Division of Psychiatry, University of Auckland, New Zealand
Department of Psychological Medicine, Guy's, King's and St Thomas' School of Medicine and Institute of Psychiatry, London, UK
Section of Epidemiology, Institute of Psychiatry, London, UK
Correspondence: Dr Melanie Abas, Research and Audit in Mental Health Services Team, Tiaho Mai, Middlemore Hospital, South Auckland, New Zealand. E-mail: m.abas{at}auckland.ac.nz
Declaration of interest Funded by the UK Medical Research Council. M.A. has received an educational award from Eli Lilly Ltd.
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ABSTRACT |
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Aims To measure the effect of depression on mortality after controlling for cognitive decline, cardiovascular risk factors and antidepressant use.
Method A prospective cohort study derived from data from a multi-centre randomised controlled trial of moderate hypertension. A total of 2584 participants, aged 65-75 years at study entry, were followed up for 11 years.
Results Depression on the SelfCARED scale was associated with mortality after controlling for gender. After controlling for cardiovascular risk factors, cognitive decline and antidepressant use, depression continued to have a modest effect (hazard ratio=1.43; 95% C11.03-1.98). Depression in males and in people aged under 70 years significantly increased the risk of death.
Conclusions Depression was associated with mortality only after controlling for gender. There was a modest but robust association between depression and mortality that was not explained by confounding by cardiovascular risk factors, cognitive decline or history of antidepressant use.
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INTRODUCTION |
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METHOD |
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Data on a range of variables were collected at baseline. Some variables were also measured at the 1-, 9-, 21- and 54-month follow-up assessments. Patients were randomised to three groups: beta-blocker (atenolol, 50 mg daily), thiazide diuretic (hydrochlorothiazide, 25 mg or 50 mg, plus amiloride, 2.5 or 5 mg daily) or placebo. The results of the main study have been published elsewhere (MRC Working Party, 1992). In summary, both treatments reduced blood pressure compared with placebo. Furthermore, the diuretic group, but not the beta-blocker group, had significantly reduced risks of stroke, coronary events and all cardiovascular events, compared with placebo.
Participants
The subjects for the current paper were those who took part in the
psychiatric substudy, namely the first 2680 recruits for the main study. Of
these 2680, 29 refused to participate. Of the 2651 who agreed, 2584 (97.5%)
contributed adequate data on the main explanatory measures. These constitute
the current sample.
Measures
Depression status
Depression was measured on a validated 12-item depression scale, the
SelfCARED. This is a self-administered depression scale derived from
the Comprehensive Assessment and Referral Evaluation depression scale and was
developed specifically for use in elderly subjects in the primary care setting
(Bird et al, 1987). Each of the 12 questions are scored either 0 or 1, therefore scores are in the
range 0-12. In the present study, the SelfCARED was applied at entry
and at each subsequent follow-up. Bird et al
(1987) suggested that a cut-off
of 6 out of 12 is indicative of clinical depression in the general elderly
population. However, a subsequent study using the Geriatric Mental State (GMS;
Copeland et al, 1986)
as the gold standard found that the mean score for cases of depression was
7, with a specificity of only 45% for the
6 cut-off
(Blanchard et al,
1994). Another study carried out in elderly people with physical
illness recommended a cut-off of
7
(Banerjee et al,
1998). Consequently, we decided to explore the effect of
depression at two cut-offs of the scale:
6 (possible
depression) and
7 (depression). History of
antidepressant medication use was recorded at baseline and at each
follow-up.
Cognitive function at baseline
Cognitive decline
A summary score, the PALT coefficient, reflecting the change
in each subject's PALT score over time was calculated by deriving the
regression equation for the PALT score against time for each subject
(Prince et al, 1996).
A more positive PALT coefficient signifies better performance and therefore
less decline in cognition. The TMT was also measured at each wave of data
collection. The TMT was converted into a summary measure, the TMT
coefficient, to reflect the change in each subject's TMT score over
time (Prince et al,
1996). A more positive TMT coefficient signifies less improvement
with time and thus worse performance.
Cardiovascular risk factors
Smoking at time of entry to trial was coded as a binary variable
(smoker/non-smoker). Non-fasting random serum cholesterol was measured at
baseline. Systolic blood pressure was measured by trained research nurses as
the sitting blood pressure using a random-zero sphygmomanometer at entry and
each follow-up. Body mass index was measured at baseline. Electrocardiogram
(ECG) evidence of cardiac ischaemia or arrhythmia was measured using expert
analysis of 12-lead electrocardiography.
Statistical analyses
All analyses were carried out using STATA version 6
(StataCorp, 1999). Univariate
associations between the potential explanatory variables and mortality were
assessed using classical MantelHaenszel methods for rate ratios. Hazard
ratios were derived using Cox's regression
(Clayton & Hills, 1996).
Assessment of the proportional hazards assumptions was carried out using an
Aalen cumulative incidence plot, and a formal test for heterogeneity of the
effect of depression over thirds of the follow-up (each with an equal number
of deaths). The effect of each continuous and ordered categorical variable on
mortality was modelled first to assess whether a factor or linear relationship
was the best fit for each variable. Any departure from linearity was formally
tested using a likelihood ratio test. The survival probability was plotted for
those with and without depression at entry, with all other variables held
constant at baseline. Multivariate analyses were carried out using Cox
regression to build up a model for the effect of depression on mortality,
adding in potential confounding variables one at a time and assessing the
contribution of depression within the model following the addition of each
confounder using the likelihood ratio test. Potential interactions between
depression and any other explanatory variables were first identified by
looking for any suggestion of unequal rate ratios using classical
MantelHaenszel methods and then, if interaction appeared likely, by a
formal likelihood ratio test using Cox's regression.
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RESULTS |
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Proportional hazards assumptions
A formal test for heterogeneity of the effect of depression over thirds of
the follow-up (each with an equal number of deaths) showed no statistical
evidence of departure from the proportionality assumption
(2=0.99, P=0.609). Thus it was reasonable to use
Cox's proportional hazards to model the effect of depression on mortality.
Univariate associations between baseline variables and mortality
Table 2 describes the
association between the main variables and mortality. Depression was only
weakly associated when coded as a binary variable (P=0.07). Possible
depression was not associated with mortality. Not surprisingly, male gender,
older age, smoking, raised systolic blood pressure and ECG ischaemia were all
associated with mortality. Lower cholesterol levels were also associated with
increased mortality. More died in the beta-blocker group than in the diuretic
group (31% . 26%), with the placebo group intermediate.
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There was no association between mortality and baseline measures of intelligence and cognition. However, decline in cognitive performance over the course of the study was associated with mortality.
Association between depression and mortality controlled for
confounders
Table 3 shows the change in
the effect of depression on mortality when various potential confounders are
added to the model. Depression (i.e. scoring 7 on the depression scale)
becomes more powerfully associated once gender is controlled for. This
reflects the higher prevalence of depression in females and the higher death
rate in males. There was some confounding by cardiovascular risk factors and
by urban residence. The full model, which controlled for gender, age,
cardiovascular risk factors, cognitive decline and urban residence, showed
that depression was still modestly associated with mortality. The effect of
depression scored as a continuous variable was similar. Assuming an overall
prevalence of major depression of 5% and a hazard ratio of 1.43, we calculate
the population-attributable risk percentage of depression on mortality to be
2.1%.
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Possible depression (i.e. scoring 6 on depression scale) had a modest
effect on mortality after controlling for gender (hazard ratio=1.33; 95% CI
1.12-1.72, P=0.041). The relationship was confounded by
cardiovascular risk factors and by urban residence. After adjustment for all
these factors, the hazard ratio was 1.22 (95% CI 0.92-1.63,
P=0.18).
Interaction between depression and gender and depression and age
We detected an interaction term (2=3.05, 1 d.f.,
P=0.081) between depression and gender. Males with depression had
considerably increased risk of dying (hazard ratio=2.12, 95% CI 1.28-3.52)
even after adjustment for cardiovascular and cognitive risk factors and for
urban residence. In females the risk was not significantly increased (hazard
ratio=1.14, 95% CI 0.75-1.73). There was also a significant interaction term
between age and depression. Younger people with depression were at increased
risk (Table 4), but depression
in those aged over 70 years at baseline did not appear to be associated with
mortality.
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Antidepressant use and mortality
There were no significant associations between antidepressant use at trial
entry and mortality. The hazard ratio for antidepressant use at entry,
adjusted for gender, cardiovascular risk factors, age, urban residence and
depression score, was 1.01 (95% CI 0.65-1.55, P=0.99). The hazard
ratio for antidepressant use during the trial (linear increase in quarters),
adjusted for gender, cardiovascular risk factors, age, urban residence and
depression score, was 1.06 (95% CI 0.99-1.13, P=0.084).
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DISCUSSION |
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Study limitations
The study restricted the sample to a relatively healthy group. Thus, it is
unlikely that the association is due to the presence of physical illness among
those rated as depressed at baseline. However, there were potential
methodological flaws in the design of this study. First, we concentrated on a
high-risk group of elderly subjects with hypertension who had agreed to
participate in a randomised trial; therefore the results may be of limited
generalisability and may not apply to younger and normotensive populations.
Second, although we were able to control for a wider range of confounders than
most previous studies, smoking was only coded as a binary variable. This
overaggregation might lead to residual confounding. However, this may not be
of major concern because controlling for cardiovascular risk factors only
reduced the hazard ratio from 1.56 to 1.50. One would expect a much more
dramatic decrease in the hazard ratio when controlling for this confounder if
residual confounding was capable of explaining the association. Third, our
measure of depression was a questionnaire. It is possible that this is less
valid than clinical interviews, although the SelfCARED has been shown
to have acceptable validity and reliability in this age group
(Bird et al, 1987;
Upadhyaya & Stanley,
1997). If there was misclassification of cases it is most likely
that this would be random misclassification, and thus lead to underestimation
of effect size.
Major versus minor depression
Our finding is consistent with recent findings from the longitudinal
Amsterdam study reporting a greater effect on mortality for major depression
than for minor depression (Penninx et
al, 1999). Given the finding by Blanchard et al
(1994), using a comprehensive
structured clinical assessment for depression in the elderly (GMS AGECAT;
Copeland et al, 1986),
that the mean score for cases of depression in an elderly community sample was
7 on the SelfCARED, it is likely that the
7 cut-off provides
greater specificity and/or indicates greater severity than the
6 cut-off.
The effect of depression that we found appeared greater and was more
statistically significant at the higher cut-off of the SelfCARED (i.e.
at
7 out of 12 compared with
6). At the
6 cut-off 8% were
depressed, and at the
7 cut-off 4.9% were depressed. If
6 represents
possible/minor depression, this prevalence is some-what lower than reported
from community studies (e.g. 12.8%;
Penninx et al, 1999).
Given that our population is from a randomised trial, this probably reflects
the healthy volunteer effect.
Male gender and mortality from depression
The increased risk associated with depression was present in males (but not
females) and in the younger age group in this sample. The interaction terms
that we detected were of only borderline statistical significance (0.05
<P <0.1) and may represent type I error. However, our findings
are consistent with recent papers suggesting that the effect of depression on
mortality is greater in men than in women
(Mallon et al, 2000).
Furthermore, Pennix et al (1999: p. 63) reported that although major
depression predicted mortality in males and females, minor depression
predicted mortality only in males. We are not aware of any research to date
that has detected age differences in the effect of depression on mortality, so
this finding requires replication.
Mediating factors
Given the increasing evidence for the association between depression and
cardiac mortality (Penninx et al,
2001) and the association between male gender and cardiovascular
disease, it could be that the effect of depression is partly explained by
cardiovascular and/or cerebrovascular disease, which has not been dealt with
in the analysis. Although suicide may be another explanation for the excess
mortality in males with depression, this is unlikely because it is a rare
cause of death in community samples
(Penninx et al,
1999). It would be valuable to carry out further analysis in our
sample to look at cause-specific mortality.
The literature that has previously linked depression and mortality has proposed two main mechanisms. The first relates to life-style, namely that depression may be a more distal risk factor for a number of risk factors that increase morbidity and mortality from cardiovascular and other physical disease. For example, people with depression may smoke more, exercise less, adhere less to treatment and drink more alcohol (Allgulander, 1994; Blanchard et al, 1994). We have been able to study markers for cardiovascular disease, including ECG ischaemia and smoking. Although these sorts of variable have been dealt with as confounders in this analysis, they are, strictly speaking, intermediary factors on the same causal pathway. Our analyses suggest that the association is unlikely to be entirely explained by these risk factors, although we were unable to control effectively for exercise or alcohol intake.
The second mechanism involves a group of risk factors that relate to possible biological change occurring in depression. Depression is known to be associated with increased cortisol, increased platelet co-agulability and changes in heart rate variability, perhaps indicating a cardiovascular system more prone to arrhythmias (Dalack & Roose, 1990; Mikuni et al, 1992). These findings are predominantly derived from small clinical samples of patients with severe depression. The next step will be to explore such associations in large epidemiologically based samples. We were able to adjust for ECG evidence of arrhythmia and hence this does not appear to have mediated the association between depression and mortality.
Future research
In terms of public health implications, depression is a common exposure.
Most people with depression in the community do not receive any specific
treatment for depressive symptoms
(Schoevers et al,
2000). Two early studies suggest that treatment of depression may
lower mortality, especially in men (Avery
& Winokur, 1976; Craig
& Lin, 1981). The findings here, together with the previous
literature, suggest the need to investigate the effect on mortality of
vigorous treatment of confirmed depression.
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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 December 3, 2001. Revision received April 23, 2002. Accepted for publication April 23, 2002.
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