifetime diagnosis of
depression, dementia or other serious psychiatric disorders,
and good command of the Dutch language [22]. The overall
sample of 510 persons had a mean age of 70.6 years (SD:
7.3; range 60–93) and consisted of 331 (64.9%) women and
179 (35.1%) men. The mean level of education was 11.0 years
(SD = 3.6; range 5–18 years). The majority of the sample
had the Dutch nationality (99.4%). The depressed persons
did not differ from the non-depressed comparison group
with respect to mean age and sex, but they had a lower level
of education, were more often divorced or widowed, and
had a lower score on the MMSE [22].
Materials and procedure
Data collection
Data collection of the baseline NESDO measurement
started in 2007 and was finished in September 2010. It
included an extensive assessment of psychopathology,
socio-demographic characteristics, physical health and
physical health markers, cognitive functioning, psychosocial functioning, and life style variables. The course of
late-life depression was followed up every 6 months by
means of a postal assessment, including questionnaires
on the severity of depressive symptoms and physical
health in the past 6 months, incident (chronic) stressors
and functional limitations, and use of medications and
health care. The questionnaires were the same questionnaires that were used during the face-to-face assessments
[22]. A second face-to-face assessment was performed
2 years after the baseline assessment. It started in 2009
and was completed in September 2012. It consisted of all
baseline measures (determinants and outcome variables)
that were open to change, such as severity of psychopathology and diagnostics. Well-trained research assistants,
mainly consisting of psychologists and mental health care
nurses, conducted the interviews. All interviews were
audio taped and were regularly controlled for their quality.
Ethical issues
The study protocol of NESDO has been approved centrally by the Ethical Review Board of the VU University
Medical Center, and subsequently by the local ethical
Comijs et al. BMC Psychiatry (2015) 15:20
review boards of the Leiden University Medical Center,
University Medical Center Groningen and the Radboud
University Medical Center in Nijmegen. Written informed
consent was obtained from all participants at the start of
the baseline assessment. Written informed consent was
asked for participating in the study, for permission to use
genetic information, to retrieve medical information from
the GP’s, and to link information to external databases. A
privacy protocol has been developed in which confidentiality of data is guaranteed by using a unique research ID
number for each respondent, which enables to identify individuals without using their names. Only the data manager has access to the record that links the ID number
with the name of the participant [22]. All data are available on request (see http://nesdo.amstad.nl/).
Course of depression
Diagnoses of major depression, dysthymia and minor depression according to DSM-IV-TR criteria [24] at baseline and at two-year follow-up were assessed with the
Composite International Diagnostic Interview (CIDI; WHO
version 2.1). The CIDI is a structured clinical interview that
is designed for use in research settings and has high validity
for depressive and anxiety disorders [25,26]. Questions were
added to determine the DSM-IV research diagnosis of
current minor depression [22].
More detailed information about the severity of the
depressive symptoms was obtained from the postal questionnaires, that were send to the respondents every
6 months. Severity of the depressive symptoms was
assessed with the Inventory of Depressive Symptoms
(IDS) [27]. The IDS is a 30-item self-report scale that
was developed to carefully assess all core criterion
diagnostic depressive symptoms. The scale has acceptable psychometric properties in depressed outpatients
e.g. [27,28] and depressed inpatients [29]. The IDS is
sensitive to both change over time and to differences
between treatment conditions [30]. Chronbach’s alpha
for the IDS in our sample was 0.83. The IDS was also
included in the baseline and 2-year follow-up assessment, resulting in a total of 5 IDS ratings per participant. The IDS-scores range between 0 and 84, and is
categorized according to severity as; < 14: no depression, 14–25: mild depression, 26 – 38 moderate depression,
39–48: severe depression and ≥ 49: very severe depression.
Course types of depressive symptoms were computed from
patients from whom we had at least 4 out of 5 IDS scores.
We distinguished 5 course types:
1. remission, defined as at least the last two
observations IDS score < 14,
2. intermittent depression, defined as at least one of
the observations IDS < 14 (not being the last two
observations),
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3. chronic depression, defined as all IDS scores > 14
and 38 and sub classified as:
a. chronic mild to moderate depression, defined as
all IDS scores between 14 and 26,
b. chronic moderate to severe depression, defined as
all IDS scores between 26 and 84,
c. chronic depression with variable severity, defined
as IDS scores varying between 14 to 84.
Determinants of depressive disorder at 2-year follow-up
Socio-demographic characteristics including age, sex, years
of education, and partner status were assessed with standard questions. Sampling characteristics included sampling
site (Amsterdam, Leiden, Groningen, Apeldoorn/Zutphen
and Nijmegen) and sampling frame (primary care, ambulant health care and clinical health care).
Clinical variables included; first episode MDD (y/n),
comorbid dysthymia (y/n), age of onset, comorbid anxiety disorder(s) (y/n), severity of depressive symptoms,
cognitive functioning and number of chronic diseases.
Information about the first episode MDD, recurrent
MMD, dysthymia, and age of onset were all obtained
from the CIDI (WHO version 2.1). Comorbid anxiety
disorders (General Anxiety Disorder, Panic Disorder,
Agoraphobia and Social Phobia) were also assessed
using the CIDI. The Mini-Mental State Examination
(MMSE) [23] was used to assess global cognitive functioning. The presence of chronic diseases was assessed
by means of a self-report questionnaire. The participants were asked whether they currently or previously
had any of the following chronic diseases or disease
events: cardiac disease (including myocardial infarction),
peripheral atherosclerosis, stroke, diabetes mellitus, COPD
(asthma, chronic bronchitis or pulmonary emphysema),
arthritis (rheumatoid arthritis or osteoarthritis), cancer, or
any other chronic disease. The accuracy of self-reports of
these diseases was compared to general practitioner information, and was shown to be adequate and independent of
cognitive impairment [31]. Use of anti-depressive medication and benzodiazepines was determined by inspection of
the medication that the participants brought in.
Statistical analyses
Descriptive statistics were used to describe attrition and
its determinants according to depression status at baseline. Next, diagnoses at 2-years follow-up were described
according to baseline diagnostic status. In addition,
specific course types were described according to the
severity of depressive symptoms obtained from the five
6-monthly assessments with the IDS (see description IDS).
The socio-demographics, clinical and treatment characteristics were described for the depressed patients according to their depression diagnoses (MDD, dysthymia
or minor depression) according to DSM-IV-R criteria at
Comijs et al. BMC Psychiatry (2015) 15:20
Page 4 of 9
2-year follow-up. Associations between baseline characteristics and the outcome measure depression diagnoses
(y/n) at 2-year follow-up, were first assessed with univariate
logistic regression analyses. Subsequently, when p < 0.10
the variables were entered in a final multivariate model. All
analyses were performed by using SPSS 21.0 (IBM SPSS,
Chicago, IL).
Results
Attrition and its determinants
From the 510 persons that were included at baseline,
401 persons participated in the 2-year follow-up assessment (overall attrition rate of 21.4%). Twenty-eight persons died during the two-year follow-up (5.5%). From
the 482 participants who were still available for the study
at that time point, 401 persons (83.4%) participated in
second face-to-face measurement. In the patient group,
the most important reasons for attrition were death (28.0%)
and mental problems (37.6%). In the non-depressed comparison group the most important reason for attrition was,
having no interest or no time (50%) (Table 1).
Attrition was significantly higher among persons who
were depressed at baseline, and among those with lower
education, more severe psychopathology and lower cognitive functioning (all p < 0.05). Recruitment area and
sampling frame also differed between respondents and
non-respondents at follow-up. Non-respondents had more
often been recruited in Apeldoorn/Zutphen and Nijmegen
and from outpatient and inpatient mental health facilities
(both p < 0.01).
Table 1 Attrition at 2-year follow-up according to depression
status at baseline (n = 510)
Patient group
(n = 378)
Control group
(n = 132)
N (%)
N (%)
Respondents at 2-y follow-up
285 (75.4)
116 (87.9)
Non-respondents at 2-y follow-up
93 (24.6)
16 (12.1)
Reasons of attrition
Deceased
26 (28.0)
2 (12.5)
Refusal
No interest/no time
14 (15.0)
8 (50.0)
Bad experience with previous
interview
1 (1.1)
0 (0)
Due to physical reasons
12 (12.9)
2 (12.5)
Due to mental reasons
35 (37.6)
4 (25.0)
No contact
4 (4.3)
0 (0)
Moved abroad
1 (1.1)
0 (0)
Unable
Noncontact
Course of depression
Depression diagnoses at two-year follow-up according to
baseline depression diagnoses are shown in Table 2.
From the 285 persons who were suffering from a depressive disorder at baseline, almost half (48.4%) also suffered from a depressive disorder two years later. About
59% of the persons with a double depression (MDD and
dysthymia) at baseline, also had a depression diagnoses
at 2-year follow-up. From the persons with a MDD at
baseline 44% were also depressed at follow-up. All four
persons with dysthymia only at baseline were also depressed at FU. Among the persons with a minor depression the highest remission rates were reached (63.6%).
Only 19% of the persons that was depressed at baseline
was completely in remission, with at least the last two IDS
assessments lower than 14, whereas 56% of the persons
with a depressive disorder at baseline, but without a
depressive disorder at follow-up, still had IDS-score
higher than 14, suggesting residual depressive symptoms at follow-up.
According to the severity of depressive symptoms as
assessed with the IDS every six months, 61% of the persons that were depressed at baseline had a chronic
(mild/moderate, severe, or variable) course (see Figures 1
and 2), whereas 20% had intermittent depression – with
at least one assessment during the 2-year period without
depressive symptoms (IDS score <14).
Determinants of depressive disorder at 2-year follow-up
Finally, we examined which baseline socio-demographic
and clinical characteristics predicted a depression diagnoses at 2-year follow-up (Table 3). Univariate analyses
showed that dysthymia, a younger age of onset, higher
IDS score, more chronic diseases and being recruited
from primary care were associated with having a depressive disorder at follow-up. In multivariate regression analyses, independent associations appeared to be a younger
age of onset, higher IDS score, and having more chronic
diseases at baseline (Table 4).
Discussion
Our study showed that in a sample of clinically depressed older patients nearly 50% still had a depression
diagnoses at 2-year follow-up. Of our patients 61%
showed a chronic course of the depressive symptoms
during the two-year period. Patients with more severe
depressive symptoms, comorbid dysthymia, younger age
of onset and more chronic diseases were more likely to
be depressed at 2-year follow-up.
Our findings are largely in line with expectations from
community based, primary care and other clinical samples of older persons [6,10,13,15,32]. Consistent with the
findings of Hybels et al. [13], we found that the persons
with a double depression (MDD and dysthymia) had the
Comijs et al. BMC Psychiatry (2015) 15:20
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Table 2 Depression diagnoses at 2-year follow-up according to baseline diagnoses
N
Baseline
2 year follow-up
Double depression1
Major depression
Dysthymia
Minor depression
No depression diagnoses
Double depression1, n (%)
71
20 (28.2)
17 (23.9)
3 (4.2)
2 (2.8)
29 (40.8)
Major depression, n (%)
199
38 (19.1)
36 (18.1)
6 (3.0)
8 (4.0)
111 (55.8)
Dysthymia, n (%)
4
0
1 (25)
3 (75.0)
0
0
Minor depression, n (%)
11
0
1 (9.1)
2 (18.2)
1 (9.1)
7 (63.6)
1
Major depression and dysthymia.
poorest prognosis, with 59% still suffering from a depressive disorder at two years follow-up. Compared to
studies among adults aged 18 to 65 years, our remission
rates seem somewhat lower. In the Netherlands Study
on Depression and Anxiety (NESDA) [18], which has a
comparable design and uses largely the same instruments as in NESDO, about 80% of the purely depressed
patient reached remission within 2 years, whereas from
the persons with a comorbid anxiety disorder only 50%
reached remission within that time frame. In our study,
36.8% of the depressed persons had a comorbid anxiety
disorder, however, comorbidity was no predictor of a depression diagnoses at follow-up. Thus, we may conclude
that our study confirms the poorer prognosis of depression in terms of chronicity among older persons compared to younger adults.
Figure 1 Course of depression (percentages). [Remission: at least
the last two observations IDS score < 14; Intermittent: at least one of
the observations IDS < 14 (not being the last two observations);
Chronic depression, defined as all IDS scores > 14 and sub classified
as: chronic mild to moderate depression, defined as all IDS scores
between 14 and 26; chronic moderate to severe depression, defined
as all IDS scores between 26 and 84; chronic depression with
variable severity, defined as IDS scores varying between 14 to 84].
Since we assessed the severity of depressive symptoms
every 6 months, it was possible to study the course of
depression in more detail. Of the depressed patients,
61% showed a chronic course of the depressive symptoms during the two years of follow-up, whereas 20%
had intermittent depressive symptoms. These findings
suggest that most patients had clinically relevant levels
of depressive symptoms all the time during this 2-year
period, further stressing the persistence and chronicity
of the depressive symptoms, despite the fact that most
of them were being treated in mental health care facilities. Only 19% of the depressed older people reached
complete remission, whereas 56% of the persons without
a depression diagnoses at follow-up still had residual depressive symptoms.
With respect to the determinants of the prognosis of depression we found that patients with more severe depression
at baseline, comorbid dysthymia, younger age of onset and
more chronic diseases were more likely to be depressed at
2-year follow-up. None of the socio-demographic variables
appeared to be a predictor of the prognosis, neither was
comorbid anxiety disorder or cognitive functioning.
Figure 2 Severity of depressive symptoms according to course
during 2-year follow-up. [Remission: at least the last two
observations IDS score < 14; Intermittent: at least one of the
observations IDS < 14 (not being the last two observations); Chronic
depression, defined as all IDS scores > 14 and sub classified as:
chronic mild to moderate depression, defined as all IDS scores
between 14 and 26; chronic moderate to severe depression, defined
as all IDS scores between 26 and 84; chronic depression with
variable severity, defined as IDS scores varying between 14 to 84].
Comijs et al. BMC Psychiatry (2015) 15:20
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Table 3 Descriptives of patient who were depressed at
baseline according to their depression status at 2-year
follow-up
Table 4 Univariate and multivariate determinants of a
depressive disorder (yes/no) at follow-up in the patient
group (n = 285)
Not depressed at Depressed at
follow-up (n = 147) follow-up (n = 138)
The presence of depression at
2-year follow up
Socio-demographics at
baseline
Univariate
Multivariate1
OR (95% CI)
OR (95% CI)
- Mean age (sd)
70.4 (7.1)
70.9 (7.9)
Socio-demographics
- Female gender, n (%)
97 (66.0)
90 (65.2)
- Age at baseline, in years
1.01 (0.98 – 1.04)
- Years of education,
mean (sd)
10.7 (3.2)
10.5 (3.7)
- Female gender
0.97 (0.59 – 1.58)
- Education, in years
0.99 (0.92 – 1.05)
- No partner
1.34 (0.84 – 2.13)
- No partner, n (%)
66 (44.9)
72 (52.2)
- Sampling site, n (%)
- Amsterdam
61 (48.8)
64 (51.2)
- Leiden
26 (44.1)
33 (55.9)
- Groningen
22 (55.0)
18 (45.0)
- Apeldoorn/Zutphen
21 (67.7)
10 (32.2)
- Nijmegen
17 (56.7)
13 (43.3)
Clinical characteristics at
baseline
- Sampling site
- Amsterdam
Ref group
Ref group
- Leiden
1.21 (0.65 – 2.25)
1.63 (0.81-3.29)
- Groningen
0.78 (0.38 – 1.59)
0.95 (0.42-2.11)
- Apeldoorn/Zutphen
0.45 (0.20 – 1.04)
0.56 (0.21-1.53)
- Nijmegen
0.73 (0.33 – 1.63)
0.81 (0.32-2.06)
Clinical characteristics at baseline
- First episode MDD, n (%)
70 (47.6)
65 (47.1)
- First episode MDD
0.98 (0.62 – 1.56)
- Dysthymia, n (%)
29 (19.7)
46 (33.3)
- Dysthymia
2.03 (1.19 – 3.49)
- Age of onset of
depression, mean (SD)
51.2 (19.5)
44.2 (20.7)
- Comorbid anxiety disorder, 48 (32.7)
n (%)
- Severity depression
symptoms
25.6 (11.8)
57 (41.3)
33.9 (12.5)
Sampling frame, n (%)
- Onset of depression, in years
0.98 (0.97 – 0.995) 0.99 (0.98-1.00)
- Comorbid anxiety disorder
1.45 (0.90 – 2.35)
- Severity depression symptoms
1.06 (1.04 – 1.08)
1.05 (1.03-1.07)
- Primary care
Ref group
Ref group
- Ambulant mental health care
0.63 (0.32 – 1.24)
0.57 (0.26-1.21)
0.36 (0.13 – 0.96)
0.43 (0.13-1.42)
Sampling frame
- Primary care
17 (40.5)
25 (59.5)
- Clinical mental health care
- Ambulant mental health
care
111 (51.9)
103 (48.1)
- Use anti depressive medication 0.88 (0.53 – 1.47)
- Use of benzodiazepines
- Clinical mental health care 19 (65.5)
10 (34.5)
- Use anti depressive
medication, n (%)
96 (69.6)
- Use of benzodiazepines,
n (%)
106 (72.1)
54 (36.7)
57 (41.3)
1.30 (0.71-2.37)
1.05 (0.83 – 1.34)
Comorbidity at baseline
- Number of chronic diseases
1.37 (1.16 – 1.63)
- MMSE
0.91 (0.80 – 1.04)
1.21 (1.01-1.46)
1
All variables with univariate p < 0.10 included.
MMSE: Mini Mental State Examination.
P-levels < 0.05 are printed bold.
Comorbidity
- Number of chronic
diseases, mean (sd)
1.8 (1.2)
2.4 (1.7)
- MMSE, mean (sd)
28.0 (1.7)
27.7 (1.8)
MMSE: Mini Mental State Examination.
Our findings are partly in line with previous studies
that reported severity and chronicity of depressive
symptoms [19] and medical comorbidity [21] to be related with an increased time to recovery. In contrast
with Alexopoulos [19] however, we found an early onset of depression to be associated with poor prognosis.
Also in contrast with our results, Bogner [14] showed
in the PROSPECT study that married patients had a
favourable course of depression, suggesting that depressed
persons with a supportive relationship improve more
quickly. In our study, partner status was not statistically
significant. This may be the due to the severity of depression, our sample was mainly recruited in in- and outpatients facilities, whereas the PROSPECT sample was
recruited in primary care.
Although we included important socio-demographic,
and clinical characteristics as possible determinants for
the prognosis of depression, additional key biological,
health and psychosocial determinants may be of relevance for the prognosis of depression. However, before
conducting such in-depth analyses in the NESDO sample,
Comijs et al. BMC Psychiatry (2015) 15:20
we needed detailed insight in the course of late-life depression and its socio-demographic and clinical determinants, as was the aim of the present paper.
Attrition is an inevitable problem in studies among
vulnerable older persons. We made extensive efforts to
contact and invite persons to participate in the study
and offering them shortened interviews when necessary.
We kept in touch with all participants every half year
and send them yearly newsletters. Nevertheless, the attrition at 2-year follow-up was highest in the depressed
group 24.6% compared to 12.1% in the non-depressed
control group. In the depressed group 28% died and
37.6% did not want to participate due to mental reasons.
Unfortunately attrition was selective; attrition was higher
among persons who were depressed at baseline and who
had severe psychopathology, lower cognitive functioning,
and were recruited from outpatient or inpatients mental
health care settings. In the aforementioned comparable
NESDA study among younger adults aged 18–65, the
two-year attrition rate was 12.9% which was relatively
low compared to other epidemiological studies in psychiatric samples and was mainly due to refusal to further
participate [33]. Among older adults, attrition rates are
expected to be higher, because of a higher risk for death
and diseases compared to younger adults. In the Longitudinal Aging Study Amsterdam, a population based cohort
study among older persons age 55 years and older, threeyear attrition rates were around 19% and was mainly due to
death [34]. We may therefore conclude that the attrition rate
in our study is not extremely high, when taking age and disease status of our sample into account, but it may limit the
generalizability of the findings to some extent and needs to
be reflected upon in future studies.
It should be noted that our findings cannot be generalized to community-dwelling older persons, as most of
our patients were recruited from specialized mental
health facilities and may represent a group with more refractory depression at baseline. However, we were especially interested in this group because patients with
clinical depression are often underrepresented in community based samples. Thus far, few studies investigated
the naturalistic course of late-life-depression in a large
sample of older persons with formal depression diagnoses. Our findings are therefore important for clinical
practice.
Clinical implications
As most of the diagnosed patients (85.3%) were under
treatment when they entered the NESDO study, the results may tell us something about the adequacy of the
depression treatment in this older age group. Regular interventions are mainly adapted from guidelines that are
based on research performed in younger adults, assuming
that depression in older persons has the same underlying
Page 7 of 9
mechanism as depression in younger adults. Although
pharmacological and psychotherapy are effective treatments for late-life depression [35,36], it is suggested that
antidepressants may be less efficacious in in older depressed patients compared to younger ones [37,38].
Moreover, studies are generally limited to the youngest
old, reflected by average samples ages below 70 years
and minimal physical comorbidity [36].
In older persons, depression treatment may need to be
tailored to address underlying etiological factors and comorbidity as well. The group of Alexopoulos [39] developed a personalized intervention for depressed patients
with severe chronic obstructive pulmonary dysplasia
(COPD) and showed that this intervention reduced depressive symptoms and dyspnea-related disability more
than usual care over 28 weeks. However, thus far there
is only limited evidence that such a multifactorial personalized treatment is more effective than the regular
treatment. Nevertheless, personalizing depression treatment seems necessary to improve the treatment of depression, especially in this older age group. Our results suggest
that physical comorbidity may be candidate for adjusted
and intensified treatment strategies of older depressed
patients with chronic and complex pathology.
Conclusions
Our study showed that almost half of a group of older
patients with a depressive disorder were also suffering
from a depressive disorder two years later, and that most
of them had a chronic course of the depressive symptoms during the 2 years of follow-up. More serious depression, a younger age of depression onset, and more
somatic comorbidity were independent determinants of
a poor prognosis of depression.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
HCC, principle investigator of NESDO, was responsible for the conception
and the design of the study and the acquisition of the data. She wrote the
paper and supervised the data-analyses. JN supervised the data collection,
performed the overall data management, and carried out the data-analyses.
RK contributed to the local data collection and co-authored the paper.
HWJM was involved in the design of the study and co-authored the paper.
RCM was involved in the conception and the design of the study, supervised
the local data collection and co-authored the paper. PN was involved in the
conception and the design of the study, supervised the local data collection
and co-authored the paper. ROV was involved in the conception and the
design of the study, supervised the local data collection and co-authored
the paper. PV contributed to the local data collection and co-authored
the paper. MWMW contributed to the local data collection and co-authored
the paper. MLS was involved in the conception and the design of the study,
supervised the local data collection and co-authored the paper. All authors
read and approved the final manuscript.
Acknowledgement
The infrastructure for the NESDO study (http://nesdo.amstad.nl) is funded
through the Fonds NutsOhra (project 0701–065), and the participating
universities and mental health care organizations (VU University Medical
Comijs et al. BMC Psychiatry (2015) 15:20
Center, Leiden University Medical Center, University Medical Center
Groningen, UMC St Radboud, GGZ inGeest, GG Net, GGZ Nijmegen, GGZ
Rivierduinen, Lentis, and Parnassia).
Author details
1
Department Psychiatry/EMGO Institute for Health and Care Research VU
University Medical Center/GGZinGeest, Amsterdam, The Netherlands.
2
GGZinGeest, Amsterdam, The Netherlands. 3Parnassia/BAVO groep,
Department of Old-age Psychiatry, The Hague, The Netherlands. 4VU University
Medical Center, Department of General Practice and Elderly Care
Medicine/EMGO Institute for Health and Care Research, Amsterdam, The
Netherlands. 5Department of Psychiatry, Leiden University Medical Center,
Leiden, The Netherlands. 6GGNet, Department of Old-age Psychiatry,
Apeldoorn/Zutphen, The Netherlands. 7Department of Psychiatry,
Radboud University Nijmegen Medical Center, Nijmegen, The
Netherlands. 8University of Groningen, University Medical Center
Groningen, Interdisciplinary Center for Psychopathology of Emotion
regulation (ICPE), Groningen, The Netherlands. 9Department General
Practice, University of Groningen, University Medical Center Groningen,
Groningen, the Netherlands. 10NIVEL, Netherlands Institute of Health
Services Research, Utrecht, the Netherlands. 11Department of Public
Health and Primary Care, Leiden University Medical Center, Leiden, The
Netherlands.
Received: 15 July 2014 Accepted: 26 January 2015
Page 8 of 9
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References
1. Wittchen HU. The burden of mood disorders. Editorial. Science. 2012;338:15.
2. Beekman AT, De Beurs E, Van Balkom AJ, Deeg DJ, Van Dyck R, Van Tilburg
W. Anxiety and depression in later life: Co-occurrence and communality of
risk factors. Am J Psychiatry. 2000;157:89–95.
3. Lenze EJ, Mulsant BH, Shear MK, Alexopoulos GS, Frank E, Reynolds 3rd CF.
Comorbidity of depression and anxiety disorders in later life. Depress
Anxiety. 2001;14:86–93.
4. Steffens DC. A multiplicity of approaches to characterize geriatric depression
and its outcomes. Curr Opin Psychiatry. 2009;22:522–6.
5. Kessler RC, Bromet EJ. The Epidemiology of Depression Across Cultures.
Annu Rev Public Health. 2013;34:119–38.
6. Beekman AT, Geerlings SW, Deeg DJ, Smit JH, Schoevers RS, de Beurs E,
et al. The natural history of late-life depression: a 6-year prospective study in
the community. Arch Gen Psychiatry. 2002;59:605–11.
7. Stek ML, Van Exel E, Van Tilburg W, Westendorp RG, Beekman AT. The prognosis
of depression in old age: outcome six to eight years after clinical treatment.
Aging Ment Health. 2002;6:282–5.
8. Mueller TI, Kohn R, Leventhal N, Leon AC, Solomon D, Coryell W, et al. The course
of depression in elderly patients. Am J Geriatr Psychiatry. 2004;12:22–9.
9. Mitchell AJ, Subramaniam H. Prognosis of depression in old age compared
to middle age: a systematic review of comparative studies. Am J Psychiatry.
2005;162:1588–601.
10. Licht-Strunk E, Van Der Windt DA, Van Marwijk HW, De Haan M, Beekman AT.
The prognosis of depression in older patients in general practice and the
community. A systematic review. Fam Pract. 2007;24:168–80.
11. Andreescu C, Lenze EJ, Dew MA, Begley AE, Mulsant BH, Dombrovski AY,
et al. Effect of comorbid anxiety on treatment response and relapse risk in
late-life depression: controlled study. Br J Psychiatry. 2007;190:344–9.
12. Zisook S, Lesser I, Stewart JW, Wisniewski SR, Balasubramani GK, Fava M,
et al. Effect of age at onset on the course of major depressive disorder.
Am J Psychiatry. 2007;164(10):1539–46.
13. Hybels CF, Pieper CF, Blazer DG, Steffens DC. The course of depressive
symptoms in older adults with comorbid major depression and dysthymia.
Am J Geriatr Psychiatry. 2008;16:300–9.
14. Bogner HR, Morales KH, Reynolds CF, Cary MS, Bruce ML. Prognostic factors,
course, and outcome of depression among older primary care patients: the
PROSPECT study. Aging Ment Health. 2012;16(4):452–61.
15. Magnil M, Janmarker L, Gunnarsson R, Björkelund C. Course, risk factors, and
prognostic factors in elderly primary care patients with mild depression: a
two-year observational study. Scand J Prim Health Care. 2013;31(1):20–5.
16. Spijker J, de Graaf R, Bijl RV, Beekman AT, Ormel J, Nolen WA. Duration of
major depressive episodes in the general population: results from The
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
Netherlands Mental Health Survey and Incidence Study (NEMESIS). Br J
Psychiatry. 2002;181:208–13.
Spijker J, de Graaf R, Bijl RV, Beekman ATF, Ormel J, Nolen WA. Determinants
of persistence of major depressive episodes in the general population.
Results from the Netherlands Mental Health Survey and Incidence Study
(NEMESIS). J Affect Disord. 2004;81:231–40.
Penninx BW, Nolen WA, Lamers F, Zitman FG, Smit JH, Spinhoven P, et al.
Two-year course of depressive and anxiety disorders: results from the
Netherlands Study of Depression and Anxiety (NESDA). J Affect Disord.
2011;133(1–2):76–85.
Alexopoulos GS, Meyers BS, Young RC, Kakuma T, Feder M, Einhorn A, et al.
Recovery in geriatric depression. Arch Gen Psychiatry. 1996;53:305–12.
Alexopoulos GS, Kiosses DN, Heo M, Murphy CF, Shanmugham B,
Gunning-Dixon F. Executive Dysfunction and the Course of Geriatric
Depression. Biol Psychiatry. 2005;58:204–10.
Murphy E. The prognosis of depression in old age. Br J Psychiatry.
1983;142:111–9.
Comijs HC, van Marwijk H, van der Mast RC, Naarding P, Oude Voshaar RC,
Beekman ATF, et al. The Netherlands Study of Depression in Older persons
(NESDO); design and methods. BMC Research Notes. 2011;4(1):524.
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical
method for grading the cognitive state of patients for the clinician. J Psych
Res. 1975;12:189–98.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental
Disorders. 4th ed. Washington DC: American Psychiatric Publishing; 2000.
Kessler RC, Birnbaum H, Bromet E, Hwang I, Sampson N, Shahly V. Age
differences in major depression: results from the National Comorbidity
Survey Replication (NCS-R). Psychol Med. 2010;40:225–37.
Wittchen HU, Robins LN, Cottler LB, Sartorius N, Burke JD, Regier D. Cross-cultural
feasibility, reliability and sources of variance of the Composite International Diagnostic Interview (CIDI). The Multicentre WHO/ADAMHA Field Trials. Br J Psychiatry.
1991;159:645–53.
Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The Inventory of
Depressive Symptomatology (IDS): psychometric properties. Psychol Med.
1996;26:477–86.
Corruble E, Legrand JM, Duret C, Charles G, Guelfi JD. IDS-C and IDS-SR:
psychometric properties in depressed inpatients. J Affect Disord.
1999;56:95–101.
Trivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, et al.
The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and
Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology,
Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector
patients with mood disorders, a psychometric evaluation. Psychol Med.
2004;34:73–82.
Rush AJ, Trivedi MH, Carmody TJ, Ibrahim HM, Markowitz JC, Keitner GI,
et al. Self-reported depressive symptom measures: sensitivity to detecting
change in a randomized, controlled trial of chronically depressed, nonpsychotic
outpatients. Neuropsychopharmacology. 2005;30(2):405–16.
Kriegsman DM, Penninx BW, Van Eijk JT, Boeke AJ, Deeg DJ. Self-reports and
general practitioner information on the presence of chronic diseases in
community dwelling elderly. A study on the accuracy of patients’ self-reports
and on determinants of inaccuracy. J Clin Epidemiol. 1996;49:1407–17.
Licht-Strunk E, Beekman AT, de Haan M, van Marwijk HW. The prognosis of
undetected depression in older general practice patients. A one year
follow-up study. J Affect Disord. 2009;114(1–3):310–5.
Lamers F, Hoogendoorn AW, Smit JH, van Dyck R, Zitman FG, Nolen WA,
et al. Sociodemographic and psychiatric determinants of attrition in the
Netherlands Study of Depression and Anxiety (NESDA). Compr Psychiatry.
2012;53(1):63–70.
Huisman M, Poppelaars J, van der Horst M, Beekman AT, Brug J, van Tilburg TG,
et al. Cohort profile: the Longitudinal Aging Study Amsterdam. Int J Epidemiol.
2011;40(4):868–76.
Kok RM, Nolen WA, Heeren TJ. Efficacy of treatment in older depressed
patients: A systematic review and meta-analysis of double-blind randomized
controlled trials with antidepressants. J Affect Disord. 2012;141:103–15.
Cuijpers P, van Straten A, Smit F, Andersson G. Is psychotherapy for
depression equally effective in younger and older adults? A meta-regression
analysis. Int Psychogeriatr. 2009;21:1–16.
Tedeschini E, Levkovitz Y, Lovieno N, Ameral VE, Nelson JC, Papakostas GI. Efficacy
of antidepressants for late-life depression: a meta-analysis and meta-regression of
placebo-controlled reandomized trials. J Clin Psychiatry. 2011;72:1660–8.
Comijs et al. BMC Psychiatry (2015) 15:20
Page 9 of 9
38. Gould RL, Coulson MC, Howard RJ. Cognitive behavioural therapy for
depression in older people: a meta-analysis and meta-regression of
randomized controlled trials. J Am Geriatr Soc. 2012;60:1817–30.
39. Alexopoulos GS, Raue PJ, Sirey JA, Arean PA. Developing an intervention for
depressed, chronically medically ill elders: a model from COPD. Int J Geriatr
Psychiatry. 2008;23(5):447–53.
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