www.elsevier.com/locate/jad

Journal of Affective Disor

Research report

Stability and change of emotional functioning in late life:

modelling of vulnerability profiles

Edwin de Beursa,*, Hannie Comijsb, Jos W.R. Twiskc,d, Caroline Sonnenbergb,

Aartjan T.F. Beekmanb, Dorly Deegb

aDepartment of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The NetherlandsbDepartment of Psychiatry, Vrije Universiteit, Amsterdam, The Netherlands

cEMGO Institute, Vrije Universiteit, Amsterdam, The NetherlandsdDepartment of Clinical Epidemiology and Biostatistics, Vrije Universiteit, Amsterdam, The Netherlands

Received 23 July 2004; received in revised form 21 September 2004; accepted 27 September 2004

Abstract

Background and aims: The present study investigated stability and change in emotional well-being in a prospective study of a

large sample of community-dwelling older adults (z55 years). Emotional functioning was conceptualized according to the

tripartite model distinguishing three aspects: general negative affect (NA), depression, and anxiety. The study tested models for

the decline of mental health in late life based on the diathesis–stress model. In previous studies, support has been found for the

diathesis–stress model (for an overview, see [Goldberg, D.P., Huxley, P., 1992. Common mental disorders: a biosocial model.

Routledge, London; Zuckerman, M., 1999. Vulnerability to psychopathology. American Psychological Association,

Washington, DC.]). The predictive ability of vulnerability factors (the personality characteristics mastery and neuroticism)

and stressful life events and their interaction was tested for an increase in general negative affect, decreased positive affect (PA),

and increased anxiety. More specifically, we tested the hypothesis that loss leads to decreased positive affect in subjects with

low mastery, whereas threat leads to anxiety in subjects with high neuroticism.

Methods: Data from the Longitudinal Aging Study Amsterdam (LASA) were used. LASA is a longitudinal study in a large

representative sample of adults aged 55 to 85 (N=1837). Self-report data on depression, anxiety, and negative affect were

collected from adults over a 6-year period in three waves. The data were analyzed using multilevel analysis.

Results: The findings revealed an association between low mastery, high neuroticism, and an increase in negative affect, lack of

positive affect, and anxiety. Furthermore, high mastery protected against the negative impact of loss events, but neuroticism did

not augment the negative impact of threat events on emotional health.

Conclusion: Partial support was found for a diathesis–stress model of change in emotional functioning in late life. Furthermore,

support was found for distinguishing between symptoms of negative affect, depression, and anxiety.

D 2004 Published by Elsevier B.V.

Keywords: Anxiety; Depression; Risk factors; Vulnerability; Life events; Multilevel analysis

* Corresponding author. Tel.: +31 71 526 3416; fax: +31 71 524 8156.

E-mail address: e.de_beurs@lumc.nl (E. de Beurs).

0165-0327/$ - s

doi:10.1016/j.jad

ders 84 (2005) 53–62

ee front matter D 2004 Published by Elsevier B.V.

.2004.09.006

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–6254

1. Introduction

Anxiety and depression are the most prevalent

psychological problems in late life. Traditionally,

research into emotional aspects of the aging process

focused on depression. However, recently, studies

have been undertaken investigating anxiety in late

life, and knowledge regarding the prevalence and

comorbidity patterns of anxiety in older persons is

growing (Flint, 1994; Fuentes and Cox, 1997). These

studies show that anxiety disorders are quite prev-

alent among older persons. In an overview, the 6

months prevalence of anxiety in older persons was

estimated at 10% (Flint, 1994). Although prevalence

rates for major depression among older persons are

generally lower (ranging between 0.5 and 3%), an

estimated 10% to 15% suffers from sufficient

depressive symptoms to have a significant dimin-

ished quality of life and increased medical con-

sumption (Beekman et al., 1999). Similar findings

regarding the impact of anxiety disorders in late life

have been reported (de Beurs et al., 1999; Flint,

1994).

Commonly, a strong association between depres-

sion and anxiety is reported; correlation coefficients

between self-report measures for depression and

anxiety usually range from r=0.50 to r=0.70.

Although this may in part be explained by lack of

specificity of these measures for depression and

anxiety (Clark and Watson, 1991), there is also

considerable true overlap in symptoms between both

disorders. Furthermore, there is a high comorbidity

of anxiety and depression at the disorder or caseness

level (Barbee, 1998), especially in late life (Kirby et

al., 1997). Among elderly, about 50% of the

clinically depressed suffers from comorbid anxiety

disorders, and 25% of patients with anxiety suffers

from major depression (Beekman et al., 2000).

Finally, depression and anxiety respond equally well

to similar therapeutic interventions, such as Selective

Serotonin Reuptake Inhibitors, further blurring a

distinction between both disorders. Current knowl-

edge on the interplay of depression and anxiety in

late life is limited. The scarce available data suggest

that distinctive features of depression and anxiety

become even less pronounced with rising age

(MacKinnon et al., 1994). Findings such as these

raise doubt on the usefulness of distinguishing

between both conditions (Tyrer, 1989) and made

some researchers suggest that a dimensional

approach to affective psychopathology would do

more justice to the state of affairs (Andrews, 1996;

Ormel et al., 1995).

To explain the high comorbidity and high

concurrence of symptoms in anxiety and depression,

Clark and Watson (1991) proposed a tripartite model,

postulating three dimensions for symptoms commonly

found in patients suffering from depression and/or

anxiety disorders. The model states that anxiety and

depression share a common component, negative

affectivity (NA) with presumably a genetic/temper-

amental background (Clark and Watson, 1991; Wat-

son and Clark, 1984). This general dimension can be

considered as a core component of anxiety disorders

and depressive disorders (Brown et al., 1998) and

consists of symptoms such as feeling depressed,

hopeless, sad, afraid, and nervous. The second

dimension comprises symptoms specific to depres-

sion, which they named positive affect (PA). Rela-

tively unique to depression is a lack of emotional

states such as feeling good about oneself and feeling

optimistic or successful; the third dimension consists

of symptoms specific to anxiety, predominantly

somatic symptoms of anxiety and therefore named

physiological hyperarousal or Somatic Anxiety (SA)

(Keogh and Reidy, 2000).

An important aspect on which these dimensions of

anxious and depressive symptomatology may be

distinguished are the risk profiles they are associated

with. Some vulnerability factors or life events may be

uniquely associated with negative affect, while others

rather predict lack of positive affect or somatic

anxiety symptoms. The predominant model for the

etiology of psychopathology is the diathesis–stress

model (Zuckerman, 1999). Initially formulated to

describe risk factors of schizophrenia, the model has

been applied with success to study etiological factors

in depression and anxiety, where it became known as

the vulnerability–stress model (Brown and Harris,

1978; Goldberg and Huxley, 1992). Basically, the

model states that destabilization (getting symptoms) is

the result of long-lasting vulnerability factors, acting

in concert with exposure to environmental stressors,

usually one or more highly stressful events. Regard-

ing the question why some persons develop depres-

sion whereas others develop anxiety, Finlay-Jones and

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–62 55

Brown (Finlay-Jones and Brown, 1981) suggested

that the type of event may be a decisive factor:

stressful life events involving loss (e.g., death of a

loved one, retirement) are more likely to lead to

depression, whereas stressful events involving threat

(e.g., being victimized by crime) are more likely to

lead to anxiety. Furthermore, interactions of these life

events and specific vulnerability factors are sug-

gested. Events involving loss would be especially

troublesome for subjects with a low sense of mastery,

whereas threat events would have a stronger impact

on subjects high in neuroticism. Put differently, the

model proposes a moderator effect of mastery and

neuroticism on the destabilizing effect of stressful life

events. The notion that low mastery or an external

locus of control is important for the development of

depression is founded in the work of Rotter (1975)

and can also be related to Seligman’s concept of

learned helplessness in animal models of depression

(Seligman, 1978). Also from other theoretical per-

spectives, a relation is proposed between depression

on the one hand and low mastery, low perceived

control, or dependency on the other (Beck, 1996;

Blatt and Zuroff, 1992). Experiencing adverse events

increases the risk for depression (Paykel, 2003),

especially in those persons who feel limited control

over their life’s course (Brown and Siegel, 1988).

High neuroticism is a notorious risk factor for both

depression and anxiety (Clark et al., 1994; Eysenck

and Eysenck, 1991; Zuckerman, 1999). The impor-

tance of threat operationalized as the perception of

looming vulnerability for the development of anxiety

has been underlined by Riskind (1997).

In the present study, the prognostic value of the

risk factors is assessed for change in negative affect,

positive affect, and somatic anxiety symptoms. Risk

profiles for these three groups of symptoms are

compared, evaluating main effects of risk factors

and their interactions. The main research questions are

the following: which factors predict a significant

increase of emotional problems in late life and what

decides whether the outcome of destabilization is

predominantly negative affect, lack of positive affect,

or somatic anxiety? These research questions are

broken down into the following:

(1) Are different long-standing vulnerability factors

involved for the three dimensions?

(2) Are certain types of stressful life events (loss vs.

threat events) specific for developing negative

affect, decreased positive affect, or somatic

anxiety symptoms?

(3) Do stressful events and vulnerability factors

(mastery*loss and neuroticism*threat) interact

in the predicted manner, or do they rather have

an additive effect on destabilization?

Data from the Longitudinal Aging Study Amster-

dam (LASA; Deeg et al., 1993) were used to

investigate risk factors for changes in negative

affect, positive affect, and somatic anxiety in the

elderly. LASA is a longitudinal community-based

study in a large representative sample of adults aged

55 to 85. In a previous cross-sectional study

(Beekman et al., 2000), clear differences were found

between subjects with a diagnosis of major depres-

sion and subjects with anxiety disorders. Major

depression was associated only with age and an

external locus of control, whereas having an anxiety

disorder was associated with a wide range of

vulnerability factors and stressors. Subjects with a

comorbid condition had again a quite distinct risk

profile from those with pure depression or anxiety

(Beekman et al., 2000). We also investigated the

development of depression and anxiety in longitu-

dinal data from two waves of the LASA study. We

used cutoff scores on symptom measures to delin-

eate adults as either anxious, depressed, or both.

Results revealed that depression and anxiety have

many risk factors in common, but specific risk

factors were also found, especially in subjects with

both depression and anxiety (de Beurs et al., 2001).

The present study builds on these findings by using

longitudinal data from three waves of LASA. A

different data analytic strategy is used, no longer

dichotomizing patients as disordered (yes–no) but

using the full range of scores on assessment

instruments. This approach is more suitable to test

the dimensional approach to psychopathology.

Moreover, this way of analyzing the data yields

more statistical power by preserving the continuous

character of the symptom scores. Emotional prob-

lems were conceptualized according to the tripartite

model for negative emotional states, distinguishing

negative affect, lack of positive affect, and somatic

anxiety.

Table 1

Descriptives of the sample at baseline and 6 years later

T1 T3

N 3107 1837

Negative affect, mean (S.D.) 1.72 (2.87) 1.80 (2.74)

(Lack of) Positive affect,

mean (S.D.)

3.28 (3.04) 3.53 (3.02)

Somatic anxiety, mean (S.D.) 2.53 (3.30) 3.12 (3.58)

Sex

Male 1506 (48.5%) 816 (44.4%)

Female 1601 (51.5%) 1021 (55.6%)

Marital status

Married 1942 (62.7%) 1236 (67.3%)

Unmarried 1165 (37.3%) 601 (32.7%)

Age, mean (S.D.) 70.8 (8.8) 71.1 (8.1)

SES, mean (S.D.) 33.7 (19.3) 29.9 (19.0)

Education

Low 1376 (44.3%) 713 (38.8%)

Middle 1370 (44.1%) 908 (49.4%)

High 353 (11.4%) 216 (11.8%)

MMSE, mean (S.D.) 26.6 (3.8) 27.4 (2.9)

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–6256

2. Method

2.1. Sample and procedure

Data for LASA were collected by interviewing

participants in their homes by trained and intensively

supervised interviewers. All interviews were audio-

taped to allow random quality checks. In 1992, a

random sample of older (55–85 years) men and

women stratified for age and sex was drawn from

the population registers of 11 municipalities in three

regions of The Netherlands. Older men were initially

oversampled to ensure sufficient participants in these

strata for a later phase of the study. In the first cycle of

LASA (T1), 3107 participants were interviewed. This

sample has been described extensively in previous

publications of LASA (Beekman et al., 1995; de

Beurs et al., 1999; Deeg and Westendorp-de Seriere,

1994). Three years later (T2), the participants were

contacted again, and 2302 (74%) were willing and

still able to be interviewed again. When we contacted

the participants again in 1998–1999, 2076 (66.8%) of

the initial sample could be interviewed again. Of the

1031 nonrespondents, 761 (24.5% of the T1 sample)

had died, 81 (2.6%) were too ill or cognitively

impaired to be interviewed, 160 (5.2%) indicated that

they were no longer interested in participating in the

study, and 29 (0.9%) could not be contacted. Due to

item nonresponse on measures for depression and

anxiety at T1, T2, or T3, a further 239 subjects were

lost, leaving 1837 subject for whom scores on

emotional functioning were available at all time

points (60.1% of the T1 participants). The present

analysis was performed on this sample.

The 1270 nonrespondents were compared with the

1837 participants on key variables to check for

selective attrition. No significant difference was found

between participants and nonrespondents regarding

anxiety symptoms, but lower positive affect [t(3105)=

7.43; pb0.001] and higher negative affect [t(3105)=

6.59; pb0.001] at T1 did make attrition more likely.

For other variables, we also found an association with

attrition: nonrespondents were more likely to be male

[v2(1)=22.7; pb0.001], unmarried [v2(1)=32.3; pb

0.001], older [t(3105)=21.8; pb0.001], had lower so-

cioeconomic status (SES; t=9.05; pb0.001), less edu-

cation [v2(2)=60.7; pb0.001], and a lower score on

the Mini Mental State Exam (MMSE) [t(3105)=23.5;

pb0.001]. Thus, the subjects who were lost from T1 to

T3 comprised the less healthy and worse functioning

part of the initial participants at T1. Baseline

characteristics of the baseline sample and the final

study sample are presented in Table 1.

3. Measures

3.1. Negative affect, lack of positive affect, and

somatic anxiety symptoms

In LASA, depressive symptoms were measured

with the Center for Epidemiological Studies Depres-

sion scale (CES-D; Radloff, 1977). This 20-item

scale comprises Likert-type items which describe

feelings such as depression, hopelessness, and the

blues. The respondent is asked to indicate whether

these feelings were experienced in the past week on

a four-point scale, ranging from 0=brarely or neverQto 3=balways or almost always.Q Two subscales of

the CES-D were used. To assess negative affect, we

used a subscale of seven items: having the blues,

feeling depressed, life is a failure, feeling fearful.

Lack of positive affect was assessed with four items:

feeling as good as others, hopeful about the future,

being happy, enjoying life. Thus, we limited use of

the available CES-D data to two of the four sub-

scales of this instrument. These two subscales mea-

Fig. 1. Model for the association between predictors and change in

emotional functioning.

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–62 57

sure the closest intended concepts of negative affect

and lack of positive affect.

Anxiety was measured with the anxiety subscale of

the Hospital Anxiety and Depression Scale (HADS-A;

Zigmond and Snaith, 1983). The HADS-A comprises

seven Likert-type items in which the respondent is

asked to indicate whether he/she has experienced

feelings such as restlessness, tenseness, or panic on a

scale scoring from 0=bseldom or neverQ to 3=balwaysor almost always.Q The anxiety subscale score has a

theoretical range from 0 to 21.

3.2. Risk factors

Two stable psychological characteristics of the

participants were assessed: mastery and neuroticism.

Mastery was assessed in the interview with a five-

item scale adapted from Pearlin and Scooler (1978).

A higher score means a more external locus of control

or less mastery. Neuroticism (15 items) was measured

through the abbreviated subscale of the Dutch

Personality Inventory (Luteijn et al., 1985). This

self-report scale was completed after the interview

and mailed in by the respondent. Not all participants

complied: 138 of the 1837 participants (8%) failed to

return fully completed questionnaires. Nonresponse

on the self-report data was not related to sex of the

participant [v2(1)=0.92, p=0.34] but was related to

higher age [more nonresponse in older participants,

t(3105)=7.69; p=0.002].

3.3. Life events

In the T2 and T3 interviews, it was assessed

retrospectively whether stressful life events had

occurred in the 3-year time interval prior to the

interview. The following stressful events were

assessed: illness of one’s partner, death of one’s

partner, illness of a relative, death of a relative, a

major conflict with others, income loss (of at least $50

a month), victimized by crime, and relocation. To

investigate the impact of these life events, we

constructed two composites: one for events associated

with loss (e.g., death of a partner or relative) and one

for events associated with threat (e.g., illness of a

partner or relative, crime). Composites scores were

made by differentially weighting life events and

combining them in one score, representing the impact

of the events. Weights for various life events were

derived from Tennant and Andrews (Tennant and

Andrews, 1976). As both composites had a skewed

and peaked distribution, they were log-transformed to

approach a normal distribution.

All assessment instruments used in the study had

been previously validated in The Netherlands or their

psychometric properties had been evaluated for their

use in the older population in LASA pilot studies

(Deeg et al., 1993).

3.4. Statistical analysis

To examine the association between neuroticism,

mastery, and the outcome variables, multivariate

multilevel analysis were carried out. The general idea

behind using multilevel analysis for multivariate

problems is that the measurements of the different

outcome variables can be seen as dclusteredT withinthe subject (Goldstein, 1995). As this was a longi-

tudinal study, three levels of analysis can be distin-

guished: (1) the outcome variables negative affect,

lack of positive affect, and anxiety, (2) the observa-

tions at different time points, and (3) the participants.

This multivariate multilevel analysis is basically a

multivariate linear regression analysis. There is,

however, an additional level because we have

repeated observations within each participant. In

addition to the main effects for neuroticism and

mastery, the interaction between neuroticism*threat

and mastery*loss were added to the models. In a

second analysis, the association between the predictor

variables and the three outcome variables were

examined in separate multilevel analyses. Figs. 1

and 2 present the associations of main interest for a

simple model with one outcome variable and for the

Fig. 2. Hypothesized model for the associations among predictors and three dependent variables.

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–6258

complete model. All analyses were adjusted for

gender, age, socioeconomic status, and health (num-

ber of somatic diseases) and were performed with

MLwiN (version 1.10.0007; Centre for Multilevel

Modeling, Institute of Education, London, UK). For

socioeconomic status, we used a weighted score

composed of level of education, occupation, and

income (range 0–100; van Tilburg et al., 1995).

4. Results

First, the complete model was analyzed. Results

are presented in Table 2. Overall, adjustment for

control variables (age, sex, and SES) did not change

the results of the analyses in a meaningful way. The

results of analysis of the entire model revealed main

Table 2

Results of multivariate multilevel analyses (main effects)

Unadjusted Adjusteda

B 95% CI p B 95% CI p

Mastery �0.15 �0.13 to

�0.17

b0.001 �0.13 �0.11 to

�0.15

b0.001

Neuroticism 0.10 0.09 to

0.11

b0.001 0.09 0.08 to

0.11

b0.001

a Adjusted for sex, age, socioeconomic status, and health of the

respondent.

effects of mastery ( pb0.001) and neuroticism

( pb0.001) on deterioration of emotional functioning

(the overall outcome, not distinguishing negative

affect, lack of positive affect and anxiety). Less

mastery and higher neuroticism were significantly

associated with decreased emotional well-being (see

Table 2). Furthermore, a significant interaction effect

of mastery and loss events (B=0.002; CI=0.001–

0.003; p=0.002) was found. Apparently, loss events

have a greater impact for participants who report less

mastery. This finding is in accordance with our

prediction. However, the predicted interaction bet-

ween neuroticism and threat events is not supported

by the data since this interaction failed to reach

significance (B=0.001, p=0.44).

Finding significant effects in the overall model

justifies a closer look into the associations by

analyzing three models separately, one for each

dependent variable. Table 3 presents the results for

main effects in the separate models for general

negative affect, lack of positive affect, and somatic

anxiety.

Regarding main effects, the results reveal that

general negative affect has a positive association with

neuroticism and an equally strong but negative associ-

ation with mastery (B=0.09 and B=�0.14, respec-

tively). Lack of positive affect (specific to depression)

was associated with low mastery. Neuroticism was also

Table 3

Results of multilevel analyses for three outcomes (main effects and interaction effects)

Unadjusted Adjusteda

B 95% CI p B 95% CI p

Negative affect

Mastery �0.14 �0.11 to �0.16 b0.001 0.12 �0.10 to �0.15 b0.001

Neuroticism 0.09 0.07 to 0.10 b0.001 0.09 0.07 to 0.10 b0.001

Interaction effects

Significant interaction between loss and mastery ( pb0.011)

No significant interaction between threat and neuroticism ( p=0.90)

Lack of positive affect

Mastery �0.17 �0.14 to �0.19 b0.001 �0.15 �0.12 to �0.17 b0.001

Neuroticism 0.09 0.08 to 0.11 b0.001 0.09 0.07 to 0.10 b0.001

Interaction affects

No significant interaction between loss and mastery ( p=0.34)

No significant interaction between threat and neuroticism ( p=0.25)

Somatic anxiety

Mastery �0.14 �0.11 to �0.17 b0.001 �0.13 �0.10 to �0.16 b0.001

Neuroticism 0.13 0.11 to 0.15 b0.001 0.13 0.11 to 0.15 b0.001

Interaction affects

Significant interaction between loss and mastery ( pb0.001)

No significant interaction between threat and neuroticism ( p=0.98)

a Adjusted for sex, age, socioeconomic status, and health of the respondent.

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–62 59

associated with lack of positive affect but according to

the regression coefficients (B) to a somewhat lesser

extent than mastery (B=0.09 vs. B=�0.17). In contrast,

high somatic anxiety was equally strongly associated

with high neuroticism and lowmastery (B=0.13 andB=

�0.14). Controlling for sex, age, education, SES, and

health did not alter these results in a meaningful way.

Regarding interaction affects of personality charac-

teristics and both type of events, the results reveal some

significant associations. No modifying effect of mas-

tery or neuroticism on events leading to decreased

positive affect is apparent in the data. Mastery

moderates the impact of loss on somatic anxiety ( pb

0.001), and the same interaction effect is found with

negative affect as outcome variable ( p=0.011). The

predicted interaction effect of threat events and neu-

roticism on somatic anxiety was not found in the data.

In general, the findings of the overall model and

the three separate analyses converge: of the two

predictors, mastery has the strongest association with

the outcome variables. However, when comparing the

strength of the associations of mastery and neuroti-

cism for the three dimensions of psychopathology

according to the tripartite model, neuroticism has the

strongest association with somatic anxiety, a finding

in accordance with the hypothesized distinctness of

these three dimensions.

The interaction of neuroticism and threat events is

not found in the overall model and neither in the

analyses of dependent variables separately. Instead,

mastery modifies the effects of loss events on somatic

anxiety ( pb0.001) and, to a lesser extent, on negative

affect ( p=0.011). The direction of the interaction

effect of mastery and loss events on anxiety is as one

would expect: high mastery protects for the effect of

loss events.

5. Discussion

Overall, support has been found for the proposed

model predicting different pathways for symptoms of

depression, anxiety, and general negative affect.

Increases in anxiety and in negative affect were both

associated with an interaction effect of life events

involving loss and low mastery. Contrary to our

hypothesis, no significant interaction effect was found

between neuroticism and negative life events involving

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–6260

threat. What do the present finding reveal about the

validity of the tripartite model for anxiety and

depression in late life? The findings suggest clearly

explanatory power for the present model. By demon-

strating different effects for risk factors on depression,

anxiety, and general negative affect, the findings

underline the validity of separating out these distinct

groups of symptoms according to the tripartite model.

Furthermore, distinguishing vulnerability in lack of

mastery and high neuroticism proved fruitful given the

distinct outcomes for these variables: mastery appeared

a better predictor of decreased negative affect than

neuroticism. The same holds for distinguishing

between loss and threat events.

In spite of the general support for the proposed

model, differences among predicting variables for

distinct outcomes were modest (e.g., B=�0.09 vs.

B=0.14). In interpreting this outcome, one should also

bear in mind that the present model for developing

emotional problems or destabilization in late life is far

from complete. The decisive factor for whether the

outcome of life events and vulnerability is depression

or anxiety may very well be of a biological (e.g.,

genetic (Kendler et al., 2001)) or social nature.

Regarding the latter, the buffering effect of an

extensive social network on the impact of negative

life event is well documented, in part by studies on

data from LASA (Penninx et al., 1998). Regarding the

former, we have previously reported on the profound

impact of physical health on anxiety (de Beurs et al.,

2000). Other biological factors, such as HPA-axis

functioning in depression, are currently under study.

These factors were not included in the present

analysis. More conclusive evidence regarding the

utility of the tripartite model for a dimensional

conceptualization of psychopathology will come from

studies linking the dimensions to biological factors or

to response to interventions in clinical populations.

The present findings may have been influenced by

a potential lack of variance in our composite scores

for events. Particularly, the composite for threat events

yielded low scores. For instance, very few subjects

reported being victimized by crime. Furthermore, by

their very nature, loss events may have a stronger

impact than stress events. For instance, mourning a

close relative has a greater impact on emotional

functioning as compared to the same relative falling

ill (a threat event mirroring losing a relative).

Furthermore, life events were assessed by putting

information from different sections of the interview

together. Potentially, a more thorough assessment of

events would have yielded different results. (e.g., the

life history calendar approach to assessing life events

(Caspi et al., 1996).

Furthermore, the lack of support for some of our

predictions, especially those regarding distinct pre-

dictions for somatic anxiety and lack of positive affect

may be due to the fact that the present study was

undertaken in a nonclinical elderly population. The

present sample was population-based. Moreover, as

time progressed, it comprised predominantly of those

with the best chances of survival. The hypotheses may

get more support when studied in a patient group,

where symptom profiles will be more clearly distinct

and where potentially more aggravating life events

will be reported.

Another limitation to the present study was the use

of subscales of the CES-D and the HADS-A to

measure symptoms according to the tripartite model.

Although both instruments are well researched and

valid, they are not the best choice for an optimum

distinction between the symptoms of anxiety and

depression. The subscales of the MASQ (Watson et

al., 1995) or the Beck Depression Inventory and the

Beck Anxiety Inventory (Beck et al., 1961; Beck and

Steer, 1990) show less concordance between anxiety

and depression and may have yielded more pro-

nounced differences between correlates of depression

and anxiety than the subscales of the CES-D and

HADS-A. Future research with a dependent variable

that is better suited for distinguishing the three factors

of the tripartite model may yield more clear-cut results.

In addition, the predictive power of the model might be

improved by incorporating additional predictors.

Promising predictors could be found in the biological

realm (Charney, 2004) or in other psychological traits,

such as attributional style or cognitive biases, that

produce vulnerability for the development of psycho-

pathology. Currently, in The Netherlands, three uni-

versities have started a collaborative effort to study

(determinants of) the course of depression and anxiety

in primary and secondary care patients in a longitudi-

nal design (NESDA). A large number of patients will

be repeatedly assessed over a 10-year time span. Data

will be gathered on diagnostic status, symptoms of

anxiety and depression, biological parameters, such as

E. de Beurs et al. / Journal of Affective Disorders 84 (2005) 53–62 61

cortisol, and psychological parameters (personality

traits and other vulnerability factors such as anxiety

sensitivity). Availability of these data will allow testing

a more comprehensive model for different age groups.

6. Conclusion

The present findings lend partial support to the

diathesis–stress model. Low mastery and neuroticism

are both associated with a decrease in emotional well-

being over time, mastery most strongly with depres-

sion, and neuroticism with anxiety. The predicted

modifying effect of neuroticism on the association

between threat events and anxiety was not corrobo-

rated by the data. However, the significant interaction

between mastery and loss events delineates those

specifically at risk: individuals who experience

negative life events and tend not to feel in control

of their lives. A possible clinical implication of this

finding is that efforts to increase perceived control,

e.g., through cognitive behavior therapy, may enhance

the outcome of pharmacological treatment for depres-

sion in late life and may prevent relapse after

successful therapy. Finally, the study findings support

distinguishing three types of symptoms: negative

affect, lack of positive affect, and anxiety.

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