Patterns of co-morbidity with anxiety disorders in
Chinese women with recurrent major depression
Y. Li1, S. Shi2,3, F. Yang3, J. Gao4, Youhui Li5, M. Tao6, G. Wang7, K. Zhang8, C. Gao9, L. Liu10, Kan Li11,
Keqing Li12, Y. Liu13, Xumei Wang14, J. Zhang15, L. Lv16, Xueyi Wang17, Q. Chen18, J. Hu19, L. Sun20,
J. Shi21, Y. Chen22, D. Xie1, J. Flint1, K. S. Kendler23* and Z. Zhang24*
1Wellcome Trust Center for Human Genetics, Roosevelt Drive, Oxford, UK;2Fudan University Affiliated Huashan Hospital, Shanghai, People’s
Republic of China;3Shanghai Jiao Tong University School of Medicine Affiliated Shanghai Mental Health Center, Shanghai, People’s Republic of
China;4Zhejiang Traditional Chinese Medical Hospital, Hangzhou, Zhejiang, People’s Republic of China;5No. 1 Hospital of Zhengzhou
University, Zhengzhou, Henan, People’s Republic of China;6Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou,
Zhejiang, People’s Republic of China;7Beijing Anding Hospital, Capital Medical University, Xicheng District, Beijing, People’s Republic of
China;8No. 1 Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China;9No. 1 Hospital of Medical College of Xian
Jiaotong University, Xi’an, Shaanxi, People’s Republic of China;10Shandong Mental Health Center, Jinan, Shandong, People’s Republic of China;
11Mental Hospital of Jiangxi Province, Nanchang, Jiangxi, People’s Republic of China;12Hebei Mental Health Center, Baoding, Hebei, People’s
Republic of China;13The First Hospital of China Medical University, He Ping District, Shenyang, Liaoning, People’s Republic of China;
14ShengJing Hospital of China Medical University, Shenyang, Liaoning, People’s Republic of China;15No. 3 Affiliated Hospital of Sun Yat-sen
University, Tian He District, Guangzhou, Guangdong, People’s Republic of China;16Psychiatric Hospital of Henan Province, No. 388 Jian She
Zhong Lu, Xinxiang, Henan, 453002, People’s Republic of China;17The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s
Republic of China;18Dalian No. 7 People’s Hospital and Dalian Mental Health Center, Gan Jing Zi District, Dalian, Liaoning, People’s Republic
of China;19No. 1 Mental Health Center Affiliated Harbin Medical University, Nangang District, Harbin, Heilongjiang, People’s Republic of
China;20Jilin Brain Hospital, Siping, Jilin, People’s Republic of China;21Xi’an Mental Health Center, Qujiang Xin District, Xi’an, Shaanxi,
People’s Republic of China;22Clinical Trial Service Unit, Richard Doll Building, Roosevelt Drive, Oxford, UK;23Virginia Institute for
Psychiatric and Behavioral Genetics of Virginia Commonwealth University, Richmond, VA, USA;24No. 4 Affiliated Hospital of Jiangsu
University, Zhenjiang, Jiangsu, People’s Republic of China
Background. Studies conducted in Europe and the USA have shown that co-morbidity between major depressive
disorder (MDD) and anxiety disorders is associated with various MDD-related features, including clinical symptoms,
degree of familial aggregation and socio-economic status. However, few studies have investigated whether these
patterns of association vary across different co-morbid anxiety disorders. Here, using a large cohort of Chinese
women with recurrent MDD, we examine the prevalence and associated clinical features of co-morbid anxiety
Method. A total of 1970 female Chinese MDD patients with or without seven co-morbid anxiety disorders [including
generalized anxiety disorder (GAD), panic disorder, and five phobia subtypes] were ascertained in the CONVERGE
study. Generalized linear models were used to model association between co-morbid anxiety disorders and various
Results. The lifetime prevalence rate for any type of co-morbid anxiety disorder is 60.2%. Panic and social phobia
significantly predict an increased family history of MDD. GAD and animal phobia predict an earlier onset of MDD
and a higher number of MDD episodes, respectively. Panic and GAD predict a higher number of DSM-IV diagnostic
criteria. GAD and blood-injury phobia are both significantly associated with suicidal attempt with opposite effects.
All seven co-morbid anxiety disorders predict higher neuroticism.
Conclusions. Patterns of co-morbidity between MDD and anxiety are consistent with findings from the US and
European studies; the seven co-morbid anxiety disorders are heterogeneous when tested for association with various
Received 6 August 2011; Revised 17 October 2011; Accepted 31 October 2011; First published online 30 November 2011
Key words: Co-morbid anxiety disorders, major depression.
The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons
Attribution-NonCommercial-ShareAlike licence <http://creativecommons.org/licenses/by-nc-sa/2.5/>. The written permission of
Cambridge University Press must be obtained for commercial re-use.
* Address for correspondence: K. S. Kendler, M.D., Virginia Institute for Psychiatric and Behavioral Genetics of Virginia Commonwealth
University, Box 980126, Richmond, VA 232980126, USA.
(Email: email@example.com) [K.S.K.]
(Email: firstname.lastname@example.org) [Z. Zhang]
Psychological Medicine (2012), 42, 1239–1248.
f Cambridge University Press 2011
A large number of studies agree that anxiety disorders
occur in patients with major depressive disorder
(MDD) far more frequently than expected by chance
(Kessler et al. 1996; Gorwood, 2004). In fact, in clinical
settings, more than half of MDD patients have co-
morbid anxiety disorders (Zimmerman & Chelminski,
2003). Furthermore, a number of clinical features
characterize MDD patients with co-morbid anxiety.
Typically, their depressive disorder is more severe,
with more episodes, earlier onset age, greater suicidal
risk and poorer treatment response (Brown et al. 2001);
they have a lower social competence (Cerda ´ et al.
2010); and they are more likely to have a family his-
tory of MDD (Clayton et al. 1991; Kendler et al. 1992).
A number of explanations have been put forward to
explain this co-morbidity. In part, it appears to arise
from a shared genetic propensity to both anxiety and
depression: multivariate twin modeling has identified
a common genetic factor contributing to internalizing
disorders, including MDD, generalized anxiety dis-
order (GAD) and phobias (Kendler et al. 2003).
However, a common genetic origin is clearly not
the whole explanation. Genetic studies themselves
indicate that there are some genetic factors that act
specifically on anxiety and MDD (Kendler et al. 2003).
They also show that the genetic factors explain only
part of the co-occurrence of illnesses. We know that
non-shared environment explains almost all the co-
variance between MDD and agoraphobia and more
than 40% between MDD and GAD for female twins
(Cerda ´ et al. 2010). Our understanding of the non-
genetic factors that drive co-morbidity is still very
limited. The responsible environmental factors remain
to be identified but it has been shown that low socio-
economic status in childhood and adult unemploy-
ment distinguishes the MDD GAD co-morbid group
from the MDD-only group (Cerda ´ et al. 2010).
Studies that investigate the prevalence and features
of MDD associated with co-morbid anxiety typically
examine the relationship between MDD and a single
anxiety disorder (such as GAD or panic disorder)
(Garvey et al. 1987; Reich et al. 1993; Grunhaus et al.
1994; Maier et al. 1995; Kessler et al. 1998, 1999;
Gorwood, 2004; Kendler et al. 2007). A few studies
(Pini et al. 1997; Fava et al. 2000; Lamers et al. 2011)
report that there are differences in the prevalence rates
of co-morbid anxiety disorders, but rarely distinguish
or control for different co-morbid anxiety disorders
when testing for association with MDD-related fea-
tures (Kessler et al. 2003; Fava et al. 2004; Rhebergen
et al. 2011). This leaves open an important question: is
there similarity in the clinical features of patients with
MDD with different co-morbid anxiety disorders?
One possibility is that co-morbidity arises from
separate and independent associations with each
anxiety disorder, as reflected in the pattern of associ-
ations with symptoms, severity indices and risk
factors. The alternative is that co-morbidity reflects a
common mechanism among all anxiety disorders.
In this article, we examine co-morbid anxiety in a
large cohort of female Han Chinese recruited through
clinical settings and diagnosed with recurrent MDD
using a structured clinical interview. We set out to
determine first whether co-morbidity between anxiety
and depression was similar in China to that observed
elsewhere in the world. Our information about co-
morbid anxiety disorders, and the attendant clinical
pattern, is currently derived almost exclusively from
studies of European and US populations. To our
knowledge, no one has examined whether the
same pattern of co-morbidity holds true for MDD in
China. Second, we asked how similar were the clinical
features of MDD patients with different anxiety dis-
orders, by comparing differences in association
between clinical features of MDD and different co-
morbid anxiety disorders. Distinguishing the clinical
features of different types of anxiety disorders helps
us to identify risk factors that are associated with
each anxiety disorder specifically, which may in turn
alter the ways patients with MDD who have co-
morbid anxiety disorders are assessed and the treat-
ments they are offered.
Data for the present study were drawn from the on-
going China, Oxford and VCU Experimental Research
on Genetic Epidemiology (CONVERGE) study of
MDD. The analysis was based on a total of 1970 cases
recruited from 51 mental health centers and psychi-
atric departments of general medical hospitals in
40 cities in 21 provinces.
The project utilized samples collected for a genome-
wide association study of MDD. Given evidence that
the genetic effects on MDD are different between men
and women (Kendler et al. 2001), in order to control
for this known genetic heterogeneity, we collected
female participants only with four Han Chinese
grandparents. Cases were excluded if they had a pre-
existing history of bipolar disorder, any type of psy-
chosis or mental retardation. Cases were aged between
30 and 60 years, had two or more episodes of MDD
with the first episode occurring between the ages of
14 and 50 years, and had not abused drugs or alcohol
before their first episode.
All subjects were interviewed using a computerized
assessment system, which lasted on average 2 h.
All interviewers, who were postgraduate medical
1240Y. Li et al.
students, junior psychiatrists or senior nurses, were
trained by the CONVERGE team for a minimum of
1 week. The interview includes assessment of psy-
chopathology, demographic and personal charac-
teristics, and psychosocial functioning. Interviews were
tape-recorded and a proportion of them were listened
to by the trained editors, who provided feedback
on their quality. The study protocol was approved
centrally by the Ethical Review Board of Oxford
University and the ethics committee in participating
hospitals in China.
The diagnoses of depressive (dysthymia and MDD)
and anxiety disorders (GAD, panic disorder with
or without agoraphobia) were established with the
Composite International Diagnostic Interview (World
Health Organization lifetime version 2.1; Chinese
version), which classifies diagnoses according to the
Diagnostic and Statistical Manual of Mental Disorders,
fourth edition (DSM-IV) criteria. The interview was
originally translated into Mandarin by a team of psy-
chiatrists in Shanghai Mental Health Center, with the
translation reviewed and modified by members of the
CONVERGE team. Phobias, divided into five subtypes
(animal, situational, social and blood-injury, and
agoraphobia), were diagnosed using an adaptation
of DSM-IV criterion D (APA, 1994) requiring one or
more unreasonable fears, including fears of different
animals, social phobia and agoraphobia, that objec-
tively interfered with the respondents’ life or resulted
in severe anxiety when exposed to the phobic stimu-
lus. The section on the assessment of phobias was
translated by the CONVERGE team from the inter-
view used in the Virginia Adult Twin Study of
Psychiatric and Substance Use Disorders (VATSPUD)
(Kendler & Prescott, 2006). The history of lifetime
major depression in the parents and siblings was
assessed using the Family History Research Diagnos-
tic criteria (Endicott et al. 1975). Neuroticism was
measured with the 23-item Eysenck Personality
Questionnaire (Eysenck & Eysenck, 1975).
All interview sections were fully computerized into
a bilingual system of Mandarin and English devel-
oped in-house in Oxford, UK, called SysQ (a self-
administered interview system). Skip patterns were
built into SysQ. Interviews were administered by
trained interviewers and entered offline in real time
onto SysQ, which was installed in laptop computers.
Once an interview was completed, a backup file
containing all the previously entered interview data
could be generated with a database-compatible
format. The backup file together with an audio record
of the entire interview was uploaded to a designated
server currently maintained in Beijing by a service
provider. All the uploaded files in the Beijing server
were then transferred to an Oxford server quarterly.
The diagnoses of MDD were based on information
collected in the medical records and DSM-IV symp-
toms during the worst episode. Symptoms infor-
mation collected for the diagnoses of co-morbid
disorders of MDD was for lifetime.
Statistical methods: generalized linear regression
model choosing, analysis of variance (ANOVA)
In order to test whether co-morbid anxiety disorders
significantly predict various MDD features, including
family history, age of onset, number of episodes,
number of DSM-IV diagnostic criteria, suicidal at-
tempt and neuroticism score, generalized linear
models (GLMs) with different link functions were
chosen for modeling different types of dependent
variables controlling for age. Data for the age of onset
were tested for normality and modeled with linear
regression, and results represented as the standar-
dized parameter estimate (b). Suicidal attempt was
modeled with logistic regression and results re-
presented as odds ratios (ORs). The family history
variable, represented by the total number of first-
degree family members among the two parents and
all the siblings with a history of MDD, could be con-
sidered as a series of Bernoulli trials with a finite
number of trials in statistical terms; hence binomial
regression was used for modeling the association,
weighted against the total number of family members
for each subject. The same reason and choice were
applied to variables such as the number of DSM-IV
diagnostic criteria and the neuroticism score, which
could also be considered as a finite number of
Bernoulli trials. Poisson regression was chosen to
model the number of episodes data, as it is considered
to be count data with an upper limit of 96 (denoting 96
or more) being removed. Since binomial and Poisson
regressions model the natural logarithms of the
count and the event rate, respectively, results are re-
presented by count ratio (CR) and rate ratio (RR), both
calculated by exponentiating the regression coeff-
icients. The statistical tests were implemented using R
(R Development Core Team, 2011), which allows the
specification of quasibinomial and quasipoisson link
functions. They differ from binomial and Poisson
functions only in that the dispersion parameter is not
fixed at 1; in other words, over-dispersion is included
in the model, which controls for the over-reporting of
In addition to calculating the individual effects of
the seven co-morbid anxieties, the method of Analysis
of Deviance for GLM Fits (ANOVA) was used to
Anxiety disorders in women with major depression1241
examine whether the anxiety regression coefficients in
the multiple GLMs were homogeneous or hetero-
geneous in predicting each of the MDD features. Two
GLM objects were specified in ANOVA; one with a
derived independent variable which is calculated as
the sum of all seven anxiety diagnostic status, nested
by another containing all the seven co-morbid anxiety
diagnoses as additive independent variables. The
result gives a table with a row for the residual degrees
of freedom and deviance for each model. Test statistics
could be specified in ANOVA, comparing the re-
duction in deviance for the row to the residuals. For
models with dispersion estimated by moments, such
as Gaussian, quasibinomial and quasipoisson fits, the
F test is considered to be the most appropriate.
The lifetime prevalence rate in our sample of women
with recurrent MDD for any of the seven co-morbid
anxiety disorders was 60.2%. The rates of the indi-
vidual anxiety disorders in our cohort were 26.4% for
GAD, 10.1% for panic disorder, 15.0% for agora-
phobia, 14.3% for social phobia, 28.0% for animal
phobia, 20.3% for situational phobia, and 21.7% for
The mean number of co-morbid anxiety disorders
among the MDD patients was 1.35 (S.D.=1.56). Among
the 1136 MDD (59.8%) patients who had at least one of
the seven co-morbid anxiety disorders, 59.3% patients
had two or more co-morbid anxiety disorders. Of the
seven anxiety disorders, there are 128 possible combi-
nations of what a patient might or might not have.
Table 1 contains the top 13 combinations including the
40.2% of MDD patients without any of the seven co-
morbid anxiety disorders, 16.2% with GAD only, 8.8%
with animal phobia only, and 5.1% with blood-injury
phobia only, etc. The top 12 combinations (excluding
the non-anxious group) accounted for 54.1% of all the
MDD cases with co-morbid anxiety disorders. Because
so many patients had more than one condition, we
used a multiple regression model in order to tease
apart individual effects.
We looked at the relationship between clinical
features of MDD and the seven anxiety disorders,
attempting to identify those that were shared between
disorders or were disorder-specific. Tables 2 and 3
contain the summary statistics of the variables in-
cluded in the regression analysis. We first tested the
effect of each disorder separately. Then we combined
all disorders into one model to test for their joint effect
on each MDD feature.
We found significant effects for each disorder when
tested separately, as well as combining the seven
diagnoses into one variable – any type of anxiety dis-
order (Table 4). Results for jointly testing disorders are
more complex and are shown in Table 5. Panic and
social phobia independently significantly predicted an
increased family history of MDD, with social phobia
showing the highest effect (CR 1.52, p=5.58r10x4),
controlling for the additive effects of the other co-
morbid anxiety disorders. GAD with one or more
Table 2. Variables included in general linear models
Age of onset, years
Number of episodes
(excluding 96 or morea)
Number of DSM-IV diagnostic criteria
Number of positively diagnosed
Number of family members
S.D., Standard deviation; NA, number of missing data
entries; DSM, Diagnostic and Statistical Manual of Mental
aSee Statistical methods section.
Table 1. Top 13 combinations among the total of 128 possibilities
with seven co-morbid anxiety disorders that could either be
present or not present in every patient with major depressive
128 possibilitiesNumber (%)
Top 13 combinations
Animal phobia only
Blood-injury phobia only
Situational phobia only
GAD and animal phobia
Animal and blood-injury phobia
Animal and situational phobia
Animal and situational and
Social phobia only
GAD and blood-injury phobia
Total of top 12 combinations
(excluding the non-anxious group)
Total of other combinations
(excluding the non-anxious group)
Total (excluding the non-anxious group) 1136
GAD, Generalized anxiety disorder.
1242Y. Li et al.
than 1-month duration (b=x0.04, p=4.71r10x2)
significantly predicted earlier MDD onset age. Animal
phobia (RR 1.18, p=1.12r10x2) significantly predicted
higher number of MDD episodes. Panic and GAD
independently significantly predicted higher numbers
of positive DSM-IV diagnostic criteria, with GAD
(CR 1.70, p=3.62r10x8) showing the largest and most
significant effect. GAD and blood-injury phobia were
significantly associated with the probability of a sui-
cide attempt, with GAD predicting higher probability
(OR 1.38, p=9.95r10x3), and blood-injury phobia
predicting lower probability (OR 0.66, p=9.35r10x3).
All anxiety disorders independently and significantly
predicted a higher neuroticism score, with GAD
(CR 1.69, p=7.42r10x22) showing the highest effect.
We looked for common patterns in the way that
anxiety disorders made an impact on the clinical
features of MDD. Our hypothesis was that we would
find some clinical features on which one or more
anxiety disorder had similar impacts, as assessed
Table 3. Suicide-related response rates and major depressive disorder prevalence rates for
NA, Number of missing data entries.
Table 4. Effects of generalized linear models testing for association between each co-morbid
anxiety disorder as well as any of the seven co-morbid anxiety disorders, and major
depressive disorder features taken one at a timea
FH, Family history; AAO, age of onset; NE, number of episodes; NDC, number of
Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria; SA, suicidal
attempt; N, neuroticism; GAD, generalized anxiety disorder; OR, odds ratio; CR,
count ratio; RR, rate ratio.
aValues reported for the four types of regression models: linear regression: stan-
dardized parameter estimates (b); logistic regression: OR; quasi-binomial re-
gression: CR; quasi-Poisson regression: RR. ORs, CRs and RRs were calculated by
exponentiating the regression coefficients.
bQuasibinomial regression was used to model FH, NDC and N.
cLinear regression was used to model AAO.
dQuasipoisson regression was used to model NE.
eLogistic regression was used to model SA.
*p<0.05, ** p<0.01, *** p<0.001.
#p<1, ## p<0.1.
Anxiety disorders in women with major depression 1243
by the equivalence of their regression coefficients.
We applied a global heterogeneity test for the multiple
regression coefficients. The results showed that coeffi-
cients of the seven co-morbid anxiety disorders were
homogeneous with respect to their association with
family history, age of onset and the number of episode
data. However, they were heterogeneous with respect
to their association with the number of DSM-IV diag-
nostic criteria (F=3.48, p=1.99r10x3), suicidal at-
tempt (F=2.79, p=1.02r10x2) and neuroticism score
(F=5.72, p=6.64r10x6) (Table 6). When the diag-
noses of all seven co-morbid anxiety disorders were
included in a multiple regression model, controlling
for each other’s additive effects, the ones that were
significant when tested for association with various
MDD features were different, such that only GAD
predicted earlier MDD onset, whereas only animal
phobia predicted more episodes of MDD. Results from
global heterogeneity tests also indicated that MDD
patients with different co-morbid anxiety disorders
manifested different clinical features.
Our work establishes two important findings: first, in
China co-morbidity between MDD and anxiety dis-
orders is similar to that reported in the West; second,
there is important heterogeneity in the association
between anxiety disorders and some clinical features
of MDD. We discuss these two points below.
The lifetime prevalence rate for any type of co-
morbid anxiety disorder among MDD patients re-
cruited through clinical settings is 60.2%. This is
higher than the 50.6% lifetime rate reported in the
Depression Research Program with patients recruited
through clinical settings (Fava et al. 2000), and lower
Table 6. ANOVA F test examining the heterogeneity of the multiple regression coefficients of the seven co-morbid anxiety disorders in
predicting each of the six major depressive disorder features
AnxietyFH AAONENDC SAN
ANOVA F test
ANOVA p value
ANOVA, Analysis of variance; FH, family history; AAO, age of onset; NE, number of episodes; NDC, number of Diagnostic
and Statistical Manual of Mental Disorders (DSM)-IV criteria; SA, suicidal attempt; N, neuroticism.
Table 5. Effects of multivariate generalized linear models testing for association between the seven co-morbid anxiety disorders all
considered together and various major depressive disorder featuresa
FH, Family history; AAO, age of onset; NE, number of episodes; NDC, number of Diagnostic and Statistical Manual of
Mental Disorders (DSM)-IV criteria; SA, suicidal attempt; N, neuroticism; GAD, generalized anxiety disorder; OR, odds ratio;
CR, count ratio; RR, rate ratio.
aValues reported for the four types of regression models: linear regression: standardized parameter estimates (b);
logistic regression: OR; quasi-binomial regression: CR; quasi-Poisson regression: RR. ORs, CRs and RRs were calculated
by exponentiating the regression coefficients.
bQuasibinomial regression was used to model FH, NDC and N.
cLinear regression was used to model AAO.
dQuasipoisson regression was used to model NE.
eLogistic regression was used to model SA.
fThe over-dispersion parameter was included in the model due to the quasi-terms.
*p<0.05, ** p<0.01, *** p<0.001.
#p<1, ## p<0.1.
1244 Y. Li et al.
than the 75% lifetime rate reported in the Netherlands
Study of Depression and Anxiety (NESDA) with
patients mostly recruited through primary care (54%)
and specialized mental health settings (27%) (Lamers
et al. 2011). Additionally, the reported lifetime
co-morbidity rates for panic disorder among MDD
patients in a cross-national epidemiological survey
study are 10.7% in the USA, 16.2% in West Germany,
17% in Korea and 5.9% in Taiwan (Weissman et al.
1996). The figure in Taiwan is lower than the 10.1%
reported in our study. Different sampling frames and
disorder diagnostic criteria should be taken into con-
sideration when comparing these figures; for example,
our study recruited patients with recurrent MDD
through clinical settings while the cross-national
epidemiological survey studied community samples.
Despite the sampling differences, we found that the
clinical features of co-morbidity are generally consist-
ent in China with those reported elsewhere in the
world: co-morbidity is associated with increased
MDD severity and chronic course, suicidal attempts,
higher rates of neuroticism, and increased familial
aggregation (Coryell et al. 1992; Kessler et al. 1998,
2003; Fava et al. 2000, 2004; Sareen et al. 2005; Bolton
et al. 2008; Hettema, 2008; Howland et al. 2009; Lamers
et al. 2011). The similarity we observed between co-
morbidity in China and the rest of the world en-
courages us to believe that our other findings will be
applicable elsewhere. The diagnoses of MDD and co-
morbid anxiety disorders in our sample are lifetime.
In a large clinical study, the current co-morbidity rate
of any anxiety disorder was found to be 64% among
current MDD patients, whereas the co-morbidity rate
of lifetime diagnoses was 95% (Brown et al. 2001).
Hence we expect a large proportion of our patients
with lifetime co-morbidity also would have had con-
current co-morbidity. However, this cannot be proved
with our data.
Our second important finding concerns the hetero-
geneity of co-morbid anxiety disorders. Our large data
set allowed us to ask whether co-morbidity between
MDD and one anxiety disorder is the same as co-
morbidity between MDD and other anxiety disorders:
for example, whether patients with co-morbid GAD
look more or less similar in their clinical presentation
and known risk factors for MDD to patients with co-
morbid social phobia. Our results indicate that there is
considerable heterogeneity, and that when we talk of
co-morbid anxiety it would be best to mean by this
distinct co-morbidities with specific anxiety disorders
rather than generic co-morbidity across all the anxiety
Significant heterogeneity was observed for three of
the six MDD features that were tested for association
with co-morbid anxiety disorders. They are (i) the
number of MDD diagnostic criteria, (ii) suicidal at-
tempt and, (iii) neuroticism measure. When control-
ling for the effects of all seven co-morbid anxiety
disorders, we found that GAD predicts earlier onset
and a higher number of DSM-IV criteria; panic dis-
order predicts higher number of DSM-IV criteria;
animal phobia predicts higher number of episodes.
There are conflicting results about whether co-morbid
anxiety disorders are risk factors for suicide attempt
among MDD patients (Roy, 1993; Sareen et al. 2005;
Claassen et al. 2007; Bolton et al. 2008; Brown et al.
2010; Perroud et al. 2010). Our findings suggest
that some co-morbid anxiety disorders (i.e. GAD)
increase the risk for suicidal attempt, whereas others
(i.e. blood-injury phobia) may be protective perhaps
because the disorder is associated with a fear of death.
Hence, treating all types of anxiety disorder together
when testing for association with suicidal attempt
might counterbalance the opposite effects, resulting in
insignificant findings. Studies examining the relation-
ship between co-morbid panic disorder and suicidal
attempt show that either panic disorder increases the
risk for suicidal attempt (Claassen et al. 2007) or the
association is insignificant (Placidi et al. 2000). Our
results disagree with most previous findings in sug-
gesting that co-morbid panic disorder is protective
against suicidal attempt. However, if we apply a
conservative correction for multiple testing then this
observation becomes non-significant, so only further
study of this question will determine if this finding
in Chinese women represents a true or false-positive
result. Neuroticism showed the clearest pattern of
heterogeneity: the test of heterogeneity gave the most
significant of all results (p=6.64r10x6).
We hypothesize that examining anxiety disorders as
a single class hides important heterogeneity in their
association with MDD. Heterogeneity is likely to be
due to two factors: (i) opposite effects among different
anxiety disorders; and (ii) individual effects of differ-
ent anxiety disorders. Evidence for the former comes
from results on suicidal attempt. While we found that
all seven co-morbid anxiety disorders were signifi-
cantly associated with suicidal attempt when tested
separately, the direction of the effect differs: some
anxiety disorders increase the occurrence of suicide
attempts (GAD), while others (panic and blood-injury
phobia) are protective (even when controlling for all
the other co-morbid anxiety disorders).
Evidence for the latter comes from results on the
number of DSM-IV diagnostic criteria and neuro-
ticism. One important source for heterogeneity lies
in differing genetic susceptibilities to each co-morbid
condition. Thus, while we know that there is a
common genetic predisposition to MDD and anxiety
(Bienvenu et al. 2001; Khan et al. 2005; Middeldorp
Anxiety disorders in women with major depression 1245
et al. 2005; Kendler et al. 2007; Spinhoven et al. 2009;
Rhebergen et al. 2011), we also know that there are
some unique genetic effects on anxiety disorders.
For example, some genetic effects are shared between
neuroticism and anxiety disorders; others are unique.
The pattern of what is shared and what is common is
specific to each condition.
The findings from the study have implications for
the recognition, diagnosis and possibly treatment of
MDD patients with different co-morbid anxiety dis-
orders. For instance, the presence of GAD should alert
doctors that the MDD patient is likely to be of a more
severe kind, indicated by earlier onset and more
symptom criteria, with suicidal ideation. Hence inter-
vention could be applied at an earlier stage to prevent
more negative outcomes.
The reported results should be interpreted in the
context of five potential limitations.
First, we only studied female patients and the
relevance of our results to male patients is unknown.
Second, the criteria used for the diagnoses of co-
morbid disorders of MDD were lifetime; hence the
diagnoses of the seven anxiety disorders might not
be co-morbid as in they might not have occurred
concurrently with the worst episode of MDD. Third,
patients were recruited through clinical settings;
hence representativeness of our findings to the general
population in China and the rest of the world is un-
known. Fourth, cases recruited in the study were
patients with at least two episodes of MDD; hence
when co-morbid anxieties were tested for association
with the number of episodes data, the effects and sig-
nificance of effects were likely to be reduced compared
with samples that only fulfilled the clinical diagnoses
of MDD without the additional recruitment criteria.
This might also have implications for the results of
the global heterogeneity test for multiple regression
coefficients. Fifth, our study differs from traditional
family studies of anxiety disorders which involve the
personal interview of first-degree family members
(Crowe et al. 1983; Fyer et al. 1990; Brown et al. 1993;
Weissman et al. 1993). Given the size of our study, it
was only feasible to collect family history information
from the patient about first-degree family members.
An extensive literature on the family history method
indicates that, in general, it has low sensitivity but
high specificity (Andreasen et al. 1977, 1986; Roy et al.
1996), although some evidence for bias has been
detected (Kendler et al. 1991). Furthermore, due to the
design of our study, we do not have patients with
anxiety but without MDD; hence we cannot fully test
the transmission of MDD and the anxiety disorders.
Declaration of Interest
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