Normal personality traits and comorbidity among phobic, panic and major depressive disorders

Psychiatry Research 102 Ž2001. 73᎐85

Normal personality traits and comorbidity among phobic, panic and major depressive disorders O. Joseph Bienvenu a,U , Clayton Brownb, Jack F. Samuels a , Kung-Yee Liang b,1, Paul T. Costac , William W. Eaton d, Gerald Nestadt a a

Department of Psychiatry and Beha¨ ioral Sciences, School of Medicine, Johns Hopkins Uni¨ ersity (JHU), Baltimore, MD 21287, USA b Department of Biostatistics, School of Hygiene and Public Health, Johns Hopkins Uni¨ ersity (JHU), Baltimore, MD, USA c National Institute on Aging, National Institutes of Health, Baltimore, MD, USA d Department of Mental Hygiene, School of Hygiene and Public Health, Johns Hopkins Uni¨ ersity (JHU), Baltimore, MD, USA Received 9 June 2000; received in revised form 3 January 2001; accepted 14 January 2001

Abstract High comorbidity among anxiety and depressive conditions is a consistent but not well-understood finding. The current study examines how normal personality traits relate to this comorbidity. In the Baltimore Epidemiologic Catchment Area Follow-up Study, psychiatrists administered the full Schedules for Clinical Assessment in Neuropsychiatry to 320 subjects, all of whom completed the Revised NEO Personality Inventory. The disorders of interest were simple phobia, social phobia, agoraphobia, panic disorder, and major depression. Analyses were carried out with second-order generalized estimating equations. The unadjusted summary odds ratio ŽSOR ᎏ or weighted mean odds ratio. for all five disorders was 1.72 Ž95% confidence interval s 1.21᎐2.46.. Neuroticism, introversion, younger age, and female gender were all significant predictors of prevalence of disorders. After adjustment for the relationships U

Corresponding author. 600 N. Wolfe St., Meyer 125, Baltimore, MD, 21287, USA; Tel.: q1-410-614-9063; fax: q1-410-614-8137. E-mail address: [email protected] ŽO. Joseph Bienvenu.. 1 For correspondence regarding second-order generalized estimating equations ŽGEE2., please contact Dr Liang at [email protected] 0165-1781r01r$ - see front matter 䊚 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 1 6 5 - 1 7 8 1 Ž 0 1 . 0 0 2 2 8 - 1

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between these personality and demographic predictors and prevalence, the association among disorders was much weaker ŽSORs 1.11, 95% CI s 0.79᎐1.56.. However, subjects with high extraversion had a SOR 213% as high Ž95% CI s 102᎐444%. as those with low extraversion Ž1.60 vs. 0.75.. Therefore, neuroticism and introversion are associated with increased comorbidity due to relationships in common with the prevalence of the different disorders. In contrast, extraversion is associated with increased comorbidity per se. 䊚 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Anxiety disorders; Unipolar depression; Quantitative trait; Epidemiology

1. Introduction High comorbidity among anxiety and depressive disorders is a consistent finding in both clinical and community studies ŽBoyd et al., 1984; Maser and Cloninger, 1990; Sanderson et al., 1990; Goisman et al., 1995; Merikangas et al., 1996; Krueger et al., 1998; Krueger, 1999b.. Despite our increasing awareness of this phenomenon, its causes and correlates are not yet well understood ŽKessler, 1995.. One possibility is that normal personality traits mediate this comorbidity. In recent years, the five-factor model of personality has been increasingly recognized among personality psychologists as a comprehensive model of normal personality traits ŽJohn, 1989; Digman, 1990; Goldberg, 1993.. It was developed through factor-analytic studies of personality adjectives Žthe lexical tradition. and has strong external empirical support ŽCosta and McCrae, 1992a.. The five factors are neuroticism, one’s tendency to experience negative emotions and cope poorly; extraversion, one’s quantity and intensity of interpersonal interactions and positive emotions; openness to experience, one’s appreciation of experience for its own sake; agreeableness, one’s orientation toward others Žaltruistic vs. antagonistic .; and conscientiousness, one’s organization, motivation, and persistence in achieving goals. Numerous studies have demonstrated relationships between neuroticism, introversion, and anxiety and depressive disorders ŽEysenck and Rachman, 1965; Liebowitz et al., 1979; Hirschfeld et al., 1983, 1989; Solyom et al., 1986; Kendler et al.,

1993; Trull and Sher, 1994.; however, few have addressed comorbidity. One exception is that of Andrews et al. Ž1990b., who found that, in both patients and volunteer subjects, higher levels of neuroticism were associated with more anxiety and depressive disorders in the same person. However, we know of no studies that have attempted to determine to what extent anxiety and depressive disorders are associated if these personality correlates in common are taken into account. Also, we know of no studies that examine the influence of personality traits on comorbidity per se Ži.e. personality traits could influence the likelihood of having another disorder given one is present.. The current study examines how comorbidity among phobic, panic, and major depressive disorders is related to five-factor model of personality traits. This is approached from two perspectives, using cross-sectional data from the Baltimore Epidemiologic Catchment Area Follow-up Study. Firstly, we determine how personality traits relate to associations among disorders by virtue of common relationships between specific personality traits and the prevalences of the different disorders. Next, we examine whether personality traits are related to comorbidity per se, independent of relationships with prevalence. Strengths of this study include the use of a community sample; face-to-face semi-structured psychiatrist evaluations; a widely used measure of five-factor model personality traits, the Revised NEO Personality Inventory ŽNEO-PI-R; Costa and McCrae, 1992b.; and a novel analytic method, second-order generalized estimating equations ŽGEE2; Qaqish and Liang, 1992..

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2. Methods The Epidemiologic Catchment Area ŽECA. surveys were completed at five sites in the USA in 1980᎐1983 ŽRegier et al., 1984.. Trained nonclinician interviewers administered the Diagnostic Interview Schedule ŽDIS; Robins et al., 1981. to a probabilistic sample of the adult population at each site. In the Baltimore ECA Follow-up Study Ž1993᎐1996., 88% of the original Baltimore cohort were traced, and 73% of those known to be alive Ž n s 1920. were re-interviewed using the DIS ŽEaton et al., 1997.. A subsample of the Baltimore ECA Follow-up Study cohort was invited for an evaluation by a psychiatrist ŽEaton et al., 1998.. Only these subjects are considered in this report, as normal personality traits were not assessed in the entire cohort. Respondents who appeared to have incident DIS disorders Žsince 1981. in any of seven major diagnostic categories ᎏ social phobia, agoraphobia, panic disorder, major depression, alcohol use disorders, cognitive impairment, or obsessive-compulsive disorder ᎏ were invited. Respondents with DIS diagnoses in both 1981 and 1982 were also invited, as was a small random sample of all respondents Ž41 subjects who did not meet other selection criteria .. Informed consent was obtained. Three hundred forty-nine subjects participated in the psychiatric evaluation, which included the use of a semi-structured diagnostic instrument, the Schedules for Clinical Assessment in Neuropsychiatry ŽSCAN; Wing et al., 1990.. The SCAN has acceptable inter-rater reliability ŽTomov and Nikolov, 1990.; though reliability was not assessed in the current study, all cases were reviewed in detail by at least two psychiatrists in diagnostic consensus conferences. During the same office visit, 333 of the subjects completed the NEO-PI-R, 320 of whom had no missing information on the disorders of interest; only the latter subjects were considered in the analyses. The mean age in this sample was 49.8 years ŽS.D.s 14.6.. One hundred and fifteen were male, and 205 were female. Two hundred and two were white, 110 were black, and 8 were of other races. The disorders of interest for this study were

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lifetime SCANrDSM-III-R simple phobia Ž n s 75., social phobia Ž n s 42., agoraphobia Ž n s 24., panic disorder Ž n s 26., and unipolar major depression Ž n s 59.. There were too few cases of obsessive᎐compulsive disorder for meaningful analyses Ž n s 4.. The mean ages of onset Žyears. and standard deviations ŽS.D.. for the disorders of interest were: simple phobia s 12.1 ŽS.D.s 13.2.; social phobia s 13.9 ŽS.D.s 9.6.; agoraphobias 24.2 ŽS.D.s 19.6.; panic disorders 38.2 ŽS.D.s 15.9.; and major depression s 34.3 ŽS.D.s 15.7.. Most subjects with histories of phobic disorders met full criteria at the time of evaluation Žsimple phobia s 89%, social phobia s 77%, agoraphobia s 88%.. In contrast, only 45% of subjects with a history of panic disorder, and only 25% of those with a history of major depression, met full criteria at the time of evaluation. The NEO-PI-R is scaled to produce domain scores for each of the five factors. Each of the domains is made up of six subscales or facets. Scores were standardized by converting raw scores to T-scores, using raw score means and standard deviations of men and women in a general population sample ŽCosta and McCrae, 1992b.. The average T-score in the general population is 50, with S.D.s 10. Different reference means and standard deviations were used for men and women as, e.g., women generally have higher raw neuroticism and agreeableness scores than men. Factor scores were calculated, with an algorithm that incorporates facet scores ŽCosta and McCrae, 1992b., to create more precisely orthogonal measures of the five factors than domain scores; domain scores tend to be slightly correlated with one another. T-scores - 45 are considered in the ‘low’ range, those 45᎐55 in the ‘average’ range, and those ) 55 in the ‘high’ range. The factor means and standard deviations for this sample were: neuroticism s 49.7 ŽS.D.s 10.0.; extraversion s 47.9 ŽS.D.s 8.9.; openness s 46.6 ŽS.D.s 8.7.; agreeableness s 49.3 ŽS.D.s 9.9.; and conscientiousness s 46.7 ŽS.D.s 9.1.. Readers may be curious as to how the average neuroticism factor score for this subsample, selected largely for psychopathology, is so close to the general population average. It must be recalled that the disorders of interest for the current study were not

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the only ones upon which selection was based. Subjects without the disorders of interest had relatively low mean neuroticism scores ŽBienvenu et al., in press.. 2.1. Analyses The statistic of association in this study was the odds ratio ŽOR.. This describes, in the bivariate case, the odds of having one disorder given another. An OR greater than 1.0 indicates that disorders co-occur more often than would be expected by chance. GEE2 is a powerful method for modeling associations among disorders. It was designed to analyze correlated binary data when the point of interest is the degree of association within the cluster ŽLiang and Beaty, 1991; Qaqish and Liang, 1992.. In this study, the correlated binary variables of interest were anxiety and depressive disorders, clustering within individuals Žcomorbidity.. With GEE2, one can calculate separate pairwise ORs or a summary OR ŽSOR.. The SOR is a weighted mean OR; it describes the odds of having another disorder given any one disorder. An important feature of the GEE2 method is that it allows analysis of the dependence of associations Žcomorbidity. on additional factors, such as personality, through regression modeling. To the extent that variables have similar effects on bivariate associations within a cluster, using the SOR provides increased power to detect such relationships. Alpha was set at 0.05 for all analyses, and all tests were two-tailed. Analyses were carried out in three stages, illustrated as a, b and c in Fig. 1. In the first analytic stage, unadjusted pairwise lifetime ORs among simple phobia, social phobia, agoraphobia, panic disorder, and major depression were calculated using GEE2 Žas with logistic regression.. The unadjusted SOR for the five disorders of interest was also calculated. These models correspond to a in Fig. 1. In the second stage, the logistic regression estimation routines of GEE2 were used to assess whether individual personality factors or demographic variables Žage, gender, race, education, or marital status . predicted lifetime prevalence of the disorders of interest. SORs were then calcu-

Fig. 1. Three different models for estimating the association Žodds ratio, OR. between disorders Žd., with and without the inclusion of other variables Ž ¨ .. The first model, a, is the unadjusted model. The second model, b, assesses the association between disorders, adjusting for the relationships of disorders with predictor variables. The third model, c, assesses the association between disorders at different levels of a variable Ž ¨ 1 ., adjusting for the relationships of disorders with predictor variables.

lated, including variables that significantly predicted prevalence in the models. These models estimate associations among disorders, adjusting for relationships between predictor variables and the prevalence of disorders; they correspond to b in Fig. 1. With logistic regression, similar analyses are possible, but the focus must be restricted to one pair of disorders at a time. Demographic variables Žespecially age and gender. were included because of their consistent associations with the prevalence of anxiety and depressive disorders ŽKessler et al., 1994; Horwath and Weissman, 1995., and accounting for such associations is important for the next analytic stage. In the third stage, GEE2 was used to assess the SORs at different levels of personality factor scores Žlow, average and high., adjusting for variables found at the second stage to be significant predictors of prevalence. These models test relationships between personality traits and comorbidity per se. That is, these models test effects of personality traits on the odds of having a second disorder given that a person has one disorder,

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independent of prevalence; they correspond to c in Fig. 1. Analogous analyses with logistic regression would test for interactions between personality traits and the likelihood of one disorder given another particular disorder. Again, to the extent that personality traits have similar effects on bivariate associations within a cluster, using the SOR provides increased power to detect such relationships.

3. Results One hundred and fifty-eight subjects had none of the five lifetime SCANrDSM-III-R disorders of interest; 117 subjects had one; 30 subjects had two; 11 subjects had three; and four subjects had four. None of the subjects had all five disorders. There were 87 instances of pairwise comorbidity among the disorders of interest. Agreement between diagnostic methods Ži.e. the DIS administered by non-clinician interviewers and the SCAN administered by psychiatrists . is discussed elsewhere Že.g. see Eaton et al., 1998; Neufeld et al., 1999.. Unadjusted lifetime comorbidity among the five disorders of interest is shown in Table 1; these analyses correspond to a in Fig. 1. All OR point estimates for pairs of disorders were ) 1.0, except for that between simple phobia and panic disorder. There were significant associations between social phobia and agoraphobia, as well as between social phobia and panic disorder; there were trends for associations between simple phobia and agoraphobia, as well as between panic disorder and major depression. The weighted mean OR was significantly greater than 1.0 ŽSOR s 1.72, 95% CI s 1.21᎐2.46, P- 0.005.. Relationships between personality and demographic predictors and lifetime prevalences of the disorders of interest are shown in Table 2; results are shown only for those predictors that had statistically significant monotonic relationships with at least one disorder. In this case, ORs represent the odds of having disorders given specific predictor variable attributes. ORs less than 1.0 indicate inverse relationships, and ORs greater than 1.0 indicate positive relationships. Neuroti-

77

cism was significantly associated with the prevalence of each of the five disorders of interest. Low extraversion Žintroversion. was only significantly associated with social phobia and agoraphobia. The mean neuroticism factor score for subjects with each of the disorders of interest except specific phobia was ; 0.5 standard deviations above average. The mean extraversion factor score for subjects with social phobia and subjects with agoraphobia was almost 1 standard deviation below average ŽBienvenu et al., in press.. Though most of the disorders were associated with younger age, only social phobia had a significant association. All of the disorders had significant associations with female gender except for social phobia. Neither openness, agreeableness, nor conscientiousness had statistically significant monotonic relationships with the prevalence of any of the disorders of interest. Also, neither race, education, nor marital status was significantly related to prevalence. Relationships between personality factor scores Žlow, average, and high. and mean numbers of disorders per subject are illustrated in Table 3. As might be expected from the results in Table 2, both neuroticism and introversion were associated with more disorders per subject. Also as might be expected, when social phobia and agoraphobia were excluded as outcomes, there was no discernible relationship between extraversion and mean number of disorders per subject Žresults not shown.. Adjusted lifetime comorbidity among the five disorders is shown in Table 4; these analyses correspond to b in Fig. 1. Adjusting for the significant predictors of prevalence separately Žneuroticism, extraversion, age and gender., the SOR point estimates were lower than in the unadjusted model Ži.e. 1.72., though all were still significantly greater than 1.0 except that in the neuroticism model Žtrend only.. However, adjusting for all of the significant predictors of prevalence simultaneously Žneuroticism, extraversion, age and gender., the SOR was not significantly greater than 1.0 ŽSOR s 1.11, 95% CI s 0.79᎐1.56.. In other words, because of similar associations between predictor variables and different disorders Žsee

78

Simple phobia a

Social phobia b

c

a

Agoraphobia b

c

a

c

q rqa

ORb

95% CIc

q rq

OR

95% CI

q rq

OR

95% CI

Social phobia

13

1.56

Ž0.76᎐3.18.

᎐

᎐

᎐

Agoraphobia

9

2.09

Ž0.88᎐5.00.e

8

3.85

Ž1.53᎐9.68. UU

᎐

᎐

᎐

Panic disorder

5

0.76

Ž0.28᎐2.10.

7

2.73

Ž1.07᎐6.95. U

4

2.49

Ž0.78᎐7.93.

᎐

᎐

᎐

15

1.14

Ž0.59᎐2.19.

11

1.70

Ž0.80᎐3.62.

7

1.93

Ž0.76᎐4.90.

8

2.12

Ž0.87᎐5.14.e

Major depression a

q rq s number of subjects with both disorders. ORs odds ratio. c CI s confidence interval. d SORs summary odds ratio for all 5 disorders. e t s trend Ž P- 0.1. ᎏ greater than 1.0. U P- 0.05 ᎏ greater than 1.0. UU P- 0.005 ᎏ greater than 1.0. b

q rq

Panic disorder b

OR

95% CI

UU

SORd s 1.72 Ž95% CI s 1.21᎐2.46.

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Table 1 Unadjusted lifetime comorbidity among SCAN DSM-III-R disorders

Predictors

Neuroticismb Extraversionb Age Žyears.c Female gender a

Simple phobia

Social phobia

Agoraphobia

Panic disorder

Major depression

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

1.16 1.06 1.02 2.93

Ž1.02᎐1.32.q Ž0.92᎐1.23. Ž0.94᎐1.11. Ž1.56᎐5.49.UU

1.24 0.68 0.82 1.17

Ž1.04᎐1.47.q Ž0.54᎐0.85.qq Ž0.71᎐0.94.qq Ž0.56᎐2.46.

1.27 0.74 0.91 4.92

Ž1.00᎐1.61.q Ž0.59᎐0.91.U Ž0.80᎐1.04. Ž1.41᎐17.1.q

1.40 0.91 0.97 5.66

Ž1.15᎐1.70.UU Ž0.72᎐1.14. Ž0.85᎐1.11. Ž1.56᎐20.6.U

1.44 1.16 0.93 2.54

Ž1.23᎐1.70.UU Ž0.97᎐1.38. Ž0.84᎐1.03. Ž1.22᎐5.30.q

All significant predictors of at least one disorder Žneuroticism, extraversion, age, and gender. are included in the model. ORs odds ratio. CI s confidence interval. b Estimated increase in odds ratio for each 5 points higher factor score. c Estimated increase in odds ratio for each 10 years older age. q P - 0.05 ᎏ ) 1.0. U P- 0.01 ᎏ ) 1.0. qq P- 0.005 ᎏ ) 1.0. UU P- 0.001 ᎏ ) 1.0.

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Table 2 Personality factor and demographic predictors of lifetime prevalence of SCAN DSM-III-R disordersa

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80

Table 3 Mean numbers of disorders a per subject, given different levels of personality factor scores Factor score

Neuroticism b

Low: - 45 Average: 45᎐55 High: ) 55 a b

Extraversion b

Openness b

Agreeableness b

Conscientiousness

n

mean

n

mean

N

mean

n

mean

nb

mean

100 135 85

0.37 0.65 1.19

118 133 69

0.84 0.65 0.59

141 129 50

0.62 0.74 0.84

100 133 87

0.80 0.55 0.84

141 120 59

0.82 0.58 0.71

simple phobia, social phobia, agoraphobia, panic disorder, and major depression. n s number of subjects.

Table 2., each of these personality and demographic variables accounted for some of the comorbidity among disorders. As would be expected from Table 2 results, neuroticism accounted for more comorbidity than extraversion, age, or gender. Together, these variables accounted for most of the comorbidity among disorders. In the next set of models, neuroticism, extraversion, age and gender were controlled as predictors of prevalence, and relationships were analyzed between personality factors and comorbidity per se. These analyses correspond to model c in Fig. 1. Though there was a tendency for higher neuroticism to be associated with greater comorbidity per se, this did not approach statistical significance ŽTable 5.. In contrast, extraversion was significantly associated with comorbidity per se. Subjects with high extraversion had an SOR 213% as high Ž95% CI s 102᎐444%. as those with low extraversion Ž1.60 vs. 0.75.. In other words, subjects with high extraversion had more than twice the odds of having another disorder given the presence of a single disorder. There was a trend for subjects with high agreeableness to have a higher SOR Ž238%, 95% CI s 92᎐619%. than those with low agreeableness Ž2.33 vs. 0.98.. Neither openness nor conscientiousness had a statistically significant relationship with comorbidity per se. Given the possibility of a compositional bias for the extraversion finding Ži.e. that one or a few pairwise ORs heavily influenced the SORs at different levels of extraversion., we performed logistic regression analyses for each pair of diagnoses, stratified by extraversion level ŽTable 6.. We performed these analyses unadjusted Žas

shown. and adjusted for relationships between neuroticism, extraversion, age, and gender and the prevalences of disorders Žas in the model represented in Table 5 ᎏ results not shown.. In most cases, the pairwise ORs were lowest for the low extraversion group, and higher in the average and high extraversion groups. There were often but not always steadily higher ORs from one extraversion level to the next. Therefore, a compositional bias was not evident. Because of lower disorder prevalences in the high extraversion group Žespecially for social phobia and agoraphobia., there were several undefined ORs for this group Ži.e. at least one empty cell in corresponding 2 = 2 tables.. The unadjusted results Žwhich were very similar to the adjusted results . demonstrate that the finding of increased comorbidity per se in those with high extraversion is

Table 4 Adjusted lifetime comorbidity among SCAN DSM-III-R disorders a Adjusted for

SOR

Neuroticism Extraversion Age Gender All four b

1.34 1.59 1.69 1.54 1.11

a

95% CI Ž0.95᎐1.89.c Ž1.10᎐2.30.U Ž1.20᎐2.38.UU Ž1.08᎐2.20.U Ž0.79᎐1.56.

Simple phobia, social phobia, agoraphobia, panic disorder, and major depression. b Neuroticism, extraversion, age, and gender. SORs summary odds ratio for all 5 disorders. CI s confidence interval. c Trend Ž P- 0.1.. U P - 0.05 ᎏ ) 1.0. UU P- 0.005 ᎏ ) 1.0.

Factor score

Low: - 45 Average: 45᎐55 High: ) 55 a

Neuroticism

Extraversion

Openness

SOR

SOR

SOR

0.73 1.01 1.32

95% CI Ž0.38᎐1.00. Ž0.46᎐1.49. Ž0.55᎐2.02.

0.75 1.45 1.60

95% CI Ž0.49᎐1.16. Ž0.67᎐3.14. Ž0.76᎐3.35.U

1.22 1.25 0.66

95% CI Ž0.80᎐1.86. Ž0.56᎐2.79. Ž0.31᎐1.40.

Agreeableness

Conscientiousness

SOR

95% CI

SOR

95% CI

Ž0.60᎐1.59. Ž0.37᎐1.42. Ž0.90᎐6.06.c

1.26 0.78 1.36

Ž0.74᎐2.12. Ž0.39᎐1.56. Ž0.51᎐3.60.

0.98 0.72 2.33

Simple phobia, social phobia, agoraphobia, panic disorder, and major depression. Adjusted for associations of neuroticism, extraversion, age, and gender with disorder prevalences. SORs summary odds ratio for all 5 disorders; CI s confidence interval. c Trend Ž P - 0.1. ᎏ higher than low agreeableness group. U P- 0.05 ᎏ higher than the low extraversion group. b

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Table 5 Adjusted lifetime comorbidity among SCAN DSM-III-R disorders a , stratified by personality factor scores b

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82

Table 6 Unadjusted lifetime comorbidity of SCAN DSM-III-R disorders, stratified by extraversion factor scores Simple phobia

Social phobia

b

b

Agoraphobia

Panic disorder

OR

q rq

OR

q rq

OR

q rqb

OR

Extraversion - 45 Ž n s 118. Social phobia 7 Agoraphobia 3 Panic disorder 1 Major depression 5

1.3 1.0 0.3 1.1

᎐ 4 4 5

᎐ 1.7 1.9 1.1

᎐ 2 2

᎐ 1.7 0.8

᎐ 4

᎐ 2.6

Extraversion 45᎐5 Ž n s 133. Social phobia 4 Agoraphobia 4 Panic disorder 3 Major depression 4

1.9 2.7 1.2 0.6

᎐ 3 3 4

᎐ 7.2 5.3 3.1

᎐ 2 4

᎐ 3.6 4.4

᎐ 4

᎐ 3.1

2.4

᎐ 1

᎐ 16

a

a

q rq

Extraversion ) 55 Ž n s 69. Social phobia 2 a Agoraphobia Panic disorder 1 Major depression 6

a

1.7 2.9

2

2.6

b

᎐

᎐

a

a

1

3.8

᎐

a

᎐

a

a

at least one empty cell in corresponding 2 = 2 table. q rq s number of subjects with both disorders. ORs odds ratio. b

also not an artifact of the complex statistical modeling represented in Table 5. We did further analyses to assess whether the findings above would generalize to the population of survivors of the original Baltimore ECA survey, using a differential weighting procedure which incorporated demographic and selection information. The results were almost identical to those presented above; that is, neuroticism was associated with all of the disorders of interest; introversion was associated with social phobia and agoraphobia; and extraversion was associated with stronger relationships among disorders.

4. Discussion Our results indicate that the associations among phobic, panic, and major depressive disorders are substantially reduced when personality correlates in common Ži.e. neuroticism and introversion. are taken into account. The SOR point estimate was most substantially reduced Žfrom 1.72 to 1.34. when associations between neuroticism and dis-

order prevalences were taken into account. Indeed, after adjusting for neuroticism, this summary association among disorders was not much greater than that expected by chance Žthe confidence interval included 1.0.. The situation for extraversion was more complex. The summary association among disorders was slightly reduced when associations between introversion and disorder prevalences were taken into account. However, high extraversion was associated with increased comorbidity per se; subjects with high extraversion had an association among disorders 213% as high as those with low extraversion. The finding that high extraversion is associated with increased comorbidity per se is novel and intriguing. Though this may seem counterintuitive, it is important to remember that the analytic questions addressed by models b and c ŽFig. 1. are fundamentally different. The analytic question in b is, ‘to what extent are disorders associated with each other if common correlates like personality traits are taken into account?’ The analytic question in c is, ‘to what extent are disorders associated with each other at different

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levels of personality factors, independent of prevalence?’ The answer to the former question could be anticipated, to some extent, by prior research. However, the latter question has not been addressed previously, to our knowledge. It may be that extraverts are more susceptible to global deterioration when distressed with any anxiety or depressive conditions. Attempts to replicate this unexpected finding are in order, especially given the number of comparisons made. The unadjusted OR point estimates reflecting pairwise comorbidity among the disorders of interest were almost all above 1.0 in this study, but they were generally smaller than those reported by Kessler Ž1995. for the ECA and National Comorbidity Surveys. This may reflect differences in instruments ŽSCAN vs. DIS and Composite Interview Diagnostic Instrument ., interviewers Žpsychiatrists vs. non-clinicians ., selection, or analytic methods ŽKessler did not use DSM diagnostic hierarchy rules in his analyses .. Our findings regarding relationships between neuroticism, extraversion, age, gender, and the prevalences of disorders are in agreement with previous studies conducted in various settings ŽEysenck and Rachman, 1965; Liebowitz et al., 1979; Hirschfeld et al., 1983, 1989; Solyom et al., 1986; Kendler et al., 1993; Kessler et al., 1994; Trull and Sher, 1994; Horwath and Weissman, 1995.. This study included only some of the anxiety disorders and one unipolar depressive disorder. Future investigations should include larger samples and a greater range of diagnoses Že.g. generalized anxiety disorder, obsessive᎐compulsive disorder, post-traumatic stress disorder, and dysthymia.. Larger samples will make analyses of concurrent comorbidity possible; here, we focused on lifetime comorbidity in order to enhance statistical power. An important limitation of this study is its cross-sectional nature. Previous studies have shown that neuroticism both predicts future onset and is influenced by the state of major depression ŽLiebowitz et al., 1979; Hirschfeld et al., 1983, 1989; Kendler et al., 1993.; also, high neuroticism predicts poor prognosis in terms of chronicity, etc. ŽWeissman et al., 1978; Hirschfeld et al., 1986; Frank et al., 1987; Surtees and Wainwright, 1996..

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Consistent with these studies, we found that subjects with current major depression in our sample had higher mean neuroticism scores than those in remission; also, those in remission had higher mean neuroticism scores than those with no history of major depression ŽBienvenu et al., in press.. The literature on etiologic relationships between normal personality traits and anxiety disorders is more limited ŽWidiger and Trull, 1992; Clark et al., 1994.. Though Reich et al. Ž1986. reported state᎐trait confounding in panic disorder, these authors did not assess neuroticism. There is some longitudinal evidence that constructs similar to neuroticism predispose to anxiety disorders ŽAngst and Vollrath, 1991; Krueger, 1999a. and that state᎐trait confounding is not operative ŽPerna et al., 1992.; we found no evidence of state᎐trait confounding at the factor level in subjects with anxiety disorders in our sample ŽBienvenu et al., in press.. Nevertheless, it is possible that we over-adjusted for personality factors in our adjusted estimates of comorbidity. That is, anxiety and depressive states could have influenced measures of normal personality traits, which may not perfectly reflect premorbid traits. A particularly powerful approach to understand etiologic mechanisms would be a longitudinal genetic epidemiologic study, with attention to both genetic and environmental variables that could affect personality and psychiatric disorder risk ŽRutter et al., 1997.. Such work could integrate findings that suggest that childhood adversity is a common risk factor for anxiety and depressive disorders and, thus, their comorbidity ŽBrown et al., 1996.. There is evidence that neuroticism and anxiety and depressive disorders share common genetic determinants ŽAndrews et al., 1990a; Kendler et al., 1993.. GEE2 is well suited to comorbidity analyses with dichotomous outcomes, as illustrated in this article. Another potential application in psychiatric research is in family studies. With GEE2, one can detect both inter- and intra-class aggregations of binary traits, while incorporating effects of environmental covariates ŽLiang and Beaty, 1991.. In conclusion, neuroticism and, to a limited extent, introversion are associated with greater

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prevalences of phobic, panic, and major depressive disorders and the comorbidity that results from higher prevalences. In contrast, high extraversion is associated with increased comorbidity per se, independent of prevalence. It is possible that neuroticism and introversion predispose persons to develop one or more conditions, while extraversion predisposes persons to develop more, once one has developed. Further work is necessary to clarify etiologic mechanisms.

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