Journal of Psychosomatic Research 76 (2014) 61–67

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Journal of Psychosomatic Research

Familiality and clinical outcomes of sleep disturbances in majordepressive and bipolar disorders

Yin-Chieh Lai a, Ming-Chyi Huang b,c, Hsi-Chung Chen d, Ming-Kun Lu e, Yi-Hang Chiu f, Winston W. Shen f,Ru-Band Lu g, Po-Hsiu Kuo a,⁎a Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwanb Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwanc Department of Psychiatry, School of Medicine, Taipei Medical University, Taipei, Taiwand Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwane Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwanf Department of Psychiatry, Taipei Medical University-Wan Fang Medical Center, Taipei, Taiwang Department of Psychiatry, National Cheng Kung University Hospital, Tainan, Taiwan

⁎ Corresponding author at: Department of Public Healtand Preventive Medicine, College of Public Health, Nati521, No. 17, Xuzhou Road, Taipei 100, Taiwan. Tel.: +82351 1955.

E-mail address: phkuo@ntu.edu.tw (P.-H. Kuo).

0022-3999/$ – see front matter © 2013 Elsevier Inc. All rihttp://dx.doi.org/10.1016/j.jpsychores.2013.10.020

a b s t r a c t

a r t i c l e i n f o

Article history:

Received 4 May 2013Received in revised form 28 October 2013Accepted 31 October 2013

Keywords:Bipolar disorderFamilial aggregationMajor depressive disorderQuality of lifeSleep disturbance

Objective: Sleep disturbances are frequently observed inmajor depressive (MDD) and bipolar disorder (BD). Thisstudy reported sleep profiles of patients and their relatives versus controls, and examined the familiality of sleepfeatures in mood disorder families. We also evaluated the influences of sleep disturbance on patients' quality oflife (QOL), functional impairment, and suicidality.Methods:We recruited 363 BD and 157MDD patients, 521 first-degree relatives, and 235 healthy controls, whichcompleted a diagnostic interview, Pittsburgh Sleep Quality Index (PSQI), and QOL questionnaire. The magnitudeof heritability of sleep features was calculated and familiality was evaluated by mixed regression models andintraclass correlation coefficient (ICC). The associations between sleep problems and clinical outcomes were ex-amined using multiple regression models.Results:More than three-quarters of mildly-ill patients were classified as “poor sleepers”. MDD patients had sig-

nificantlyworse sleep quality as compared to BD patients. Moderate but significant familial aggregation wasobserved in subjective sleep quality, sleep latency, disturbance, daytime dysfunction, and global score(ICC = 0.10–0.21, P b .05). Significant heritability was found in sleep quality (0.45, P b .001) and sleep dis-turbance (0.23, P b .001). Patients with good sleep quality had better QOL and less functional impairment(P b .05) than poor sleepers. Poor sleep quality and nightmares further increased the risk for suicidal idea-tion (ORadj = 2.8) and suicide attempts (ORadj = 1.9–2.8).Conclusion: Subjectively measured sleep features demonstrated significant familiality. Poor sleep qualityfurther impaired patients' daily function and QOL, in addition to increasing the risk of suicidality, andthus requires special attention in related clinical settings.

© 2013 Elsevier Inc. All rights reserved.

Introduction

Previous studies have shown a link between sleep disturbancesand emotional dysregulation [1,2]. Sleep complaints are commonlyobserved prodrome symptoms of affective disorders [3]. The currentDSM-IV diagnostic system for mood disorders lists sleep complaintsas one of the major symptoms in both manic and depressive episodes.Patients usually have a reduced need for sleep during manic episodes,whereas patients in the midst of a depressive episode exhibit either

h and Institute of Epidemiologyonal Taiwan University, Room86 2 3366 8015; fax: +886 2

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insomnia or hypersomnia. Even in a remission period, a high percentageof patients with mood disorders continue to encounter sleep prob-lems [4]. For instance, up to 70% of euthymic bipolar patients showedclinically significant sleep disturbances [5]. In addition, insomnia duringa remission period is associated with a substantially increased risk forthe recurrence of a depressive episode [6]. Moreover, in the generalpopulation, non-depressed individuals who suffer from insomnia alsohave a twofold risk of developing depression during follow-up [7].Overall, sleep disturbances are not only present before and at the timeof making a diagnosis, but they are also among the most common re-sidual symptoms that occur during remission periods [8]. However,relatively few studies exist that examine detailed features of sleepproblems in patients with mood disorders [9]. To what extent differ-ent sleep features are present in BD versus MDD patient groups isless clear at this time.

62 Y.-C. Lai et al. / Journal of Psychosomatic Research 76 (2014) 61–67

Family, twin, and adoption studies have found evidence of strongfamilial aggregation in mood disorders. In addition to the diagnosisof mood disorders, several clinical features also run in families,such as substance abuse, personality, history of suicide attempts,and the level of social functioning [10,11]. Although sleep disordershave been reported to exhibit familial aggregation [12] and the riskof familiality was further increased in patients with an earlier ageof onset (b40 years) of insomnia [13], very few studies have exam-ined the familial aggregation of subjectively measured sleep relatedphenotypes [14]. Substantial familiality of sleep disturbances inmood disorder families would indicate its potential to serve as anendophenotype for further genetic analysis [15]. In general, subjectiveassessment of sleep quality is more feasible in studies with a largersample size and is often applied in clinical and epidemiological studieswith good validity. One commonly used sleep questionnaire is thePittsburgh Sleep Quality Index (PSQI), which assesses multiple com-ponents of sleep quality, including both numbers and severity ofsleep problems in different dimensions, such as sleep duration andefficiency [16]. The current study aimed to examine the aggregationand heritability of sleep features in families of mood disorders usinga standard subjective measurement, the PSQI. We also evaluatedwhether or not specific characteristics of sleep disturbances have ahigher magnitude of familiality than others. In particular, the liabilityof sleep problems in different diagnostic groups of mood disordersmight vary.

Finally, patients with mood disorders often exhibit difficulties withsocial settings, interpersonal relationships, and occupational function-ing [17]. The phenomena of persistent sleep disturbances are not onlyrelated to chronic illness courses with more recurrent manic and de-pressive episodes, but are also related to poor quality of life (QOL)and even suicidality [14,18]. Previous studies have reported that BDpatients with sleep problems showed more impaired QOL, particu-larly in the physical and psychological domains [19], as well as im-paired global function than those without sleep complaints [20].Gruber and colleagues [21] measured total sleep time among pa-tients and found that short (b6 h) and long (≧9 h) sleepers havemore severe mania and depressive symptoms, poorer life function-ing, and QOL as compared to normal sleepers. Moreover, frequent in-somnia and nightmares are related to increased severity of clinicalsymptoms [22], worse treatment response [23], and increased riskof suicidal ideation and suicide attempts in MDD patients [24].Using a standardized measure such as PSQI, we evaluated the rela-tionships between different sleep quality and quantity variablesand QOL, functional impairment, and suicidal behaviors in patientswith mood disorders.

The current study examined whether patients with BD and MDDexhibit different sleep problems and to what extent their relativeshave sleep complaints, and compared with healthy controls. Wealso investigated the magnitude of familial aggregation for differentsleep components in mood disorder families among the two diagnosticgroups. Finally, among patients with mood disorders, we hypothesizethat those who do not sleep well (poor sleepers) have worse QOL,more functional impairment, and increased risk of suicidality thangood sleepers.

Methods

Research design and subject recruitment

We conducted a family study of mood disorders in Taiwan. Patientsaged between 18 and 70 years who were diagnosed with MDD, BD-I(bipolar disorder I) or BD-II (bipolar disorder II) based on the DSM-IVcriteriawere eligible for enrollment. The clinical global impression— se-verity scale (CGI-S) was assessed by psychiatrists in six central andregional hospitals to measure symptom severity. Patients whowere at most mildly ill (i.e. CGI-S ≦3) were consecutively referred

by psychiatrists from 2008 to 2011 as index probands. The meanCGI-S scores in BD patients were not significantly different fromthose in MDD patients (P = .32). Patients who were diagnosedwith schizophrenia, schizoaffective, or substance-induced mood dis-orders were excluded. Patients whose diagnoses were changed dur-ing the data collection period were also excluded.

We intended to recruit all available family members with whom theprobands provided permission to contact. The majority of participatingfamily members were biological first-degree relatives (i.e. father,mother, siblings and adult offspring, total N = 618, 95.32%). Onlyfirst-degree relatives were considered in the following analysis.Healthy controls were recruited from the community by sendingleaflets or word-of-mouth, and these subjects were then screenedfor mood disturbances and other major psychiatric disorders usingthe Composite International Diagnostic Interview (CIDI). Due to therelatively high prevalence of mood disorders in the general population,we recruited controls aged between 35 (approximately themean onsetage of mood disorders) and 70 years to reduce the likelihood of havingcontrol subjects develop mood disorders after recruitment. The studywas approved by the institutional reviewboard of all concerned institu-tions and hospitals. All participants provided written informed consentafter the study procedures had been fully explained to them. In total,we recruited 1275 participants, including 657 probands (318 BD-I,150 BD-II, and 189MDD), and 618 first-degree relatives (141 fathers,206 mothers, 197 siblings, and 74 adult offspring). In addition, 235healthy controls were recruited in the present study.

Diagnostic and phenotypic assessment

Composite International Diagnostic Interview, CIDIAll participants were interviewed with the Chinese version of the

WHOMental Health 2000 version of the CIDI [25]. The CIDI is a com-prehensive, fully-structured interview for the assessment of mentaldisorders. The CIDI has been used extensively in many large-scaleepidemiological surveys and cross-cultural studies demonstratinggood reliability and validity [26]. We used the CIDI interview to con-form to clinical diagnosis and to derive diagnostic information forthe relatives of index probands. If there was any inconsistency be-tween the CIDI and clinical diagnosis in the index probands, furtherconsultations with psychiatrists were made and patients were re-interviewed to gather additional information and to reduce thechance of misdiagnosis. Using the CIDI interview, we retrospectivelycollected demographic variables (e.g. socioeconomic status, lifetimesymptoms and clinical features of mood disorders, and informationon suicidal ideation and attempts).

Sheehan Disability Scale, SDSFunctional impairmentwas assessed by the SheehanDisability Scale,

SDS. The SDS asks respondents to what extent on a 0 to 10 scale theirfunctions at home, at work, in their social life, and in relationshipswere impaired by a depressive or manic episode in the last year. Themost severe score across all four domains was then coded as the overallrole impairment, which was adopted in Liao et al. [27]. Higher scoresmean greater disability (0: no interference; 1–3: minor interference;4–6: moderate interference; 7–9: severe interference; 10: very seriousinterference).

Pittsburgh Sleep Quality Index, PSQIThe PSQI is a self-reported questionnaire to evaluate quantitative

and qualitative sleep quality during theprevious 1 month of data collec-tion [16]. It has beenwidely used in clinical and epidemiological studies.The PSQI consists of seven components: subjective sleep quality, sleeplatency, sleep duration, habitual sleep efficiency, sleep disturbances,use of sleeping medication, and daytime dysfunction. A global PSQIscore is obtained by summing up scores from the seven components(ranged 0–21). Higher scores represent poorer sleep quality. A

63Y.-C. Lai et al. / Journal of Psychosomatic Research 76 (2014) 61–67

global PSQI score N5 was suggested to distinguish good from poorsleepers, which yielded a sensitivity of 89.6% and specificity of86.5% (kappa = 0.75) [16]. The Chinese version of the PSQI hasbeen reported to have good internal consistency (Cronbach'salpha = 0.83), 2–3 weeks test–retest reliability (ICCR = 0.85) andgood construct validity in a Taiwanese sample [28]. In the samestudy with 87 primary insomnia patients and 157 healthy controls,the sensitivity and specificity of the Chinese version of the PSQIwere 98% and 55%, respectively, using the same cutoff value of 5 toidentify patients with poor sleep quality. We used a cutoff value of 5to divide participants into good and poor sleepers in the currentstudy. Among recruited participants, 520 probands (363 BD, 157MDD) and 521 relatives (66 affected relatives, 455 unaffected relatives)completed the PSQI and were included in the subsequent analysis.

The World Health Organization Quality of Life Scale, brief version,WHOQOL-BREF

The WHOQOL-BREF is a 26-item self-report questionnaire to assessQOL,which consists of four domains, physical health (assesses pain, dis-comfort, sleep, activities, dependence on medical substances, and workcapacity), psychological health (assesses feelings, thinking, self-esteem,and belief), social relationships (assesses personal relationships, socialsupport, and sexual activity) and environment (assesses security, fi-nancial resources, social care, and transport). Higher scores in theWHOQOL-BREF indicate higher QOL. The WHOQOL-BREF question-naire has been applied in various clinical studies and general popula-tion surveys in the Chinese population and exhibited good internalconsistency and test–retest reliability [29].

Statistical analyses

To evaluate sleep disturbances in the affected and unaffected sub-jects, we analyzed BD vs. controls and MDD vs. controls separatelyusing linear regression models. We examined whether sleep qualitydiffered between BD and MDD patients. Among unaffected individ-uals, we evaluated sleep disturbances in unaffected relatives of BDor MDD patients vs. controls. Cohen's d was used to calculate theeffect-size. The effect size was defined as small (d = 0.2), medium(d = 0.5), and large (d = 0.8). All models were adjusted for ageand sex effects on sleep quality using linear regression models forcontinuous variables, and ANCOVA tests for categorical variables amongour subgroup comparisons. Cohen's d is reported in the tables. In thesubgroups of BD patients (BD-I and BD-II), we found no significant differ-ences in the global sleep quality and seven sleep components. Therefore,the two subgroups were combined into one overall BD group.

Using a cut-off of 5 for the global PSQI score, patients and controlswere divided into poor- and good-sleepers. Group differences in QOLbetween the poor- and good-sleepers were compared using ANCOVAand post-hoc Scheffe's tests. Pearson's correlations were used to ex-amine the correlations between sleep variables and QOL. Accordingto the Sheehan Disability Scale, the impairment of patients was di-vided into “none to mild” and “moderate, severe to very severe”.We used multiple linear regression to evaluate the effects of sleepquality on patients' functional impairments in the last year, andused multiple logistic regression for suicidality while adjusting forage at interview, sex, and employment.

Familiality of sleep components was assessed using a mixed-effectsregression model, which assumed that sleep data within clusters(i.e., families) were dependent and that both obtained global andcomponent scores were normally distributed. For each of the eightvariables (global sleep quality, and seven sleep components), weperformed mixed regression models, with age and sex treated asfixed effects and family membership treated as a random effect.The degree of dependency for sleep quality attributable to familiesis characterized by the within families variance. Two mixed modelswere compared: one with only fixed effects and the other with

family membership as an additional random effect. The likelihoodratio test with 1 df was used to examine familiality (log-likelihoodratio N1 favoring the model with family as a random effect). Thestrength of familiality for sleep variables was measured by calculat-ing the intraclass correlation coefficient (ICC), which ranges be-tween 0 and 1. All analyses were conducted using StatisticalAnalysis System statistical software version 9.1. The significancelevel was set at 0.05. In addition, the heritability of sleep featuresin mood disorder families was calculated using the SequentialOligogenic Linkage Analysis Routines (SOLAR) program, with ageand sex adjusted in all models [30].

Results

Demographic features and sleep characteristics of probands and controls areshown in Table 1. The mean age of BD patients (35.5 ± 12.4 years) was youngerthan the mean age of MDD patients (45.6 ± 12.5 years). Sixty percent of MDD pa-tients required more than a half-hour to fall asleep, followed by BD patients (~50%)and controls (~20%). Similarly, higher percentages of mood disorder patients hadlonger sleep duration (N7 h) than controls. Consequently, controls (92.3%) exhibitedhigher sleep efficiency (≧75%) than the BD (82.4%) and MDD (68.8%) patient groups.

Results of the PSQI are also shown in Table 1. The mean global PSQI score among BDand MDD patients was significantly higher than that in the controls. The same applies toall the sleep components of the PSQI, except for sleep duration, which was comparablebetween BD patients and controls (P = .22). Compared with BD patients, MDD patientsexhibited significantly poorer sleep quality, both in global score and each sleep compo-nent, with the exception of daytime dysfunction (P = .799). Among unaffected subjects(including unaffected relatives of MDD or BD patients and controls), the three subgroupsshowed similar scores in each sleep component and global sleep quality, with the excep-tions of duration (P = .017) and use of medicine (P = .008).

Table 2 displays the level of familial aggregation of sleep quality in BD and MDD fam-ilies. Subjective sleep quality, sleep latency, sleep disturbance, daytime dysfunction, andglobal score exhibited significant familial aggregation with mild effect size (ICC rangedfrom 0.10 to 0.21) in BD and MDD families. These results suggest that subjective sleepproblems may be an indicator of being at risk for mood disturbances among relatives ofmood disorder patients. The estimated heritability of two sleep variables was significant,including sleep quality (0.45 ± 0.09, P b .001) and sleep disturbance (0.23 ± 0.09,P b .001). The heritability of subjective sleep quality and sleep disturbance was in accor-dance with the significant familial aggregation for sleep problems in mood disorder fam-ilies. Furthermore, among all the relatives in mood disorder families (66 of 618 met thediagnostic criteria for mood disorders), poor sleep quality significantly increased the riskfor lifetime mood disorders (OR = 3.4, P b .001).

There was a positive correlation between global sleep quality and QOL in terms ofphysical health (Pearson's correlation coefficient, r = 0.42, P b .001), psychologicalhealth (r = 0.35, P b .001), social relationships (r = 0.21, P b .001), and environ-ment (r = 0.30, P b .001) in mood disorder patients. Similar moderate correlationwas observed when we classified the subjects into BD and MDD diagnosis groups.Among the four domains of QOL, physical health appeared to exhibit the highest cor-relation with sleep components, especially for subjective sleep quality (r = 0.39,P b .001) and daytime dysfunction (r = 0.44, P b .001). We found that 76.1% of pa-tients with mood disorders were “poor sleepers” (BD: 75.1%; MDD: 84.5%) with aglobal PSQI score N5, compared with only 29.5% in healthy controls. According toTable 3, mood disorder patients with good sleep quality reported significantly bettersatisfaction in all four domains of life quality than patients with poor sleep quality(P b .0001). On the contrary, controls who had poor or good sleep quality exhibitednon-significant differences in three domains of QOL, with the exception of life qualityin the physical domain (P = .007).

Results of functional impairment due to mood episodes in the last year are displayedin Table 4. Poor sleepers tended to experience more functional impairment than goodsleepers. The percentage of moderate to very severe impairment according to SDS washigher in the poor sleeper group across all four domains of functional impairment(67.5–78.8% due to depressive episode and 59.7–69.4% due to manic episode), comparedwith the good sleeper group (41.7–62.5% due to depressive episode and 40.0–53.3% due tomanic episode). For the overall role impairment score, poor sleepers reported having sig-nificantly more severe impairment than good sleepers (P = .007 due to a depressive ep-isode and P = .043 due to a manic episode). Additionally, poor sleepers exhibited greaterdisability at home, at work, and impaired social life (P b .05) under either depressive ormanic episodes. Table 5 shows the association between sleep disturbances and suicidality.Poor sleep quality showed a significantly increased risk for suicidal ideation(ORadj = 2.84) and suicide attempts (ORadj = 2.81). Frequent nightmareswere also asso-ciated with a higher risk of suicidal ideation (ORadj = 2.88) and attempts (ORadj = 1.89)after adjustment for age at interview and sex.

Discussion

Despite the issue of sleep disturbances in patients with mood disor-ders being well-known, few studies exist that examine sleep profiles

Table 1Characteristics of demographic variables and sleep features in the PSQI among subgroups of participants

Variables BD (N = 363) MDD (N = 157) Affected relatives(N = 66)

Unaffected relatives(N = 455)

Controls(N = 235)

BD vs. controls MDD vs. controls BD vs. MDD

Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Cohen's d Cohen's d Cohen's d

Age of interview, yeara, b, c, d 35.48 (12.36) 45.62 (12.53) 46.30 (13.88) 48.82 (15.11) 47.43 (8.53) 1.13 0.17 0.81Education, yeard 13.15 (5.66) 10.92 (4.38) 11.74 (4.78) 10.87 (4.67) 12.70 (3.72) 0.09 0.44 0.44PSQI dimensionsSubjective sleep qualitya, b, c 1.45 (0.86) 1.72 (0.82) 1.48 (0.79) 0.98 (0.82) 1.02 (0.70) 0.55 0.92 0.32Sleep latencya, b, c 1.63 (1.10) 1.89 (1.15) 1.56 (1.20) 0.97 (1.04) 0.94 (0.92) 0.68 0.91 0.23Sleep durationb, c 0.83 (1.10) 1.21 (1.20) 1.15 (1.06) 1.00 (0.97) 0.93 (0.83) −0.10 0.27 0.33Sleep efficiencya, b, c 0.68 (1.00) 1.02 (1.19) 0.62 (0.94) 0.37 (0.77) 0.33 (0.68) 0.41 0.71 0.31Sleep disturbancea, b, c 1.24 (0.62) 1.41 (0.69) 1.33 (0.54) 1.05 (0.54) 1.03 (0.44) 0.39 0.66 0.26Use of medicinea, b, c, d 1.85 (1.40) 2.25 (1.22) 1.41 (1.41) 0.27 (0.79) 0.11 (0.52) 1.64 2.28 0.30Daytime dysfunctiona, b 1.10 (0.94) 1.08 (0.92) 0.88 (0.90) 0.34 (0.57) 0.31 (0.49) 1.05 1.04 −0.02Global scorea, b, c 8.80 (4.61) 10.63 (4.74) 8.44 (4.54) 4.98 (3.40) 4.67 (2.89) 1.07 1.52 0.39

N (%) N (%) N (%) N (%) N (%)

Malea, c 173 (47.66) 49 (31.21) 23 (34.85) 189 (41.58) 88 (37.45)Sleep latencya, b, c

b15 min 64 (17.63) 25 (15.92) 16 (24.24) 188 (41.34) 84 (35.74)15–30 min 116 (31.96) 39 (24.84) 20 (30.30) 159 (34.90) 102 (43.40)31–60 min 72 (19.83) 22 (14.01) 7 (10.61) 44 (9.65) 27 (11.50)N60 min 111 (30.58) 71 (45.22) 23 (34.85) 64 (14.11) 22 (9.36)

Sleep durationa, b, c, d

b5 h 50 (13.77) 35 (22.29) 8 (12.12) 38 (8.42) 7 (2.99)5–6 h 44 (12.12) 26 (16.56) 18 (27.27) 99 (21.78) 52 (22.22)6–7 h 65 (17.91) 32 (20.38) 16 (24.24) 143 (31.44) 93 (39.74)N7 h 204 (56.20) 64 (40.77) 24 (36.36) 175 (38.37) 82 (35.04)

Sleep efficiencya, b, c

b65% 38 (10.47) 31 (19.75) 5 (7.58) 20 (4.46) 5 (2.13)65–74% 26 (7.16) 18 (11.46) 6 (9.09) 19 (4.70) 13 (5.53)75–84% 81 (22.31) 30 (19.11) 14 (21.21) 59 (14.60) 36 (15.32)≧85% 218 (60.06) 78 (49.68) 41 (62.12) 308 (76.24) 181 (77.02)

Sleep efficiency derived from the formula: hours of sleep / (get-up time − usual bedtime) × 100%.All subgroup comparisons were adjusted for age at interview, sex, and employment status.

a Significant difference (P b .05) between BD and controls.b Significant difference (P b .05) between MDD and controls.c Significant difference (P b .05) between BD and MDD.d Significant difference (P b .05) between Unaffected relatives and controls.

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among BD and MDD patients, with additional extension to their familymembers. The current study not only assessed sleep quality in BD orMDD patients and in controls, but also examined their relatives usinga well-validated sleep questionnaire with multiple components. Differ-ent sleep profiles were observed in subgroups of individuals. We foundthat therewasmoderate but significant familial aggregation and herita-bility for some of the subjectively measured sleep components in BDand MDD families. In addition, poor sleepers had significantly worseQOL,more severe functional impairment, and increased risk of suicidality.

Sleep problems are highly prevalent in patients with mood disor-ders. We observed that a high percentage of mood disorder patients(75% in BD and 85% in MDD) exhibited significantly poorer sleepquality. One early study using a British sample reported that 70% of

Table 2Familiality of sleep quality in mood disorder families

Variables BD

Likelihood ratio P-value

Subjective sleep quality 1.0073 b .0001Sleep latency 1.0020 .003Sleep duration 1.0008 NSSleep efficiency 1.0006 NSSleep disturbance 1.0042 .001Use of medicine 1.0000 NSDaytime dysfunction 1.0003 NSGlobal score 1.0012 .002

All models were adjusted for age at interview, sex, and disease diagnosis.ICC: intra-class correlation coefficient to measure the strength of familiality.

the euthymic BD patients had PSQI global score N5 [5]. Our findingsagree with previous clinical observations that BD patients may expe-rience considerable sleep disturbances, even in a euthymic state [31].Among MDD patients who show similar clinical severity as BD pa-tients in our samples, sleep disturbances were even more prominentthan in subjects with BD. When comparing the proportion of poorsleepers and scores of sleep components in our MDD patients withreports of other studies, our results were similar to those inJapanese and Caucasian populations [32,33].

We found that the MDD group exhibited significantly worse sleepquality than BD patients, except for daytime dysfunction (P = .799).On the other hand, previous studies reported no significant differencesin total sleep time, sleep efficiency [34], sleep disturbance, and EEG

MDD

ICC Likelihood ratio P-value ICC

0.18 1.0032 NS 0.110.10 1.0003 NS 0.050.07 1.0000 NS 0.000.06 1.0021 NS 0.130.12 1.0082 .005 0.210.01 1.0000 NS 0.000.04 1.0036 .040 0.170.12 1.0008 NS 0.12

Table 3Quality of life in poor vs. good sleepers among mood disorder patients and controls

WHOQOL-BREFdomains

Mood disorder patients Controls Group differences†

Poor sleep quality (N = 264)Mean (SD)

Good sleep quality (N = 85)Mean (SD)

Poor sleep quality (N = 61)Mean (SD)

Good sleep quality (N = 157)Mean (SD)

Physical 42.58 (13.04) 53.63 (14.54) 54.63 (12.42) 61.83 (9.46) MPbMG=CPbCGPsychology 39.75 (17.50) 53.71 (17.58) 54.71 (11.83) 60.38 (11.04) MPbMG=CP, CP=CG, MGbCGSocial relation 43.17 (19.29) 52.42 (19.38) 55.67 (12.88) 58.75 (10.17) MPbMG=CP, CP=, MGbCGEnvironment 45.79 (15.25) 55.54 (15.92) 53.96 (12.17) 58.33 (9.96) MPb=CP, CP=CG, MGbCG

Group comparisons were tested using ANOVA and all the P-values b .0001.MP: mood disorder patients with poor sleep quality.MG: mood disorder patients with good sleep quality.CP: controls with poor sleep quality.CG: controls with good sleep quality.

† Post-hoc Scheffe's test with significant differences (P b .05).

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variables [34,35] between the two diagnostic groups when patientswere under depressive episodes. These findings suggest that duringacute phase of the illness sleep problems might be similarly severe inthe BD and MDD groups, while in the remitted to mildly ill, MDD pa-tients haveworse sleep disturbances than BD patients. Of note, whetherepisode type exerts an effect on sleep problems aside from clinical se-verity is less clear at this time. Due to the lack of complete data for themost recent episode type in our BDpatients, wewere not able to furtherexamine the impact of episode type on sleep disturbances in our BDsamples.

Since more than three-quarters of patients were categorized as poorsleepers, sleep disturbances and mood symptoms may presumablyaggravate the negative impact of each other, in turn causing a viciouscycle to influence patients' daytime dysfunction, functional impair-ment, and poor subjective perceived QOL. We further restricted ouranalysis to patients who had reported experiencing severe to verysevere functional impairment in the last year due to mood episodes.Given the adverse influences ofmood symptoms,we found that patientswith poor sleep still exhibited significantly worse life quality than pa-tients with good sleep quality (P b .05). It is important to note that thephysical health domain of QOL includes a sleep question. However,after removing the sleep related item, a significant difference in life qual-ity still remains. Moreover, our findings on suicidality were in accor-dance with a recent study demonstrating that sleep problems andrecurrent nightmares heightened the risk of suicidal behaviors [36].These aforementioned findings have important clinical and interven-tional implications, and suggest that improving sleep quality amongpatients with mood disorders should be considered a high prioritythat may help to ameliorate the global functioning and life qualityof affected individuals, and to reduce the risk of suicidality. To improvethe overall prognostic outcomes, other than utilizing antidepressant

Table 4The role impairment in the past 12 months using the Sheehan Disability Scale amongmood disorder patients

Role impairment domains Poor sleep qualityMean (SD)

Good sleep qualityMean (SD)

β P-value

Depressive episode (N = 212) (N = 24)Home 5.74 (3.38) 3.87 (3.96) 2.12 .002Work 6.22 (3.39) 5.00 (3.95) 1.27 .064Relationships 5.46 (3.53) 4.58 (4.02) 0.75 .290Social 5.76 (3.75) 4.51 (4.20) 1.21 .111Overalla 7.97 (2.65) 6.51 (3.80) 1.47 .007

Manic episode (N = 144) (N = 30)Home 4.65 (3.77) 3.44 (3.92) 1.44 .048Work 5.35 (3.74) 3.88 (3.85) 1.73 .018Relationships 5.23 (3.64) 4.58 (3.65) 0.86 .209Social 5.00 (3.79) 3.75 (3.73) 1.52 .030Overalla 7.35 (3.19) 6.24 (3.75) 1.25 .043

All models were adjusted for age at interview, sex, and employment status.a Overall: the most severe score across all four domains of role impairment.

medications, additional sleep medicines [37] and/or behavioral treat-ment (e.g. cognitive-behavioral therapy for insomnia) [38] may beworthwhile to consider for patients with mood disorders who also suf-fer from sleep problems.

Among our unaffected relatives, 37.5%were poor sleepers, similar tothe percentage in healthy controls (29.5%), which was in the upperrange of those previously reported in the general population (20–30%)[39]. Regarding the scores of sleep components, they were similar be-tween unaffected relatives of mood disorder patients and healthy con-trols, but were significantly lower than both diagnostic groups. Similarto our findings, Mayers et al. [40] found that MDD patients had signifi-cantly longer sleep latency and poorer subjective sleep quality thantheir non-depressedfirst-degree relatives,with no significant differencebetween non-depressed relatives and controls. Importantly, we foundthat poor sleep quality significantly increased the risk for lifetimemood disorders (OR = 3.4, P b .001) among the relatives of mood dis-order patients. Interestingly, one previous study that assessed rapid eyemovement (REM) sleep latency reported that relatives of depressedprobands with short REM latency had a 2-fold increase of risk for life-time depression, compared with relatives of depressed probands withnormal REM latency [41]. Therefore, among relatives in mood disorderfamilies, both objective sleep variables and subjective sleep complaintsmay represent potential markers to identify an even higher risk groupfor developing mood episodes.

We are among the few studies to evaluate familial aggregation ofsubjective sleep quality in mood disorder families. We used a stan-dard questionnaire and also performed a mixed-effects regressionmodel to formally test the significance of familiality. Moderate butsignificant familial aggregation was found for several subjectively re-ported sleep components. In particular, subjective sleep quality(0.45) and sleep disturbances (0.23) exhibited significant heritabili-ty in our mood disorder families. Previous studies using objectivepolysomnographic measures revealed various findings, in whichREM latency but not electroencephalography variables showedfamiliality in depression families [41]. In a community-based sam-ple, Wing et al. (2012) reported substantial familial aggregationand the heritability of insomnia [14]. They also suggested that theheritability estimate of lifetime insomnia is higher than the currentone, and that heritability of clinically interviewed sleep disorder ishigher than that of subjective sleep disturbance. Therefore, sleep re-lated features seem to aggregate in families with varyingmagnitudesregardless of methods of assessment (subjective or objective) anddiagnosis (mood disorder patients or general population). Onething to note is that the non-response rate of family members inthe current study was high and the magnitude of familiality wasmild for some sleep variables. It is possible that the estimated familialaggregation of sleep disturbances in our samples represents the lowerbound of familiality levels for sleep problems inmood disorder families.Low ICC could be partly attributed to the subjective measures of sleepproblems (in the recent month). In addition, among first-degree

Table 5Effects of sleep disturbances on suicidal behaviors among mood disorder patients

Suicidal ideation Suicide attempts

Crude OR (95% CI) Adjusted OR (95% CI) Crude OR (95% CI) Adjusted OR (95% CI)

Global score 1.14 (1.09–1.19) 1.14 (1.09–1.19) 1.11 (1.06–1.17) 1.12 (1.06–1.17)Sleep qualityGood 1.00 1.00 1.00 1.00Poor 2.76 (1.79–4.27) 2.84 (1.82–4.44) 2.69 (1.41–5.13) 2.81 (1.44–5.46)

NightmaresNone 1.00 1.00 1.00 1.00b1/wk 1.38 (0.84–2.25) 1.30 (0.79–2.14) 0.81 (0.44–1.47) 0.72 (0.39–1.33)1–2/wk 2.03 (1.09–3.79) 2.15 (1.14–4.05) 0.84 (0.43–1.65) 0.87 (0.44–1.74)≧3/wk 3.15 (1.80–5.52) 2.88 (1.64–5.08) 2.03 (1.17–3.54) 1.89 (1.07–3.33)

All models were adjusted for age at interview, sex, and employment status.

66 Y.-C. Lai et al. / Journal of Psychosomatic Research 76 (2014) 61–67

relatives, young age of the adult offspring (24.8 ± 6.4 years) may beanother reason for the under-estimation of familial aggregation. Inthe future, further studies to replicate our findings of familialitywith larger sample sizes and more comprehensive sleep measuresare desired.

Limitations

The readers are cautioned not to over-interpret our study resultsdue to several methodological limitations. First, sleep characteristicswere assessed with self-report information only. Although previousstudies have reported a high correlation (r = 0.63) between subjectiveand objective total sleep times in depressed patients [42], including ob-jectivemeasures in future studies would also provide valuable informa-tion, especially for sleep parameters that are not easily obtained fromself-reported questionnaires. Second, the number of first-degree rela-tives of mood disorder families in this study was small, although thesample size of mood disorder patients in our study was comparablewith or larger than most of the previously reported clinical studies(among 363 BD patients, we recruited 403 relatives of BD; among 157MDDpatients, we recruited 118 relatives of MDD). Thus, the estimationof familial aggregation for sleep components may suffer from lowerpower. A large family study to replicate our findings is therefore sug-gested. Third, we did not control for proband severity and clinicalmood status at the time of the interviews. Nevertheless, all patientswere evaluated by psychiatrists first, and only those who were consid-ered to be in a stable status were referred to participate in this study.Previous studies showed that even in a euthymic state, BD patients ex-hibited more sleep disturbances than controls [5]. Similarly, our MDDand BD patients exhibited poor sleep quality, even if the latest episodewas prior to 1 year ago (approximately the status of long term remis-sion). Thus, it is expected that residual sleep disturbances are commonlyseen in mildly-ill mood disorder patients or even in those with remis-sion. Finally, the use and effectiveness of sleep medicine in patientswith mood disorders may have altered the response of self-reportedsleep complaints. Thus, the severity of sleep disturbances in BD andMDD patients may be underestimated.

Conflict of interest

None declared.

Acknowledgments

This research was supported by the National Science Council (NSC97-2314-B-002-184-MY2, NSC 99-2314-B-002-140-MY3) grants toDr. P-H Kuo (PI) and by the Taipei City Hospital (97002-62-045). Wethank all participating hospitals and psychiatrists who assisted regard-ing patient referrals, especially doctors YK Young, TL Yeh, JJ Lin, KYHsieh, SK Lin, andML Lu, and research assistants for their help in subject

recruitment and diagnostic interviews. We also thank all participantswho agreed to take part in this study.

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