sex-specific self-reported mood changes by patients with bipolar disorder
TRANSCRIPT
JOURNALOF
PSYCHIATRIC
Journal of Psychiatric Research 39 (2005) 77–83RESEARCH
www.elsevier.com/locate/jpsychires
Sex-specific self-reported mood changes by patients withbipolar disorderq
Natalie Rasgona,b,*, Michael Bauerb,c, Paul Grofd, Laszlo Gyulaie, Shana Elmanb,Tasha Glennf, Peter C. Whybrowb
a Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Room 2360,
Palo Alto, CA 94305-5723, USAb Department of Psychiatry and Biobehavioral Sciences, Neuropsychiatric Institute and Hospital, University of California Los Angeles (UCLA),
Los Angeles, CA, USAc Department of Psychiatry and Psychotherapy, Humboldt-University at Berlin, Charit�e University Hospital, Berlin, Germany
d Department of Psychiatry, University of Ottawa, Royal Ottawa Hospital, Ottawa, Canadae Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
f ChronoRecord Association Inc., Fullerton, CA, USA
Received 4 August 2003; received in revised form 13 May 2004; accepted 17 May 2004
Abstract
Introduction: While the prevalence of bipolar disorder I is similar between men and women, the clinical course may differ. This
study investigated if there are differences in the clinical presentation of bipolar disorder between the sexes.
Methods:Mood patterns were documented using ChronoRecord software for self-reporting. Patients entered mood, medications,
sleep, life events and menstrual data daily acquired over the period of three months. 8662 Days of data were received from 80
patients: 3483 days from 35 men and 5179 days from 45 women.
Results: The distribution of the time spent in mood categories differed between men and women (p < :001). Men were depressed
17.0% of the time, euthymic 74.0% of the time and manic 5.6% of the time. Women were depressed 28.3% of the time, euthymic
64.2% of the time and manic 7.5% of the time. Over 80% of all reported symptoms for both sexes were mild. Women exhibited large
mood fluctuations (greater than 10 in either direction on a 100-unit scale) more frequently than men. Most of the reproductive aged
women (55%) reported significant mood changes across the menstrual cycle.
Conclusions: The clinical course of bipolar disorder differed between the sexes. Women reported depression and large fluctuations
in mood more frequently than men. Women also experienced mood changes across the menstrual cycle.
� 2004 Elsevier Ltd. All rights reserved.
Keywords: Bipolar disorder; Sex; Menstrual cycle; Mood changes; ChronoRecord software
1. Introduction
Some studies suggest that the course of bipolar dis-
order may vary by sex. Women may have a higher in-
cidence of bipolar II disorder (Tondo and Baldessarini,
1998; Baldassano et al., 2002) and may be more likely to
develop a rapid cycling course (Coryell et al., 1992).
qPresented at the American Psychiatric Association Annual Meet-
ing, Philadelphia, PA, May 18–23, 2002.* Corresponding author. Tel.: +1-650-724-6689; fax: +1-650-724-
3144.
E-mail address: [email protected] (N. Rasgon).
0022-3956/$ - see front matter � 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jpsychires.2004.05.006
Compared to men with bipolar disorder, women may
suffer more depressed (Angst, 1978; Perugi et al., 1990)and mixed episodes (Taylor and Abrams, 1981; McEl-
roy et al., 1995). While depressed, women more often
experience atypical features (Benazzi, 1999).
Several lines of evidence suggest an endocrine basis
for the observed differences in the clinical course of bi-
polar disorder between the sexes including (a) the re-
peated fluctuations of reproductive hormones during the
menstrual cycle, (b) the receipt of oral contraceptives(OC) and hormone replacement therapy which may
modulate the menstrual cycle and influence affective
78 N. Rasgon et al. / Journal of Psychiatric Research 39 (2005) 77–83
symptoms (Oinonen and Mazmanian, 2002; Zweifel and
O’Brien, 1997) and (c) a lifetime prevalence of thyroid
disease (excluding thyroid cancer) that is 4–10 times
higher in women (Whybrow, 1995). Furthermore, re-
productive endocrine abnormalities may be related tothe development of affective symptoms in women. A
high prevalence of menstrual abnormalities has been
reported, in many cases preceding the diagnosis of bi-
polar disorder (Rasgon et al., 2000, 2003). In addition,
anticonvulsant drugs that are routinely used to treat
bipolar disorder may influence serum levels of repro-
ductive hormones in women with epilepsy (Isojarvi
et al., 1993; Rattya et al., 2001), and to some extent inwomen with bipolar disorder (O’Donovan et al., 2002;
Akdeniz et al., 2003).
Increased understanding of sex specific issues in the
course of bipolar disorder may help to optimize treat-
ment throughout the patient’s lifetime. This study in-
vestigates the relationship between sex and mood
patterns, and the impact of the menstrual cycle on mood
using a prospective, longitudinal, naturalistic design tofollow a sample of individuals with bipolar disorder
receiving standard outpatient care. Daily self-reported
mood ratings were obtained for a 3-month period from
80 patients. The data were grouped by sex and com-
pared for differences in the frequency in mood categories
(depressed, euthymic and hypomanic/manic) and the
frequency of mood changes. Additionally, in women,
changes in mood across the menstrual cycle wereinvestigated.
2. Methods
Data for this study were collected in a multi-center
validation study of the ChronoRecord software re-
ported elsewhere (Bauer et al., 2004). Eighty patientswere consecutively recruited from the mood disorders
clinics at UCLA, the University of Ottawa, and the
University of Pennsylvania. After a complete explana-
tion of the study, all patients signed the written consent
form approved by the Institutional Review Board at
their respective institution.
All patients met the DSM-IV criteria for bipolar
disorder, diagnosed by clinical interview and confirmedwith the MINI International Neuropsychiatric Inter-
view (Sheehan et al., 1998). Other inclusion criteria
were: age 18 years or older, daily access to a personal
computer and the skills to use it, and fluency in English.
Patients with antisocial personality disorder or dementia
were excluded from the study. No other inclusion or
exclusion criteria were used to avoid creating a bias in
the patient sample. After one-half hour of training, thepatients were given ChronoRecord software to install on
their home computers. For a 3-month period, the pa-
tients entered mood, sleep, menstrual data, psychiatric
medications and life events daily, and weight weekly.
Self-reported ChronoRecord scores were compared with
clinician-rated Hamilton Depression Rating Scale
(HAMD) (Hamilton, 1960), and Young Mania Rating
Scale (YMRS) (Young et al., 1978), and paper-basedself-ratings on the Beck Depression Inventory (BDI)
(Beck, 1996) from four visits over the 3-month study
period (Bauer et al., 2004).
2.1. ChronoRecord
ChronoRecord is a computerized version of the
ChronoSheet, an established paper based form for self-reporting (Bauer et al., 1991, 2004). The ChronoRecord
data collection software presents the patient with large,
colorful icons for mood, medication and sleep to facili-
tate data entry. ChronoRecord uses a 100-unit visual
analogue scale between the extremes of mania and de-
pression on which the patient marks mood proportion-
ately. During the patient’s training, personal anchor
points were set by the patient to describe the most de-pressed and most manic moods they ever experienced
during their most extreme episodes. By personalizing the
calibration of the anchor point for mania, the patient’s
most manic mood may be either dysphoric or euphoric.
A mood entry less than 40 was considered depression,
40–60 euthymia, and greater than 60 hypomania/mania.
Within depression, an entry of 20–39 represented mild
symptoms and an entry of 0–19 moderate to severesymptoms. An entry of 61–80 represented mild symp-
toms and 81–100 moderate to severe symptoms of
mania.
2.2. Statistical analysis
Demographic data were used to evaluate sample
bias. Distributions were compared between men andwomen using the Pearson 2-sided asymptotic v2-test.Mean values were compared between the groups using
the independent sample 2-sided t-test. Mean values
were also compared using general linear model (GLM)
fixed factor parameter estimates with and without the
patient specified as a random factor. No covariates
were used in the GLM analyses. The Kolmogorov–
Smirnov (KS) test was used to evaluate if large moodchanges (P10) were normally distributed. To evaluate
whether the menstrual cycle has an impact on mood,
data were analyzed for each woman, for each cycle
using a GLM with individual patient as a random
factor. K-Means cluster analysis using Euclidian dis-
tance was used to evaluate categorical mood groupings.
Mood changes across the menstrual cycle compared the
first seven days and the last seven days of same cycle.The start of the menstrual cycle was defined as day one
of bleeding in all cases. All analyses were evaluated at a
0.05 probability of incorrectly rejecting the hypothesis
N. Rasgon et al. / Journal of Psychiatric Research 39 (2005) 77–83 79
that there is no difference between men and women
(type I error). SPSS Version 11.5 was used to perform
the statistical computations.
3. Results
Overall, 8662 days of data were received from the 80
patients, and grouped by sex into 3483 days of data
from 35 men (40.2% of all data) and 5179 days of data
from 45 women (59.8% of all data). The patient demo-
graphic characteristics are listed in Table 1 and there
were no significant differences in the patient samplebetween men and women. Of the 80 patients, 79 were
receiving medication for bipolar disorder; one patient
received no medication. There was no significant sex
difference in the distribution of any of 17 comorbid
DSM-IV diagnoses found in the 80 patients (p ¼ 0:349).Four of the men (3 BP I; 1 BP II) had an ultra-rapid
cycling form of bipolar disorder. One of these four men
had a cycle periodicity of 24 h that was inconsistent withall other patients in the dataset. This patient was ex-
cluded because his data did not contribute to the anal-
ysis of mood patterns between men and women. There
were no ultra-rapid cyclers who were female although
there were two females with rapid cycling (both BP II).
All further analysis reported uses data from 79 patients.
A comparison of the 79 patients for clinical character-
istics upon entry to the study and compliance with theautomated data collection tool also showed no obvious
bias between the sexes (Table 2). Of the 79 patients, 26
had a change in psychotropic medications during the
study but the sex distribution of these patients by di-
Table 1
Demographic and medication characteristics of all men and women returnin
Women (N ¼ 45)
Agea 37.4� 10.2
BP I:BP IIb 31:14
Number of hospitalizationsa 0.8� 2.6
Receiving government disability N (%)b 13 (28.9%)
Number of medicationsa 4.09� 1.7
Lithium N (%)b 15 (33.3%)
Antipsychotics N (%)b 17 (37.8%)
Divalproexsodium N (%)b 17 (37.8%)
Gabapentin N (%)b 8 (17.8%)
Lamotrigine N (%)b 14 (31.1%)
Carbamazepine N (%)b 4 (8.9%)
Topiramate N (%)b 6 (13.3%)
Benzodiazepines N (%)b 22 (48.9%)
Triiodothyronine (T3) N (%)b 2 (2.5%)
LL-thyroxine N (%)b 10 (22.2%)a t-test with unequal variance assumed.b v2 Analysis.
agnosis was not significantly different (BP I p ¼ 0:059;BP II p ¼ 0:149).
3.1. Cluster analysis
The K-Means cluster analysis of the daily Chrono-
Record mood values using 3 and 5 clusters validated the
ChronoRecord mood category boundaries. The 3 clus-
ters were estimated with centers at 25 (1600 observa-
tions), 48 (5631 observations), and 65 (1220
observations). The 5 clusters were estimated with centers
at 15 (566 observations), 32 (1276 observations), 48
(4973 observations), 59 (1272 observations) and 76 (364observations). The ChronoRecord mood categories
(depressed, euthymic, manic) approximate the mid-
points between each of the clusters in the 3-cluster
analysis. The 5-cluster analysis generated approximately
the same 3 clusters but additionally had a cluster that
was more manic and a cluster more depressed, similar to
analysis of severe symptoms. The cluster analysis shows
a reasonable distribution of ChronoRecord mood rat-ings across all values.
3.2. Frequency in mood categories between sexes
A GLM was used to analyze the individual percent of
days in the mood categories using sex as a fixed factor.
The percent of time depressed was 17.0% for men and
28.3% for women with a coefficient ()10.9) significantlydifferent from zero (p ¼ 0:046). The percent of time
euthymic was 74.0% for men and 64.2% for women with
a coefficient (12.8) significantly different from zero
(p ¼ 0:029). The percent of time manic was 5.6% for
g data (N ¼ 80)
Men (N ¼ 35) P
40.3� 11.5 0.243
26:9 0.706
3.2� 4.6 0.107
10 (28.6%) 0.975
3.34� 1.8 0.072
8 (22.9%) 0.304
14 (40.0%) 0.840
11 (31.4%) 0.555
7 (20%) 0.801
10 (28.6%) 0.806
6 (17.1%) 0.268
2 (5.7%) 0.260
12 (34.3%) 0.190
2 (5.7%) 0.104
5 (14.3%) 0.367
Table 2
Comparison of men and women at start of study (N ¼ 79)
Women (N ¼ 45) Men (N ¼ 34) P
Entry rating on HAMDa 9.51� 7.6 7.38� 6.5 0.186
Entry rating on YMRSa 4.34� 5.9 2.76� 3.5 0.168
Entry mood category if BP I N (%)b 0.471
Depressed 8 (25.8%) 7 (28.0%)
Euthymic 21 (67.7%) 14 (56.0%)
Manic 2 (6.5%) 4 (16.0%)
Entry mood category if BP II N (%)b 0.520
Depressed 7 (50.0%) 3 (33.3%)
Euthymic 6 (42.9%) 4 (44.4%)
Manic 1 (7.1%) 2 (22.2%)
Days of returned dataa 115 99 0.343
Percent days missing mood dataa 4.5 8.2 0.107a t-test with unequal variance assumed.b v2 Analysis.
80 N. Rasgon et al. / Journal of Psychiatric Research 39 (2005) 77–83
men and 7.5% for women with a coefficient ()1.9) thatwas not significantly different from zero (p ¼ 0:379).Both sexes reported predominantly mild symptoms
while depressed (men 83.1%, women 82.9%) or manic
(men 86.7%, women 81.3%).
3.3. Frequency of mood changes between sexes
Change in mood was calculated across all days for a
difference of 1, 2, or 3 days and stratified into nine tiers
from the largest negative to largest positive daily
change. For both men and women, with a lag of 1, 2, or
3 days, the majority of mood changes were small. For a
lag of 1 day, 66.9% of all of mood changes for men were
between )5 and 5, and 86.4% were between )10 and 10.
For women, 66.1% of all changes were between )5 and5, and 83.5% between )10 and 10. These distributions of
mood change for a lag of 1, 2 or 3 days were significantly
different between men and women using the v2 statistic
(lag 1 day, p ¼ 0:005; lag 2 days, p < 0:001; lag 3 days
p < 0:001) (Table 3).
Table 3
Distribution of all mood changes in men (N ¼ 34) and women
(N ¼ 45) for a lag of 1 day (p ¼ 0:005)
Size of mood
change
Number of mood
changes (men) (%)
Number of mood
changes (women) (%)
<)20 67 (2.2%) 145 (2.9%)
P)20 & <)10 147 (4.7%) 266 (5.3%)
P)10 & <)5 242 (7.8%) 423 (8.5%)
P)5 & <0 514 (16.6%) 850 (17%)
¼ 0 1074 (34.7%) 1538 (30.8%)
>0 & 6 5 566 (18.3%) 909 (18.2%)
>5 & 6 10 277 (8.9%) 444 (8.9%)
>10 & 6 20 150 (4.8%) 285 (5.7%)
>20 58 (1.9%) 127 (2.5%)
For each patient, the percent of mood switches with
an absolute value P 10 with a lag of 1, 2 and 3 days
were normally distributed using the KS test (p ¼ 0:487,p ¼ 562, p ¼ 0:454, respectively). A GLM was estimated
using sex as a fixed factor for the proportion of large
mood switches P 10 for a lag of 1–3 days. All estimates
for the parameters were significantly different from zero
by t-test (lag 1: men 16.9%, women 23.4%, p ¼ 0:049; lag2: men 20.1%, women 28.9%, p ¼ 0:023; lag 3: men
22.1%, women 30.2%, p ¼ 0:035).
3.4. Mood changes across the menstrual cycle
Of the 45 women, seven were menopausal and seven
did not report a complete cycle; the remaining 31 women
reported 101 menstrual cycles. The mean length of themenstrual cycle was increased in 12 of 31 women (39%):
nine women had long cycles (29–35 days) and three
women had oligomenorrhea (>35 days). A GLM was
estimated to compare the mean mood in the first seven
days of the menstrual cycle with the mean mood in the
last seven days of the same cycle for each cycle of each
woman. The patient was specified as a random factor.
The majority of the women (17 of 31; 55%) had a sig-nificant mood change during at least one menstrual cy-
cle. Of these 16 women, 8 (50%) reported significant
mood changes in more than one cycle. However, the
significant changes in mean mood did not have a dis-
cernable pattern or consistent direction (Table 4).
Nine of the 31 premenopausal women received OC.
By t-test, the mean mood during the first seven days of
the menstrual cycle of women receiving OC was49.1� 13.2 as compared to 40.9� 13.8 for women not
receiving OC (p < 0:001), and during the last seven days
was 46.9� 13.8 for women receiving OC and 42.2� 13.4
for those not receiving OC (p < 0:001). For these 31
Table 4
Details on the 31 menstrual cycles from 17 women in which a significant mood change occurred
Subject # Age BP type Taking OC Mean cycle length (days) Mean mood days 1–7 Mean mood last 7 days pa
7 33 I N 32.5� 3.8 34.5� 9.5 45� 2.3 0.020
9b 40 I N 28.3� 3.9 23.5� 4.9 33.5� 4.6 0.033
31.0� 3.9 20.1� 2.6 0.020
20.7� 4.3 34.5� 7.2 0.009
13 37 I N 26.2� 1.5 36.14� 12.6 45.6� 5.5 0.035
16b 43 I Y 21.33� 7.5 47.1� 6.9 34.1� 8.8 0.004
44.3� 13.7 35.1� 8.3 0.041
18b 43 I N 39� 19 20.5� 6.2 48.5� 23.6 <0.001
66.0� 18.0 43.6� 11.8 0.001
49.6� 9.5 33.5� 5.5 <0.001
19 34 II Y 27.3� 2.1 40.3� 17.3 53.3� 8.7 0.004
22 45 I N 30.75� 5.3 45.0� 4.9 31.5� 7.1 0.003
23 29 II N 31.5� 0.7 7.0� 6.0 21.6� 20.2 <0.001
26b 39 I N 38.5� 17.6 37.4� 8.7 56.1� 10.7 0.033
61.1� 1.2 52.6� 11.4 0.006
32b 19 I Y 29.6� 6.0 64.3� 4.5 53.6� 18.7 <0.001
56.0� 15.3 63.4� 13.3 0.001
35b 34 II N 27.6� 0.5 18.9� 9.3 40.6� 16.6 <0.001
34.0� 10.6 18.0� 2.0 0.009
35.3� 6.0 59.0� 12.7 <0.001
40b 38 II N 27� 1.4 40.6� 0.5 28.8� 3.5 0.009
30.1� 0.6 60.1� 10.1 <0.001
41 31 I Y 19� 0 35.4� 10.6 48.3� 4.4 0.006
44 44 I N 28.6� 1.2 27.2� 5.5 49.2� 3.2 <0.001
56 42 I N 26.0� 0.7 14.7� 9.1 34.4� 16.4 <0.001
60 35 I N 40.4� 15.9 22. 1� 5.9 37.8� 10.9 <0.001
O67b 38 I Y 29.0� 1.4 48.9� 15.4 31.8� 28.2 <0.001
52.5� 12.2 31.8� 14.3 <0.001a t-test of estimated parameter.b Subjects with significant mood change across more than one cycle.
N. Rasgon et al. / Journal of Psychiatric Research 39 (2005) 77–83 81
women, the distribution of time depressed was 16.7% for
women receiving OC and 27% for women not receiving
OC, which is statistically different using the v2 statistic
(p < 0:001).
4. Discussion
The main results of this study are: (1) women re-
ported depression more frequently than men; (2) women
reported large mood fluctuations more frequently than
men; (3) mood fluctuations in females may be due in
part to the effects of the menstrual cycle. As this was a
naturalistic study of consecutively recruited patients at
mood clinics, all mood states and subtypes of the bi-
polar disorder were included. In this sample of outpa-tients compliant with treatment for bipolar disorder,
both sexes reported being euthymic for the majority of
observation, about 74% of the time for men and about
64% of the time for women. However, despite treatment,
women reported depression more frequently than men
(28.3% vs. 17.0%), consistent with prior findings that
women have more depressive episodes (Perugi et al.,
1990). Patient reports of mild inter-episode symptomsare also consistent with findings from other longitudinal
studies of bipolar disorder (Judd et al., 2002; Benazzi,
2001; Keitner et al., 1996). Large mood changes were
infrequent. For both men and women, about 85% of all
mood changes calculated with a 1, 2, or 3-day lag were
between )10 and 10 on a 100-point scale. However, the
distribution of mood changes was significantly different
between the sexes with women having large mood
changes in both directions more often than men.As in our previous report (Rasgon et al., 2003), the
majority of pre-menopausal females were found to have
significant mood changes across at least one menstrual
cycle. As with our and others prior findings, there was
no pattern or consistent direction to these mood changes
(Leibenluft et al., 1999; Rasgon et al., 2003). Such lack
of pattern may be due to the phenotypic heterogeneity
of bipolar disorder, small sample size, and the poten-tially obscuring effects of medications. A longer con-
trolled study with a larger sample may be required to
detect a pattern. Similarly, as in our previous report, the
women receiving OC reported depression less frequently
than those not on OC. This is consistent with some re-
ports that OC have mood-stabilizing effects in women
with treatment-resistant bipolar disorder (Rasgon et al.,
2003; Chouinard et al., 1987; Hatotani et al., 1983; Priceand Giannini, 1985). Menstrual cycle length was long in
82 N. Rasgon et al. / Journal of Psychiatric Research 39 (2005) 77–83
39% of the women, with 10% displaying oligomenor-
rhea, another finding consistent with previous reports of
menstrual abnormalities in women with bipolar disorder
receiving mood stabilizers (Rasgon et al., 2000, 2003).
Taken together, the high frequency of menstrual ab-normalities in women with bipolar disorder further
supports both the concepts of a trait-related liability for
reproductive dysfunction in women with bipolar disor-
der and of reproductive dysfunction associated with the
medications used to treat bipolar disorder.
This study uses self-reported mood ratings. While the
use of self-reported mood ratings to evaluate bipolar
disorder is widely accepted for depressive mood states(Denicoff et al., 2000), recent studies have shown that
the central feature of mania is increased activation ra-
ther than elevated mood (Cassidy et al., 1998, Akiskal
et al., 2001). Also, scores on both clinician and self-
rating instruments are highly correlated with activation-
related features and not mood (Bauer et al., 1991).
Within this framework, the patient’s anchor point for
mania in ChronoRecord and subsequent self-ratings ofmania reflect activation levels for either euphoric or
dysphoric mood (Bauer et al., 2004).
The limitations of this naturalistic study include the
variation in the patient’s symptoms, severity, phase of
the disorder, medications received, and the lack of
comparison with healthy controls. Also, the analyses in
this study were constrained by the data elements col-
lected with ChronoRecord. A longer data collectionperiod from each patient would be preferable and would
permit episode-based analysis. Sex differences in the re-
sponse to medications taken for bipolar disorder could
be the cause of some the observed mood changes. The
limitations in relation to menstrual cycle analysis also
include the lack of hormonal analysis, and the relatively
few number of cycles per woman included in the anal-
ysis. Further study is required to determine if the sta-tistically significant differences found are clinically
significant.
This study took advantage of the dramatic increase in
computer usage by the general public in the United
States, as compliance with the automated self-reporting
tool was excellent. As of September 2001, two-thirds of
137,000 individuals surveyed used a computer at work
or school while 56% of households had at least onecomputer at home (US Department of Commerce,
2002).
In summary, using ChronoRecord monitoring of
mood among patients treated for bipolar disorder, we
found that women reported depression and large fluc-
tuations in mood more frequently than men. Most
mood changes reported by both men and women were
small. In addition, mood in bipolar women was influ-enced by the menstrual cycle. Since the observed mood
fluctuations occurred despite treatment, these findings
are important both clinically and for further investiga-
tion of the neurobiology of sex-specific differences in
bipolar disorder. Some of the findings noted may be a
direct result of the medications received. Small sample
size, clinical heterogeneity, and short duration of ob-
servation prevent us from making clear recommenda-tions, yet present observations support variable
approaches to management of bipolar disorder between
sexes. Larger, longitudinal controlled studies are neces-
sary to discern the patterns of such differences.
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