Institute for Research in Extramural Medicine & Department of Psychiatry, Vrije Universiteit, Amsterdam
Correspondence: Edwin de Beurs, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
Declaration of interest Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims Delineating risk factors for the decline of mental health in older persons, comparing risk profiles for developing symptoms of pure depression, pure anxiety and both anxiety and depression in a prospective design.
Method Self-report data on depression and anxiety were collected
from community-dwelling older respondents ( 55 years) on two occasions, 3
years apart. Data from emotionally healthy respondents (n=1810) were
used to investigate the effects of long-standing vulnerability factors and
stressful life events.
Results After 3 years 9% of the subjects had scored beyond the thresholds for symptoms. Vulnerability for depression and anxiety was quite similar, but life events differed: onset of depression was predicted by death of a partner or other relatives; onset of anxiety was best predicted by having a partner who developed a major illness. No support for moderator effects between vulnerability factors and stress was found; the effects were purely additive.
Conclusions Depression and anxiety have many risk factors in common, but specific risk factors also were found, especially in subjects developing both depression and anxiety.
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INTRODUCTION |
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METHOD |
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At T1 120 respondents (5.5%) had depression symptoms, 84 (4.0%) had anxiety symptoms and 147 (6.8%) had both depression and anxiety symptoms. Because we aimed to investigate becoming depressed or anxious, respondents with symptoms were removed from the sample, leaving 1810 respondents. Descriptive statistics and data on health and functioning of the final study sample are presented in Table 1.
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Measures
Depression and anxiety
Depression was measured with the Center for Epidemiological Studies
Depression scale (CES-D; Radloff,
1977). Depressive symptoms were considered present if the CES-D
score was 16. Anxiety was measured with the Anxiety sub-scale of the
Hospital Anxiety and Depression Scale (HADS-A;
Zigmond & Snaith, 1983). On the HADS-A the recommended cut-off of
7 was applied to decide whether
a respondent developed symptoms of anxiety or not. However, merely crossing
the cutoff on the CES-D or HADS-A at T2 was deemed
insufficient to consider a respondent changed or destabilised, because it can
result from random fluctuations due to measurement error on the symptom scale.
Therefore, the additional requirement of statistically reliable change was
set. To be considered reliably changed, a respondent has to change beyond the
standard error of the difference score from T1 to
T2 (Speer,
1992). For our respondents this implied a change of at least seven
scale points on the CES-D and four scale points on the HADS-A. Subjects who
crossed the cut-off but failed to meet the requirement of statistically
reliable change were considered unchanged and categorised as below
threshold.
Vulnerability
The following four sets of variables, all measured at
T1, were selected as vulnerability factors for depression
and anxiety: demographics, variables regarding health and functioning,
personality characteristics and social functioning.
Demographic vulnerability factors included female gender, higher age, not/no longer married, living in Amsterdam and lower socio-economic status. We used a weighted score composed of level of education, occupation and income (range 0-100) as a measure of socio-economic status (van Tilburg et al, 1995).
Variables regarding health and functioning were included as a separate set of vulnerability factors. In the stress-vulnerability model, somatic illness usually is considered a stressor and is included as such among the stressful life events. However, in view of the fact that health declines during old age often are gradual, ill health and functional limitations also may act as age-specific vulnerability factors. Physical health status was determined in the interview and cross-checked with information from general practitioners (Kriegsman et al, 1996). Physical health includes the number of chronic diseases reported by the respondent, a self-rated health assessment using a single item (Centraal Bureau voor de Statistiek, 1989) and functional limitations, assessed with an adaptation of the Organisation of Economic Collaboration and Development (OECD) Questionnaire (van Sonsbeek, 1988; Kriegsman et al, 1997). Problems with perception (eyesight and hearing) were assessed in the interview by asking the respondent whether they could see/hear "well enough" on a four-point scale ("Yes, no difficulty" to "No, I cannot see/hear"; Centraal Bureau voor de Statistiek, 1989). Responses were recoded into one variable with two levels (no or minor problems v. much difficulty or inability with either eye-sight or hearing). Cognitive functioning was assessed with the MMSE.
Three personality characteristics of the respondents were assessed: mastery, neuroticism and self-efficacy. Mastery was assessed in the interview with the abbreviated five-item locus of control scale (Pearlin & Scooler, 1978). A higher score means a more external locus of control or less mastery. Neuroticism (15 items) was measured through the abbreviated sub-scale 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 respondents complied: 540 of the 2163 respondents (25%) failed to return fully completed questionnaires. Non-response on the self-report data was not related to the gender of the respondent but was related to higher age (more non-response in older respondents). Finally, coping was measured in the interview with a 12-item version of the General Self-efficacy Scale (Sherer et al, 1982; Bosscher & Smit, 1998).
Social resources were assessed by estimating the size of the social network. Respondents were asked to name people they regularly socialised with and whom they deemed important in various domains of life (relatives, neighbours, work, church, etc). The validity of the network size index was supported in a previous study (van Tilburg, 1994). Also, respondents were questioned about the exchange of emotional support with key members of their social network. Because "emotional support received" could be an important protective factor for developing psychopathology, in particular depression, this variable was included in the analyses as well.
Life events
In the T2 interview it was assessed retrospectively
whether stressful life events had occurred in the time interval between
T1 and T2. Regarding the question of
why some people develop depression whereas others develop anxiety,
Finley-Jones & Brown
(1981) have 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 a victim of crime) lead
to anxiety. 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 £30 a month), being
a victim of crime and relocation. Life events were analysed individually and
we also obtained a single composite score for stress by differentially
weighting life events. Weights for various life events were derived from
Tennant & Andrews
(1976).
All assessment instruments used in the study had been validated previously in The Netherlands or their psychometric properties had been evaluated in LASA pilot studies (Deeg et al, 1993).
Statistical analyses
A series of multivariate logistic regression analyses were undertaken, each
time comparing one of the symptom groups with the non-symptomatic controls.
First, vulnerability factors were analysed in four sets of conceptually
related variables: demographics, health and functioning, personality and
social functioning as measured at T1. Thus, variables
could be found that were associated significantly with destabilisation, while
controlling for the effect of other variables within the same set. This
approach limits the number of predictor variables and decreases the risk of
collinearity among predictors. Next, the association of each life event and
destabilisation for each symptom group was analysed with multiple logistic
regression analyses. Finally, in order to attain the most parsimonious set of
predictors, we used only the variables that appeared to have predictive value
in previous analyses and performed a series of stepwise logistic regression
analyses using a forward inclusion criterion of P < 0.20
(Menard, 1995).
To test hypotheses regarding interaction of vulnerability and stress, the interaction term was added to the main effects for each of the three models (Baron & Kenny, 1986; Hosmer & Lemeshow, 1989). In these analyses, we used the composite score for stressful life events.
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RESULTS |
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Vulnerability to becoming depressed
Demographics, health and functioning personality and social
functioning
Table 2 presents the results
of multiple logistic regression analyses of variables representing
vulnerability. The results indicate that for all three symptom groups the
initial symptom level (averaged score on the CES-D and HADS-A at
T1) was predictive of destabilisation. For demographic
variables the findings show that gender, age and socio-economic status were
associated with scoring beyond threshold: females were overrepresented among
the purely depressed and the purely anxious; the older old were more likely to
be purely depressed; and low socio-economic status increased the chance for
depression with anxiety. Results for social functioning were mixed: a smaller
social network was predictive of becoming depressed, but not anxious, whereas
less emotional support was predictive of anxiety but not depression. Social
functioning was not a predictive factor for getting symptoms of both
depression and anxiety. Regarding health status and functioning, we found that
worse self-rated health predicted pure depression and pure anxiety, but not
both anxiety and depression. Furthermore, functional limitations predicted the
onset of depression and hearing/eyesight problems predicted the onset of both
depression and anxiety. Of the personality variables, neuroticism was
predictive of symptoms, especially for the group scoring beyond threshold on
both depression and anxiety. Self-efficacy was predictive in all groups that
scored beyond threshold at T2.
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Stepwise multivariate analyses
Next we evaluated all variables that significantly predicted scoring beyond
threshold in three stepwise logistic regression analyses. For pure depression,
the number of significantly predictive variables was reduced from eight to
five (female gender, higher age, worse self-rated health, more functional
limitations, and neuroticism). The likelihood ratio of the final model was
2 (6)=75.0, pseudo R2=0.16. Four variables
remained to predict anxiety (higher initial symptom level, female gender, less
received emotional support and lower self-efficacy). The likelihood ratio of
this model was
2 (4)=34.2, pseudo R2=0.11.
Getting symptoms of both anxiety and depression was predicted by four
variables (higher initial symptom level, lower socio-economic status, having
hearing or eyesight problems and neuroticism); the likelihood ratio was
2 (5)=40.2, pseudo R2=0.12. All of the
stepwise logistic regression analyses were repeated while omitting neuroticism
(the variable was 25% missing values owing to non-response). The pattern of
associations of the remaining variables on this larger sample did not differ
meaningfully from the results described above. By and large, the findings of
the stepwise analyses concur with the findings when vulnerability factors were
analysed in sets. Apparently, most of the significant predictors of
Table 2 have independent
predictive value for destabilisation.
Life events associated with depression and anxiety
Stressful life events
Next, the predictive value of stressful life events that occurred in the
time interval between both assessments was evaluated. Odds ratios were
calculated representing the risk of crossing the threshold when an event had
occurred. Table 3 presents the
frequency of occurrence of events in the full sample and their odds ratios
(with 95% CIs) for each of the three symptoms groups. Statistically
significant odds ratios are printed in bold typeface.
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To investigate which events had an association with destabilisation while controlling for the effects of other events, we also performed a multiple logistic regression with stepwise selection of events. For pure depression, death of the partner, death of another family member and a major conflict were associated with destabilisation. The main events associated with an increase in anxiety symptoms were illness of the partner or a family member and having had a major conflict. Finally, events associated with crossing the threshold for both depression and anxiety were the death of a family member and having been victimised by crime.
Interaction of vulnerability factors and stressful life events
Finally, interactions between significant vulnerability factors
(neuroticism, mastery, social network size and coping style) and a selected
set of stressful life events were studied. Low mastery was expected to amplify
the effect of stress due to loss, and high neuroticism was expected to amplify
the adverse effects of stress related to threat on mental health. Regarding
social functioning, a protective effect of a large social network was
hypothesised, moderating the adverse influence of stressful life events in
general. Likewise, higher self-efficacy was hypothesised to protect for the
effect of general stress. Hypotheses regarding effect modification were
investigated by testing the main effect for each pair of predictors, as well
as their interaction. Results showed that in analyses involving neuroticism
and mastery none of the interaction terms were significant. Thus, no
augmenting effect of neuroticism or low mastery on negative life events for
developing depression and/or anxiety symptoms was found. This finding
indicates that vulnerability factors and stressful life events, rather than
interacting, add to each other in increasing the odds for destabilisation.
Regarding the buffering effect of social functioning, only the interaction
between received emotional support and stress for developing pure anxiety was
marginally significant: respondents who reported more social support were less
likely to develop anxiety when faced with stressful events (standardised
ß=1.21, OR=3.3 (0.9-12.6), P=0.07). No significant interaction
of self-efficacy and general stress was found.
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DISCUSSION |
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Another cautionary remark regarding methodological aspects of the study concerns the status of life events as predictors. Most life events were assessed retrospectively at T2 and therefore are not predictors in the true sense of the word. Our hypothesis was that negative life events would increase the odds for getting symptoms. However, respondents who destabilised into depression might have had a better recollection for negative events (mood congruent recall; Bower, 1981), thus biasing the results in favour of the hypothesis. On the other hand the most significant events, such as the death of one's spouse, are unlikely to be influenced by recall bias. Nevertheless, a cautionary presentation of the present findings regarding life events describes them as associations rather than as directional relations. With these limitations in mind we will briefly review the most interesting findings.
Variables predictive of getting depression and/or anxiety
symptoms
Important vulnerability factors for getting symptoms were female gender,
high neuroticism and worse self-rated health. Generally, epidemiological
studies report a higher prevalence of depression and anxiety among women. High
neuroticism was predictive for all symptom groups. Of course, neuroticism was
associated with depression or anxiety level at baseline (cf.
Clark et al, 1994).
The present findings reveal the prognostic value of neuroticism for
developing emotional problems in a prospective design. Similar findings have
been reported for younger age groups. Duncan-Jones
(1987) reported the findings
of a longitudinal study in an Australian sample of mixed-age adults where
fluctuations in symptoms of psychopathology were well predicted by neuroticism
scores. Ormel & Schaufeli
(1991) replicated these
findings in a sample of college students. The present findings complement this
literature, by demonstrating the importance of premorbid personality
characteristics to emotional problems in late life.
Analysis of the vulnerability factors regarding health and functioning in late life revealed self-perceived poor health as a better predictor for mental health decline than chronic diseases. Apparently, how respondents experience their own health predicts subsequent emotional functioning more strongly than their objective health status. Similar findings were reported by Bath & Morgan (1998). In contrast, with mixed-age groups many studies report a strong effect of somatic illness on emotional functioning (Viney & Westbrook, 1981). The adverse effect of a physical illness on emotional functioning may diminish with rising age, because in late life chronic diseases are much more common and accepted as a fact of life.
Regarding the specificity of vulnerability factors for either depression or anxiety, the similarity of risk profiles for the groups outweighs dissimilarity. However, some discrepancies are worth noting. Higher age was predictive only of depression and remained so after controlling for other factors, such as poorer self-rated health. This finding is in line with the literature documenting that the likelihood of depression increases with older age (Beekman et al, 1999). Functional limitations at baseline also were specifically associated with depression and not anxiety. Functional limitations have been implicated in depression among older persons previously. Regarding social functioning, network size and amount of emotional support traded places in predicting depression and anxiety. This finding underlines the multi-dimensional nature of social support (Cohen & Wills, 1985).
Recent stressful life events
Partial support for the hypothesised specificity of loss v. threat
events for depression and anxiety was found: loss events (e.g. the death of a
family member) were associated with becoming depressed, whereas threat (e.g. a
family member getting a major illness) was predictive of becoming anxious. The
significant association between death of the partner and depression may in
part reflect bereavement rather than depression
(Prince et al, 1997). However, in additional analyses, leaving out the respondents who lost their
spouse in the previous 6 months, death of the partner was still a significant
predictor of symptoms of depression. Unexpectedly, being a victim of crime
(obviously a threat event) was associated with getting symptoms of both
anxiety and depression. Apparently, this event, although seldom occurring in
the life of Dutch citizens, has a quite pervasive influence.
The distinctness of risk profiles for depression and anxiety in older persons underlines the validity of distinguishing these clusters of symptoms. It has been argued that this distinction diminishes in late life, where depression and anxiety are often found as comorbid conditions. The present results show that depression and anxiety share common vulnerability factors, but also that distinct stressful events produce different outcomes.
Neuroticism, mastery, social support and self-efficacy as effect
modifiers
The stress-vulnerability model hypothesises an augmenting effect of high
neuroticism and low mastery (Goldberg
& Huxley, 1992) and a buffering effect of social support for
the effects of life events (Brown &
Harris, 1978). Although strong direct effects of neuroticism and
distress on destabilisation were found, no evidence for significant
interactions with stress were attained. The more specific hypotheses linking
neuroticism with threat events and mastery with loss events were not supported
either. Apparently, the adverse effects of neuroticism and life's stress add
on to each other, rather than amplify their mutual effects. The results
regarding social functioning were similar. Analyses revealed only a marginally
significant interaction effect of emotional support and distress for
developing anxiety symptoms, indicating that more emotional support buffers
the effect of adverse life events. No other interaction terms were
significant. The main effects of social support on the deterioration of mental
health also were small, which is in line with recent findings
(Olstad et al, 1999).
Overall, the present results do not lend support to the interaction hypothesis
of the stress-vulnerability model.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication January 5, 2001. Revision received May 11, 2001. Accepted for publication May 17, 2001.
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