World Health Organization Collaborating Centre in Evidence for Mental Health Policy, School of Psychiatry, University of New South Wales at St Vincent's Hospital, Sydney, Australia
Correspondence: Professor Gavin Andrews, Clinical Research Unit for Anxiety and Depression, 299 Forbes Street, Darlinghurst, NSW 2010, Australia. Fax: +61 2 9332 4316; e-mail: gavina{at}crufad.unsw.edu.au
Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To explore the correlates of current comorbidity.
Method Data from the Australian National Survey of Mental Health and Well-Being were used to evaluate the relationships between comorbidity, disability and service utilisation associated with particular mental disorders.
Results The number of current comorbid disorders predicted disability, distress, neuroticism score and service utilisation. Comorbidity is more frequent than expected, which might be due to the effect of one disorder on the symptom level of another, or to the action of common causes on both. The combination of affective and anxiety disorders was more predictive of disability and service utilisation than any other two or three group combinations. When people nominated their principal disorder as the set of symptoms that troubled them the most, the affective and anxiety disorders together were associated with four-fifths of the disability and service utilisation.
Conclusions To make clinical interventions more practical, current comorbidity is best reduced to a principal disorder and subsidiary disorders.
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INTRODUCTION |
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METHOD |
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Respondents who reported symptoms consistent with more than one disorder were asked to nominate which of their clinically significant groups of symptoms they would consider to be the problem that troubles you the most. Thus, it was possible to code all respondents who met criteria for two or more disorders against a principal disorder (further details available from the author upon request). The results presented here refer to people who met criteria for a CIDI diagnosis some time in the preceding 12 months and who said that the set of symptoms they endorsed had been present in the preceding 4 weeks (i.e. current cases). Disability and psychological distress were assessed over a similar 4-week time frame. The questions on neuroticism were trait questions, asking about your nature, how you usually are. The question on number of consultations with a health professional for a mental problem such as stress, anxiety, depression or dependence on drugs or alcohol was applied to the previous 12 months.
Analysis
Is the association between comorbidity and other indicators
meaningful?
First, to evaluate disability, distress, neuroticism and service
utilisation by number of disorders in the total sample, respondents were coded
against the total number of mental disorders for which they met criteria
(none, one, two, three, four, five or more) from a total of 12: two affective
disorders (depression, dysthymia), five anxiety disorders (panic/agoraphobia,
social phobia, generalised anxiety disorder, obsessivecompulsive
disorder, post-traumatic stress disorder), two substance use disorders
(alcohol abuse/dependence, other drug abuse/dependence), and three personality
disorder clusters (cluster A, cluster B, cluster C). The age and gender
distribution, and levels of disability, distress, neuroticism and service
utilisation, were examined across these groups
(Table 1).
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Second, patterns of bivariate comorbidity in the total sample were
examined. Bivariate associations of mental disorders were calculated from a
series of logistic regression models containing only pairs of disorders. In
each model one disorder of the pair was used as the dependent variable and the
other served as the independent variable. Comparisons significant at the 0.05
level are displayed in Table 2.
However, a more conservative level of 0.001 was used to assess the
significance of comorbid disorder pairs, to account for multiple estimation
(Tabachnick & Fidell,
1996). Associations were estimated for current comorbidity and for
comorbidity in the preceding 12 months.
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Third, to investigate patterns of multivariate comorbidity in the total
sample, multivariate associations of mental disorders were calculated from a
series of logistic regression models each containing the disorder of interest
as the dependent variable, every other disorder in turn as the independent
variable, and in each case an additional variable representing the number of
other diagnoses for which criteria had been met. A conservative level
of 0.001 was again used to assess the significance of comorbid disorder pairs
to account for multiple estimation.
Fourth, patterns of comorbidity across diagnostic time-frames were examined using comparisons with the US NCS data. Bivariate odds ratios (ORs) for NCS life-time and 6-month, and current survey 12-month and 1-month, comorbid disorder pairs were calculated. The distribution of ORs was compared across these time-frames using the Wilcoxon signed ranks test (Siegel, 1956).
Is the relation between comorbidity, disability and service utilisation associated with particular disorders or groups of disorders? In order to examine the effect of specific comorbid disorder group pairs on disability and service utilisation, two separate series of regression analyses were conducted. The first contained the mental health component scale of the SF-12 as a dependent variable and modelled the effect of each comorbid disorder group pair (affective/anxiety disorders, affective/substance use disorders, affective/personality disorders, anxiety/substance use disorders, anxiety/personality disorders and substance use/personality disorders) on disability. These linear regression models controlled for the number of disorders as well as for variables that have been shown to contribute to disability in the total sample socio-demographic factors and presence of chronic physical conditions (Sanderson & Andrews, 2002). The second series of logistic regression models contained any mental health consultation as the dependent variable. Models were estimated in the same way, again controlling for the number of disorders and factors that have been shown to predict service utilisation in the total sample (Andrews et al, 2001b).
Is there a method whereby survey data could be obtained to control
for comorbidity?
Disability, distress, neuroticism and service utilisation were analysed
according to main problem (taken as a proxy for the principal disorder) among
those with two disorders from different groups. Respondents who reported
symptoms of more than one disorder were asked to nominate which of their
clinically significant groups of symptoms was the problem that troubles
you the most. Thus, it was possible to code all respondents who met
criteria for two or more disorders against their principal disorder. The age
and gender distribution and level of disability, distress, neuroticism and
service utilisation were examined across these comorbid groups.
The same analysis of disability, distress, neuroticism and service utilisation by principal disorder was performed for the total sample, with the difference that all respondents who met criteria for at least one current DSM-IV mental disorder were included and were coded against their principal disorder. Comparisons between these four groups were made using analysis of variance with planned contrasts and a conservative error rate of P=0.001 to account for multiple comparisons.
Variance estimation
Standard errors around proportions, means and regression parameters were
calculated using jackknife repeated replication to account for the complex
survey design (Kish & Frankel,
1974). The SUDAAN software package, designed for use with complex
survey samples, was used for these calculations
(Shah et al,
1997).
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RESULTS |
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In the cells below and to the left of the diagonal (signified by ) in Table 2 we present a matrix of bivariate ORs for all 66 comorbid disorder pairs that shows that almost all combinations are larger than one, and thus are much more common than expected. In the present material, 83% of the displayed ORs for current comorbid disorder were larger than the ORs for 12-month comorbidity (Wilcoxon signed ranks test, P < 0.001; Siegel, 1956).
The cells above and to the right of the diagonal in Table 2 give the multivariate ORs in which the unique association between two diagnoses are presented, after controlling for the general probability of comorbidity. The resulting multivariate ORs are significantly less than the bivariate ORs. The within-disorder group ORs (in bold) are significantly larger than those between disorders in different groups (MannWhitney U=85.5, P<0.001; Siegel, 1956). There are, however, a number of significant and informative associations between disorders from different groups. There is a significant association between generalised anxiety disorder (GAD) and affective disorders (ORs of 10.2 for depression, 12.6 for dysthymia) and the ORs are higher than those between GAD and the other anxiety disorders (ORs of 2.3-5.3). Similarly, the ORs for post-traumatic stress disorder (PTSD) are highest for its association with depression (OR=6.7), and with the exception of obsessivecompulsive disorder (OR=6.0) the associations with other anxiety disorders are not significant at the 0.001 level. The multivariate associations between obsessivecompulsive disorder and the other anxiety disorders are also non-significant (ORs of 1.6-2.3). Substance abuse/dependence have only moderate relationships with other disorders, with only alcohol abuse/dependence and depression reaching a significance level of 0.001 (OR=3.1). Cluster A personality disorders exhibit a significant relationship with panic/agoraphobia (OR=2.3) and cluster C personality disorders exhibit a significant relationship with social phobia (OR=5.5). Multivariate comorbidity is strong between the clusters of personality disorder (ORs of 7.8-24.1).
It is clear from Table 1 that comorbidity is associated with increased disability, distress, service use and neuroticism. From Table 2 it is evident that comorbidity occurs more often than would be expected by chance, and that even when controlling for this phenomenon, some disorder pairs occur more often than others and that these combinations are meaningful. What is not clear from either of these tables is which diagnostic combinations are particularly likely to generate an excess of either disability days or consulting for a mental problem.
Relationship with specific disorders
Is the relation between comorbidity, disability and service utilisation
associated with particular disorders or groups of disorders? We used
regression models to explore the association between disability, service use
and the comorbidity by pairs of disorder groups (i.e. depression plus
dysthymia equals affective disorder group, etc.), controlling for
socio-demographic factors, presence of a chronic physical disorder and number
of comorbid mental disorder groups. Although most pairs of groups were more
disabling than each disorder group alone (affective/anxiety,
P<0.001; affective/substance use, P<0.001;
affective/personality disorders, P<0.001; anxiety/substance use,
P<0.01; anxiety/personality disorders, P<0.001), the
combination of substance use and personality disorder was not
(P=0.79; Table 3).
Only the combination of affective and anxiety disorders was significantly
associated with disability as measured by the SF12
(P<0.001) and with number of consultations for a mental problem
(P<0.001) in comparison with other comorbid disorder group
pairs.
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Comorbidity, measured by the number of disorder groups, is associated with increased disability and service use, regardless of which disorder groups are in combination. However, once the general effect of comorbidity between disorder groups is controlled, only anxiety and affective disorder groups in combination are associated with increased disability and service use compared with other disorder group combinations.
Use of survey data to control for comorbidity
Respondents who reported symptoms of more than one disorder were asked to
nominate which of their clinically significant groups of symptoms they would
consider to be the problem that troubles you the most. Thus, it
was possible to code all respondents who met criteria for two or more
disorders against their principal disorder, as recommended in DSMIV. We
initially restricted analysis to people who had at least one disorder from two
different disorder groups, that is to those comorbid disorder group pairs
listed in the section above. People who had affective or anxiety disorders in
combination with other disorder groups were more likely to choose affective or
anxiety disorders as their main problem. Only a limited number of people with
comorbid personality (n=22) or substance use disorders
(n=29) identified these disorders as their main problem. People who
nominated affective or anxiety disorders as their main problem in a comorbid
pair were more likely to be female, more disabled, more distressed, to have a
higher neuroticism score, and to use more services than people with
personality or substance use disorders (P<0.001 for all
comparisons). Those with substance use disorders were younger than those in
the other three groups (P<0.001 for all comparisons).
In order to consider the usefulness of this approach it needs to be applied to the whole sample, not just to those who met criteria for disorder group pairs. In Table 4 we present data from everyone in the study who met the criteria for any of these 12 mental disorders. For the 60% who met criteria for only one disorder, that disorder would be their only, and therefore main, problem, whereas the 40% who met criteria for more than one disorder nominated one of their comorbid disorders as their main problem. Twenty people with comorbid neurasthenia or psychosis nominated one of those disorders as their main problem and were lost to the calculation. Table 4 also presents the significance of specific comparisons across the groups. In general, people whose only or main problem was an affective or anxiety disorder were more likely to be older, female, disabled, distressed, have a higher neuroticism score, or use more services than people whose only or main problem was a personality or substance use disorder (P<0.001 for all comparisons). In short, people with an affective or anxiety disorder as their main problem accounted for 73% of the total disability days and 79% of the consultations recorded by people who identified a disorder in one of these four groups of disorders as their main problem. Affective and anxiety disorders, separately and together, are significant sources of disability and service utilisation.
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In the lower part of Table 4 we list, by main-problem disorder group, the proportion who had other comorbid disorders. In the affective disorder group 52.3% had concurrent disorders, of which 36.0% were anxiety disorders, 27.5% personality disorders and 14.9% substance use disorders. In contrast, only 12.6% of people with substance use disorders as their principal disorder met criteria for a comorbid disorder and, with the exception of personality disorder (9.6%), comorbidity with affective and anxiety disorders was rare.
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DISCUSSION |
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In the present study concurrent comorbidity was common and 40% of the sample with any current disorder met criteria for more than one current disorder. Kessler (1995) and Angst (1996) noted that people who were comorbid at some time had increased rates of service utilisation. We are unaware of data on increases in disability measures, distress and neuroticism associated with current comorbidity. The data analysed here were restricted to disorders currently present, but even so, there was a strong linear relation between number of disorders and disability, distress, neuroticism and service use. Twenty-one per cent of the people who met criteria for any mental disorder met criteria for three or more current disorders, and they accounted for 33% of the disability days and for 37% of the service use. Comorbidity has serious consequences and, because of the linear nature of the relationships, is unlikely to be an artefact of the method of inquiry, a view proposed by Sturt (1981).
Does the pattern of comorbidity inform nosology?
Is the pattern of comorbidity random or meaningful? Bivariate ORs for
current comorbidity were significantly higher than those for the 12-month
comorbidity. Data from Kessler
(1995) showed a similar
phenomenon. In the NCS, 90% of the 6-month ORs were larger than the
corresponding lifetime ORs (P < 0.001). The NCS data and the
12-month and 1-month data from our survey show similar patterns. This
replicated finding raises the possibility that the occurrence of one disorder
can be affected by the presence of another disorder. Kessler
(1995) reported a drop in
average odds ratios from within a diagnostic group to between diagnostic
groups. This effect was also obvious in the present data. It is difficult to
think what might explain these changes, except for the idea that the presence
of one disorder might generate symptoms in an individual that could meet
criteria for another disorder, or be sufficient to convert a sub-threshold
secondary disorder into one that met diagnostic criteria, especially when both
were within the same diagnostic group.
Bivariate ORs illustrate the general phenomenon, whereas multivariate ORs, in which the general tendency is controlled, throw the specific associations into relief. Odds ratios were highest within disorders of the same group, as expected, but significant ORs occurred between disorder groups, and were especially pronounced between the affective and anxiety disorders. Cross-category influences are important, and many have argued that depressive disorders follow anxiety disorders. Kessler et al (1999), for example, calculated that 10-15% of depression could be attributed to earlier social phobia. Kessler (1995) had shown a stronger association between the anxiety and affective disorders than between substance use disorder and either anxiety or affective disorders. A similar picture was evident in the present regression analyses: comorbid anxiety and affective disorders were better predictors of disability and service utilisation than any other pair. Comorbidity with substance use disorders is often regarded as giving rise to great morbidity. Neither in the NCS, nor in the present survey, was this so.
Looking at the pattern of multivariate ORs, the within-group elevated ORs are to be expected because disorders in the same group share similar symptom sets, a finding that supports the dimensionality of most diagnoses. For example, depression and dysthymia, social phobia and panic/agorapobia, alcohol and drug dependence all have symptoms in common and show elevated ORs. We have elsewhere argued that the three panic/agoraphobia disorders should be reclassified as one syndrome (Andrews & Slade, 2002), and did so for this analysis because having three mutually exclusive categories would preclude the calculation of ORs.
When disorders in the same group do not show elevated ORs one can ask whether the disorder is misclassified as a member of that group. For example, obsessivecompulsive disorder does not show elevated odds ratios with the other anxiety disorders, the ICD-10 classifies it separately (World Health Organization, 1992), and there is continuing discussion as to whether it is best categorised as part of a separate group of disorders sometimes called the obsessivecompulsive spectrum disorders (Hollander & Wong, 1995). Conversely, elevated between-group ORs might inform about more appropriate classification or about common causes of two disorders. Although there is, as every clinician knows, a significant bivariate association between all affective and anxiety disorders, only GAD and PTSD maintain this association multivariately. Generalised anxiety disorder is highly comorbid with both depression and dysthymia, and there are genetic and phenomenological data that suggest it may be more akin to the affective group than to the anxiety group of disorders (Kendler, 1996; Vollebergh et al, 2001). Depression and PTSD are also highly comorbid, which may not be surprising given that adversity can cause both.
Is the principal complaint method informative?
Although the combination of affective disorders with anxiety disorders is
found to be the best predictor of disability and service utilisation, there is
no method for deciding the relative contribution of each. Identifying each
person's main problem or principal complaint is a possible advance. We looked
at data for all people reporting two or more of the four groups of disorders,
and found that few people nominated substance use or personality disorders as
their main problem. Inspecting data from the whole data-set we discovered that
when identified as the principal complaint, the anxiety and affective disorder
groups contribute equally, and together account for four-fifths of disability
days and mental health consultations attributed to people with these four
groups of disorders. In a population sample neither principal complaints of
substance use disorder nor of personality disorder are of great importance as
determinants of disability or service use.
Two disorders were excluded from the current analysis. Criteria for current neurasthenia were met by a weighted 1.1% of the population (i.e. 140 survey respondents); 33 had no comorbid condition and only 22 of the remaining 107 persons nominated neurasthenia as their main problem. The addition of neurasthenia to the present results would have complicated but not changed the meaning of the tables. Psychosis is different. The survey used a psychosis screener and identified 0.4% of the entire population as possibly suffering from psychosis. The related low-prevalence disorder survey (Jablensky et al, 2000) using precise diagnostic instruments also calculated the prevalence of psychosis to be 0.4%. We have concluded (Andrews et al, 2001c) that psychosis accounts for only 8% of the disability attributed to mental disorders given the following conservative assumptions; that the 0.4% of the population identified by the screener were all cases, that all identified psychosis as their principal complaint, and that their average level of disability was severe (3 standard deviations below the population mean on the SF-12). Even with those assumptions, the anxiety and affective disorders still accounted for more than 70% of the disability attributed to mental disorders. The inclusion of psychosis would not have materially altered the present data.
What are the implications?
This paper has described the epidemiology of current comorbidity
information that has clinical value. The majority of people who seek help for
a mental disorder have more than one disorder and will be more disabled,
distressed and have higher neuroticism scores than people who do not consult.
Patients can nominate the disorder that troubles them the most, and wise
clinicians would formulate an initial treatment plan to take this principal
complaint into account. Not to do so would invite non-compliance. Substance
use disorders and personality disorders were seldom nominated as principal
complaints, but this does not mean that they were unimportant, only that they
were not the principal reason the patient came for treatment. If compliance is
dependent on responding to the principal complaint, therapeutic success might
be dependent on treatment of the associated substance use or personality
disorder. Identification of a principal complaint does not mean devaluing the
importance of the comorbid disorders, only of prioritising the elements of the
treatment plan. For example, depression with a comorbid anxiety disorder has a
poor prognosis (McLeod et al,
1992), and its treatment although initially focused on the
depression would have to take account of the anxiety if relapse was to
be inhibited. Thus, on both epidemiological and clinical grounds comorbidity
is valuable information that needs to be understood.
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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 2, 2002. Revision received May 15, 2002. Accepted for publication May 17, 2002.
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