Journal of Psychosomatic Res

Psychological and health-related quality of life factors associated with

insomnia in a population-based sampleB

Melanie LeBlanca,b, Simon Beaulieu-Bonneaua,b, Chantal Merettec,d,

Josee Savarda,e, Hans Iversb, Charles M. Morina,b,4

aEcole de psychologie, Universite Laval, Quebec, CanadabCentre d’etude des troubles du sommeil, Centre de recherche Universite Laval-Robert-Giffard, Quebec, Canada

cCentre de Recherche Universite Laval-Robert-Giffard, Quebec, CanadadDepartement de Psychiatrie, Universite Laval, Quebec, Canada

eCentre de recherche en cancerologie de l’Universite Laval, l’Hotel-Dieu de Quebec, Quebec, Canada

Received 13 June 2006

Abstract

Objective: This study examined the relationship of psycho-

logical and health-related quality of life variables to insomnia in

a population-based sample. Methods: Data were derived from a

longitudinal epidemiological study assessing the natural history

of insomnia. The present results are based on the first of four

postal evaluations conducted over a 2-year period. Participants

(n=953) completed questionnaires assessing sleep, psychological

and personality variables, and health-related factors. Participants

were categorized into three sleep status subgroups using an

algorithm based on Diagnostic and Statistical Manual of Mental

Disorders, Fourth Edition, Text Revision and International

Classification of Diseases, 10th Edition diagnostic criteria for

insomnia: (1) insomnia syndrome (n=147), (2) insomnia symp-

toms (n=308), and (3) good sleepers (n=493). Results: Compared

to individuals with insomnia symptoms and good sleepers,

individuals with insomnia syndrome presented lower quality of

0022-3999/07/$ – see front matter D 2007 Elsevier Inc. All rights reserved.

doi:10.1016/j.jpsychores.2007.03.004

B This research was supported by a Canadian Institute of Health

Research grant (#42504).

4 Corresponding author. Ecole de psychologie, Universite Laval,

Quebec, Canada G1K 7P4. Tel.: +1 418 656 2131x3275; fax: +1 418

656 5152.

E-mail address: cmorin@psy.ulaval.ca (C.M. Morin).

life and higher scores on measures of depression, anxiety,

neuroticism, extraversion, arousal predisposition, stress percep-

tion, and emotion-oriented coping. The same pattern was observed

for individuals with insomnia symptoms in comparison with good

sleepers. An ordinal logistic regression analysis showed that the

presence of a past episode of insomnia, higher depressive

symptoms, and lower scores on the 12-item Short Form Health

Survey vitality and role physical subscales were the most useful

variables to predict subgroups membership. Conclusion: The

findings indicate that insomnia is associated with increased

psychological symptomatology and perceived stress, higher

predisposition to arousal, and more impairment of health quality.

Longitudinal follow-ups are now being conducted to assess the

relative contribution of those variables in the development and

natural course of insomnia.

D 2007 Elsevier Inc. All rights reserved.

Keywords: Associated factors; Correlates; Epidemiology; Insomnia; Sleep

Introduction

Several epidemiological studies have been conducted to

document the prevalence and correlates of insomnia. An

estimated 30% of the adult population presents insomnia

symptoms, and about 5–10% are affected by an insomnia

syndrome [1–3]. Epidemiological studies have also

demonstrated that prevalence rates increase with age and

are higher among women, the unemployed, unmarried, and

those with lower socioeconomic status [1,4–9]. In addition

to sociodemographics, higher levels of depressive and

anxiety symptoms have consistently been associated with

insomnia [10]. Individuals with insomnia also report

more medical problems (e.g., arthritis, vascular disease),

earch 63 (2007) 157–166

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166158

an increased use of medications, drugs, and alcohol and

more frequent personal history of insomnia compared to

good sleepers [6,10–15].

Most epidemiological studies examining insomnia corre-

lates have restricted their investigation to depression,

anxiety, and specific health problems [1,4–15]. To our

knowledge, none has explored other variables (e.g., person-

ality, arousability) that may be involved in the etiology of

insomnia in the general population. For instance, in clinical

samples, the personality patterns of individuals with

insomnia have been characterized by the presence of

neurotic traits, inhibition of emotions, rumination, and

inability to discharge anger outwardly [16–20]. Individuals

with insomnia have also been described as having fewer

adaptive coping skills, relying more on emotion-oriented

coping strategies than problem-solving strategies, and

reporting lower feelings of mastery [21–23]. A higher

arousability (i.e., physiological, cognitive, and emotional)

during the day, at bedtime and at night has also been

associated with insomnia [22–25]. Studies have shown that

individuals with insomnia are more emotionally reactive,

more alert and vigilant, and experience more intrusive

thoughts than good sleepers [21,26–28]. Besides psycho-

logical factors, reduced quality of life has been associated

with insomnia in population-based samples [29,30]. Finally,

individuals with insomnia tend to report higher rates of

family history of insomnia than good sleepers [31–33]. With

the exception of one study on quality of life [29], results

from clinical samples have never been replicated to the

general population.

Studies of insomnia correlates have generally considered

single factors separately. Examining several factors simul-

taneously in the same sample can provide a more precise

and exhaustive description of the profile of individuals with

insomnia compared to that of good sleepers. Moreover,

most studies that documented correlates of insomnia have

relied on treatment-seeking individuals recruited from sleep

clinics. Such studies, while valuable, are restricted to

describing a single group of individuals with chronic

insomnia [16,17,31], or when a comparative group of good

sleepers is included, it is typically based on a convenience

sample not drawn from the same population [18,20–22]. In

addition, there has been no systematic investigation of the

characteristics (e.g., personality, depression, and anxiety

symptoms) of individuals with insomnia symptoms only

(i.e., who do not fulfill all the diagnostic criteria of

insomnia, although they represent approximately 30% of

the general population) [1,2]. Consequently, the relation-

ship between insomnia correlates and less severe or

transient insomnia remains unknown. For instance, it is

not known whether the higher levels of depressive and

anxiety symptoms usually observed in individuals with an

insomnia syndrome are also noticeable in individuals with

insomnia symptoms. The investigation of these factors in

individuals with less severe insomnia could guide the

development of effective early intervention programs to

prevent the development of chronic insomnia and subse-

quent mental health disorders.

The objective of the present study was to examine the

relationship between insomnia and psychological and health-

related quality of life factors in a population-based sample,

through a comparison of subgroups of individuals with

insomnia symptoms, insomnia syndrome, and good sleepers.

Methods

Study context and sample selection

Data from this study are derived from a larger

epidemiological study conducted in the province of

Quebec, Canada. The study began with a telephone

survey, carried out by a professional pool firm [1]. The

sample consisted of French-speaking residents of the

province of Quebec, 18 years and older. Sample selection

involved two procedures: (1) random digit dialing method,

which generates geographically stratified phone numbers,

and (2) the Kish method [34], to identify the individual to

be interviewed in each household. These methods ensure

that the sample is representative of the target population.

At the conclusion of the telephone interview, participants

were asked if they wanted to take part in the longitudinal

phase of the study, which involved completion of four

postal evaluations over a 24-month period. The first

evaluation was conducted 1 month after the telephone

interview. The remaining three postal evaluations were

conducted, respectively, 6, 12, and 24 months after the

first evaluation. Data from the first postal evaluation only

are reported in the present study.

Participants and procedure

Of the 5991 persons solicited, a total of 2001 (33.4%)

respondents completed the telephone interview, and 1467

(73.3%) of them accepted to take part in the longitudinal

study. Of this number, 105 were excluded because they

reported the presence of a sleep disorder other than insomnia,

the only exclusion criterion of the study. The first postal

evaluation was mailed to 1362 participants, who were asked

to return the completed questionnaire within a 2-week period.

Reminder telephone calls were made afterwards for those

who had not yet returned the measures. Response rate was

73.2%, with 997 participants having returned the completed

measures for which they received a $25 monetary compen-

sation. Of those, 44 additional participants were excluded

because they reported the presence of another sleep disorder

on the questionnaire, which was not reported at the telephone

interview. The final sample included 953 participants.

Sleep status groups

Participants were classified in three groups according to

an algorithm based on a combination of insomnia diagnostic

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166 159

criteria from the Diagnostic and Statistical Manual of

Mental Disorders, Fourth Edition, Text Revision (DSM-IV-

TR) [35], the International Classification of Diseases, 10th

Edition (ICD-10) [36], and on the utilization of sleep-

promoting products (prescribed and over-the-counter).

Responses from the Insomnia Severity Index (ISI) [37]

and the Pittsburgh Sleep Quality Index (PSQI) [38] and

from questions on sleep-promoting medication use were

used to evaluate the presence or absence of each criterion.

The three sleep status groups were defined as follows:

! Insomnia syndrome. Participants in this group met all

the diagnostic criteria for insomnia. They were

dissatisfied with their sleep [i.e., dissatisfied (3) or

very dissatisfied (4) on a 0–4 scale] and presented

symptoms of initial, maintenance, or late insomnia at

least three nights per week for a minimum duration

of 1 month. Psychological distress or daytime impair-

ment related to sleep difficulties was also reported

by those individuals [i.e., much (3) or very much

(4) on 0–4 scales]. Finally, if prescribed medication

was used as a sleep-promoting agent at least three

nights per week, participants were automatically

classified in the insomnia syndrome group whether

or not they presented symptoms of initial, mainte-

nance or late insomnia.

! Insomnia symptoms. Participants classified in this

group presented symptoms of initial, maintenance or

late insomnia at least three nights per week, without

fulfilling all the diagnostic criteria of an insomnia

syndrome (i.e., they could be satisfied with their

sleep, not report distress or daytime consequences, or

their sleep difficulties could last for b1 month). Also

included in this group were individuals dissatisfied

with their sleep quality but without symptoms of

initial, maintenance or late insomnia. Lastly, partic-

ipants using prescribed medication to promote sleep

less than three nights per week or over-the-counter

medication at least one night per week were automati-

cally classified in this group.

! Good sleepers. These participants were satisfied with

their sleep [i.e., very satisfied (0), satisfied (1), or

neutral (2) on a 0–4 scale], did not report symptoms

of initial, maintenance, or late insomnia and did not

use prescribed or over-the-counter medication as a

sleep-promoting agent.

Measures

Several measures were used for the purpose of the

present study. These included French–Canadian versions of

validated self-report measures, as well as questions devel-

oped specifically for this study, covering four general

domains: sleep, physical health and health-care service

utilization, coping and life events, and mood and person-

ality. Two sleep questionnaires (ISI and PSQI) [37,38] were

used to classify participants in the three sleep status groups

and to describe the sample. All other measures were used to

derive dependent variables.

Sleep measures

The ISI [37] is a seven-item questionnaire assessing the

nature, severity, and impact of sleep difficulties. Dimensions

are severity of sleep onset, sleep maintenance, and early

morning awakening problems; sleep satisfaction; interfer-

ence of sleep difficulties with daytime functioning; notice-

ability of sleep problems by others; and distress caused by

the sleep difficulties. A five-point Likert scale (b0Q=not atall, b4Q=extremely) is used to rate each of these items,

yielding a total score ranging from 0 to 28. Scores can be

classified into four severity categories: absence of insomnia

(0-7), subthreshold insomnia symptoms (8–14), moderate

insomnia (15–21), and severe insomnia (22–28). The ISI has

adequate psychometric properties and is sensitive to

measure treatment outcome [39]. The French–Canadian

version of the questionnaire has good internal consistency,

test–retest reliability and convergent validity (r=.65 when

comparing with sleep diary) [40].

The PSQI [36] is a 19-item questionnaire evaluating

sleep quality and disturbances over a 1-month time interval.

The first four items are open questions, whereas items 5 to

19 are rated on a four-point Likert scale. Individual items’

scores yield seven components: subjective sleep quality,

sleep latency, sleep duration, habitual sleep efficiency, sleep

disturbances, use of sleep-promoting medication, and day-

time dysfunction. A total score, ranging from 0 to 21, can be

obtained by adding the seven component scores. A score

higher than 5 suggests poor sleep quality. Psychometric

properties of the PSQI are adequate, especially regarding

the diagnostic sensitivity (89.6%) and specificity (86.5%)

for psychophysiological insomnia. The validated French–

Canadian version has adequate psychometric properties as

well [40].

Sleep-promoting products (i.e., prescribed and over-the-

counter medications) utilization was assessed with the

following questions: bDuring the past month, how many

nights per week have you taken prescribed medication to

help you sleep?Q and bDuring the past month, how many

nights per week have you taken over-the-counter medication

(e.g., Nytol, Sominex) to help you sleep?QPersonal and familial histories of insomnia were meas-

ured with the following questions: bIn the past, have you

ever experienced insomnia a few days per week for more

than 1 month? (yes/no),Q bIs a member of your immediate

family (parents, children, brothers, sisters) currently expe-

riencing sleep difficulties? (yes/no),Q and bHas a member of

your immediate family (parents, children, brothers, sisters)

ever experienced sleep difficulties? (yes/no).Q For those

answering in the affirmative, follow-up questions asked for

identifying the family member(s) and the type of sleep

problem (insomnia, excessive daytime sleepiness, sleep

apnea, restless legs or periodic limb movements, etc.). A

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166160

family history of insomnia was defined as a report of at least

1 parent or sibling with past or current insomnia.

Psychological measures

The Beck Depression Inventory II (BDI-II) [41] contains

21 items rating depressive symptoms experienced during the

past 2 weeks on a four-point Likert scale. A total score

(ranging from 0 to 63) is derived with a higher score

suggesting a higher depressive symptomatology. The cutoff

score for depressive symptoms of moderate severity is 20

[41]. The psychometric properties of the French version are

well documented and equivalent to those of the original

version [41].

The Trait part of the State-Trait Anxiety Inventory

(STAI-Trait) [42] was used to assess anxiety as a personality

trait. The STAI-Trait is comprised of 20 items rated on a

4-point Likert scale (b1Q=not at all, b4Q=a lot). Participants

have to score how they relate to the statements in general.

Total score range from 20 to 80, and 59 was used as the

cutoff score reflecting clinically significant anxiety. This

cutoff score represents two standard deviations (S.D.) above

our sample mean. Psychometric properties of the STAI are

excellent [40] as well as the validated French–Canadian

adaptation used in the present study [43].

Stress-related measures

The Perceived Stress Scale (PSS) [44] is a 14-item self-

report scale measuring the degree to which situations in one’s

life are appraised as stressful. Items represent feelings and

thoughts that have occurred in the past month in relation to

stressful situations or events. Individuals rate the frequency

of each item on a 5-point Likert scale (b0Q=never, b4Q=veryoften). The higher the total score, the more the person

appraises life as unpredictable and uncontrollable. The PSS

has adequate test–retest reliability (.85) and internal con-

sistency (.80) and is correlated with a range of self-report and

behavioral criteria [44]. A French–Canadian version of the

questionnaire was used in the present study.

The Coping Inventory for Stressful Situations (CISS)

[45] is a 48-item self-report measure of coping. It is divided

into three subscales, each containing 16 items: task-oriented

coping, emotion-oriented coping, and avoidance-oriented

coping. CISS items illustrate different ways of coping, and

respondents are asked to rate on a 5-point scale (b1Q=not atall, b5Q=very much) how each item is representative of their

own ways of coping with stress. The higher the score for a

scale, the more likely the respondent tends to rely on the

type of coping strategies measured by the scale. The CISS

has adequate properties with internal alpha reliabilities

ranging from .76 (men on the emotion subscale) to .91

(women on the task subscale) [45,46]. A French–Canadian

version of the questionnaire was used in the present study.

Arousal predisposition

The Arousal Predisposition Scale (APS) [24] is a 12-item

inventory that has been designed to measure arousability.

Respondents are asked to report the frequency to which they

experience the proposed emotion or behavior on a 5-point

Likert scale (b1Q=Never, b5Q=Always). The APS is a useful

measure of individual differences in predisposition towards

arousability and presents an adequate internal consistency

(0.84) [47]. A French–Canadian version of the measure

was used.

Personality

The NEO Five-Factor Inventory (NEO-FFI) [48] is a

60-item questionnaire measuring five personality domains:

neuroticism (N), extraversion (E), openness (O), agree-

ableness (A), and conscientiousness (C). Each factor is

evaluated by 12 items rated on a 5-point Likert scale

(strongly disagree to strongly agree). This five-factor model

is considered an excellent representation of personality [49].

The psychometric properties of the NEO-FFI in a Canadian

context have been considered adequate with internal

consistency coefficients of at least .70 for each of the five

subscales [50]. A French-Canadian version was used in the

present study [51].

Health-related quality of life

The SF-12 Health Survey version 2 [52] is a short form of

the SF-36, the most widely used health survey. The 12 items

are rated on a 5-point Likert scale, and eight subscale scores

can be derived from the answers (physical functioning, role

physical, bodily pain, general health, vitality, social func-

tioning, role emotional, and mental health). The psycho-

metric properties of the SF-12 version 2 are adequate with

reliability coefficients for the eight subscales ranging from

0.73 to 0.87 in general population [53]. A French–Canadian

version was used.

Data analysis

Between-group comparisons (good sleepers, insomnia

symptoms, and insomnia syndrome) were performed using

chi-squares and analyses of variance (ANOVAs). When

significant, Pearson chi-squares were followed by three

post hoc comparisons, comparing each group to the others

in 2�2 contingency tables [54–56]. If the post hoc chi-

square was higher than the Bonferroni critical value, m2(1,

1 � a/c)=m2(1, 1 � .05/3)=5.73 [54], this comparison

was considered significant. For significant ANOVAs,

multiple comparisons were conducted using the Ryan-

Einot-Gabriel-Welsh F (REGW F) tests to ensure statisti-

cally powerful comparisons while controlling alpha error

inflation [57]. Then, following Baron and Kenny’s [58]

suggestion, factorial ANOVA (groups�gender) was used

to assess the moderating effect of gender on the

relationship between sleep status and insomnia correlates

(dependent variables). Lastly, a multivariate ordinal (three

levels: good sleepers, insomnia symptoms, and insomnia

syndrome) logistic regression with cumulative logit link

Table 1

Demographic characteristics of the sample

Variables

Good sleepers (n=493) Insomnia symptoms (n=308) Insomnia syndrome (n=147)

M (S.D.) M (S.D.) M (S.D.) F SA (%)

Age

42.6a (13.9) 44.5a,b (14.3) 46.2b (13.5) 3.98* .80

% (n) % (n) % (n) m2

Gender

Women 58.0a (285) 59.1a (182) 70.1b (103) 7.094 .17

Men 42.0 (206) 40.9 (126) 29.9 (44)

Marital Status

Single/divorced/widowed 40.1 (196) 40.8 (125) 48.3 (71) 3.25 .26

Married/common-law relationship 59.9 (293) 59.2 (181) 51.7 (76)

Education

Grade School 4.7 (23) 4.5 (13) 5.9 (9)

High School 44.3 (219) 43.1 (125) 50.0 (76) 4.29 .02

Junior College 21.9 (108) 23.4 (68) 22.4 (34)

University 29.1 (144) 29.0 (84) 21.7 (33)

Occupation

Working/Student 77.9 (381) 72.3 (219) 66.2 (96) 8.964 .92

Nonworking/retired 22.1a (108) 27.7b (84) 33.8b (41)

Family Income

V$60000 68.5 (318) 73.5 (211) 81.0 (111) 8.644 .90

z$60001 31.5a (146) 26.5a,b (76) 19.0b (26)

SA, strength of association.

For ordinal variables, SA was computed as squared Spearman correlation. For continuous variables, SA was computed as Eta squared. SA represents the

percentage of variance explained by the sleep quality for each of the dependent variables.

Means with different subscripts are significantly different on the REGW multiple comparison test.

4 Pb.05.

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166 161

function was performed to identify the most important

variables in predicting sleep status group membership

[59,60]. All predictors were entered in one step into the

regression equation. Variance inflation index and colli-

nearity tests were performed to investigate multicollinear-

ity among predictors. Alpha level was set at a two-tailed

5% for all analyses. Most analyses were performed using

SPSS (version 10; SPSS, Chicago, IL, USA) except the

logistic regression and multicollinearity tests that were

completed under SAS System for Windows, Release 9.1

(Cary, NC).

Results

Participants

The overall sample (n=953) included 60% women, and

participants’ mean age was 43.7 years (S.D.=14.0; range

18–83). Most participants were Caucasian (98%), had

completed at least a high school degree (94.1%), were

married or living with a partner (58.3%) and were working

(66.2%). Based on the information gathered in the telephone

survey, individuals who did not return the questionnaire

(n=365) were significantly younger (mean age, 39.9 years;

S.D. =15.4) [F(1,1360)=17.63, Pb.0001] and included a

lower proportion of women (51%) than responders [m2(1,

n=1362)=7.5, Pb.01]. There were no significant differences

between nonresponders and responders regarding marital

status and education, but there was a significant difference

regarding sleep satisfaction, with more nonresponders being

dissatisfied with their sleep (28.8%) than responders

(23.4%) [m2(1, n=1362)=4.2, Pb.05].

Sleep status

Five participants could not be classified in one of the

three groups because of missing data. Of the 948 remaining

participants, 493 (51.7%) were classified as good sleepers,

308 (32.3%) as having insomnia symptoms and 147

(15.4%) as having an insomnia syndrome. Of the last

group, 20 individuals did not fulfill all the insomnia

diagnostic criteria but used prescribed sleep medication for

at least three nights per week. ISI scores were significantly

different between groups. Good sleepers obtained lower

scores (M=3.7; S.D.=3.2) than the two other groups, and the

insomnia symptoms group (M=8.4; S.D.=4.4) presented

lower scores than the insomnia syndrome group (M=15.4;

S.D.=4.1) [F(2,945)=573.3, Pb.001]. The same pattern was

observed regarding PSQI scores: good sleepers showed

lower scores (M=3.6; S.D.=1.8) than the insomnia symp-

toms group (M=6.1; S.D.=2.7), which presented lower

scores than the insomnia syndrome group (M=10.2;

S.D.=3.1) [F(2, 945)=447.9, Pb.001].

Factors associated with insomnia

Table 1 presents demographic characteristics of the three

sleep status groups. Groups did not significantly differ

Table 2

Sleep, psychological, and health variables (n=948)

Good sleepers (n=493) Insomnia symptoms (n=308) Insomnia syndrome (n=147)

m2 SA% (n) % (n) % (n)

Sleep variables

Personal history of insomnia (yes) 18.3a (90) 35.3b (108) 54.4c (80) 78.9844 8.07

Familial history of insomnia (yes) 32.7 (161) 36.7 (113) 38.1 (56) 2.19 0.14

Psychological variables

BDI-II (score z20) 4.2a (17) 11.5b (33) 26.8c (38) 57.1644 6.00

STAI-Trait (score z59) 1.4a (7) 2.6a (8) 12.3b (18) 40.6144 3.28

M (S.D.) M (S.D.) M (S.D.) F

BDI-II 5.7a (5.9) 8.8b (7.4) 13.9c (9.0) 80.0944 14.20

STAI-Trait 37.1a (8.6) 40.0b (9.0) 46.6c (9.4) 64.9344 12.30

APS 29.9a (6.8) 31.7b (6.3) 34.8c (6.9) 31.1344 6.10

PSS 21.5a (6.6) 23.3b (6.9) 27.5c (8.2) 42.7344 8.30

CISS

Task-oriented coping 55.9 (9.5) 55.2 (9.9) 54.4 (9.9) 1.63 0.30

Emotion-oriented coping 37.8a (10.9) 39.8b (10.8) 45.4c (11.5) 27.0944 5.40

Avoidance-oriented coping 45.0a (11.0) 43.1b (11.3) 44.8a,b (10.0) 3.194 0.70

NEO-FFI

Neuroticism 15.5a (8.0) 17.5b (7.8) 22.4c (8.5) 42.1744 8.30

Extraversion 29.4a (6.3) 28.1b (6.5) 26.3c (5.9) 14.3144 3.20

Openness 26.4 (5.9) 27.3 (6.6) 26.1 (6.6) 2.59 0.60

Agreeableness 34.6 (5.1) 34.1 (5.9) 33.5 (5.6) 2.26 0.50

Conscientiousness 36.9 (5.8) 36.2 (6.3) 36.3 (5.7) 1.26 0.40

Health-related quality of life

SF-12 Health Survey

General Health 75.2a (17.8) 71.2b (19.1) 61.5c (23.3) 29.0844 5.80

Bodily Pain 87.6a (19.7) 82.8b (22.7) 71.3c (29.5) 30.0744 6.00

Social functioning 83.1a (19.8) 76.5b (21.6) 61.6c (24.9) 58.5844 11.00

Physical functioning 85.5a (24.7) 81.3b (25.9) 67.5c (34.3) 24.9644 5.00

Vitality 71.6a (15.2) 67.1b (17.8) 53.2c (22.0) 63.8844 12.90

Role physical 82.8a (19.8) 76.6b (22.0) 64.3c (25.6) 42.9344 8.5

Role emotional 81.4a (18.3) 74.2b (20.6) 61.4c (23.2) 59.0044 11.0

Mental health 73.1a (14.8) 67.7b (16.3) 55.2c (19.1) 71.6844 13.20

For ordinal variables, SA was computed as squared Spearman correlation. For continuous variables, SA was computed as Eta squared. SA represents the

percentage of variance explained by the sleep status group membership for each of the dependent variables.

Means with different subscripts are significantly different on the REGW multiple comparison test.

4 Pb.05.

44 Pb.01.

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166162

regarding marital status and education. In contrast, there

were significant differences between groups regarding age

[F(2,938)=4.0, Pb.05], gender [m2(2, n=946)=7.09, Pb.05],

occupation m2(2, n=937)=8.96, Pb.05], and family

income [m2(2, n=888)=8.64, Pb.05]. Post hoc comparisons

revealed that the good sleepers group was significantly

younger compared to the insomnia syndrome group but not

compared to the insomnia symptoms group, which, in turn,

did not significantly differ from the insomnia syndrome

group. The proportion of women was higher in the insomnia

syndrome group relative to the insomnia symptoms and

the good sleepers groups. Regarding occupation, the

proportion of individuals working or studying was higher

in the good sleepers group compared to the insomnia

symptoms and syndrome groups. Lastly, the proportion of

individuals with higher incomes was higher in the good

sleepers group compared to the insomnia syndrome group

but not relative to the insomnia symptoms group.

Table 2 presents data for insomnia history (personal and

familial), psychological variables, and health-related quality

of life. There were significantly more individuals reporting

a previous episode of insomnia in the insomnia syndrome

group than in the two other groups and in the insomnia

symptoms group compared to good sleepers. There was no

significant between-group difference for family history of

insomnia, although good sleepers presented a lower

proportion than the other groups. For psychological

measures, both the BDI-II and the STAI-Trait mean scores

were significantly different among the three groups. When

BDI-II scores were computed without the item assessing

sleep disturbances, group means were still significantly

different (5.3 for good sleepers, 7.9 for insomnia symptoms

and 12.5 for insomnia syndrome) [F(2,938)=70.15, Pb.01].

The proportion of individuals presenting a score z20 was

significantly different between groups, as was the proportion

of individuals presenting a STAI-Trait score z59. The were

Table 3

Three-category (good sleepers, insomnia symptoms, and insomnia syn-

drome) ordinal logistic regression results (n=931)

Analysis of estimates

Predictors

Odds

ratio point

estimatea

95% Wald

confidence

limits

Wald

chi-square P

Previous episode

of insomnia

2.55 1.91 3.40 40.82 b.01

BDI-II 1.05 1.02 1.08 11.12 b.01

STAI-Trait 0.99 0.96 1.03 0.12 .73

PSS 1.00 0.97 1.03 0.05 .81

CISS

Emotion-oriented

coping

1.00 0.98 1.02 0.00 .95

APS 1.01 0.99 1.04 1.51 .30

NEO-FFI

Neuroticism 0.99 0.96 1.02 0.45 .50

Extraversion 1.00 0.97 1.02 0.19 .66

SF-12 health survey

General health 1.00 0.99 1.01 0.00 .97

Bodily pain 0.99 0.99 1.00 0.49 .48

Social functioning 1.00 0.99 1.01 0.42 .52

Physical functioning 1.00 0.99 1.00 0.34 .56

Vitality 0.99 0.98 1.00 5.37 .02

Role physical 0.99 0.98 1.00 2.87 .09

Role emotional 0.99 0.99 1.00 1.77 .18

Mental health 0.99 0.98 1.00 2.29 .13

a This odds ratio is estimated by exponentiating the corresponding

parameter estimate of h, B.

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166 163

also significant differences on the PSS, the CISS emotion-

oriented coping subscale, the APS, and the NEO-FFI

neuroticism and extraversion subscales, with the insomnia

syndrome group presenting higher scores than the two other

groups and the insomnia symptoms group presenting higher

scores than good sleepers. Scores on the CISS avoidance-

oriented coping subscale were significantly higher for the

good sleepers group compared to the insomnia symptoms

group but not compared to the insomnia syndrome group. For

health-related quality of life, all SF-12 subscales were

significantly different across groups. The insomnia syndrome

group showed scores suggesting a poorer quality of life

than the two other groups, and the insomnia symptoms group

showed scores suggesting a poorer quality of life than

good sleepers.

Factorial ANOVAs (group�gender) were conducted to

control for the effect of a higher proportion of women than

men in the sample. Results showed that gender did not have

a moderating effect on the relationship between sleep status

and any of the psychological and health-related quality of

life variables.

A multivariate ordinal (three levels) logistic regression

was performed to identify the most important variables in

predicting sleep status membership. Variables entered in the

equation included previous episode of insomnia (yes/no),

BDI-II, STAI-Trait, APS, PSS, the CISS emotion-oriented

coping subscale, the NEO-FFI neuroticism and extraversion

subscales, and the eight SF-12 subscales. A total of 931

observations (listwise, missing n=22 cases or 2.3%) were

submitted to the analysis (483 good sleepers, 302 individ-

uals with insomnia symptoms, and 146 individuals with an

insomnia syndrome). Since two predictors exhibited high

variance inflation values (STAI-Trait=5.8; NEO-FFI neu-

roticism subscale=3.6) but no problems were noted on other

multicollinearity tests, no predictors were removed from the

logistic regression. The final model exhibited a moderate fit

between observed and predicted group membership

(pseudo-R2=.25, 57.0% of correct classification). Three

variables [i.e., previous episode of insomnia, BDI-II [odds

ratio (OR)=1.05], and SF-12 vitality subscale (OR=0.99)]

were significantly associated with the presence of an

insomnia syndrome, whereas one other SF-12 subscale

(role physical, OR=0.99) was near statistical significance

(see Table 3). Thus, individuals who previously experienced

insomnia were 2.55 (OR=2.55) times more at risk of being

classified in a more severe category of insomnia than those

who never experienced insomnia in the past. Moreover,

each increase of one point on the BDI-II is associated with a

5% increase (OR=1.05), and each increase of one point of

the SF-12 vitality subscale is associated with a 1% decrease

(OR=0.99) of the risk of being in a more severe category

(i.e., insomnia symptoms or syndrome).

Discussion

The present study reveals that almost all factors tradi-

tionally associated with insomnia in studies conducted with

selected clinical samples also emerge as insomnia correlates

in a population-based sample. Results suggest that individ-

uals with insomnia endorse more psychological symptoma-

tology and more impairments of quality of life than good

sleepers, with degree of impairment increasing linearly with

insomnia severity.

Results of this study highlight the critical role of mental

health in insomnia. Indeed, several mental health-related

variables (e.g., BDI-II, and SF-12 mental health) differed

significantly across groups, with depressive symptomatol-

ogy among the most reliable predictors of sleep status

group membership. Moreover, a considerable number of

individuals in the insomnia symptoms and syndrome

groups (11.5% and 26.8%, respectively) obtained BDI-II

scores z20, indicating depressive symptoms of at least

moderate intensity [41], compared to only 4.2% of good

sleepers exceeding that threshold. Several epidemiological

studies have already shown that individuals with insomnia

complaints present higher levels of depression and anxiety

symptoms than those without insomnia [6,10–12,61]. In the

present study, the distinction between insomnia symptoms

and syndrome showed that even when sleep difficulties

are less severe, anxiety, neuroticism and depressive

symptomatology are more salient than in good sleepers.

However, given that all these measures are highly

correlated, it is unclear whether this is reflecting different

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166164

psychological dimensions of insomnia or a more generic

psychological distress profile. Furthermore, those results

are similar to some previous studies that suggested that

the presence of neurotic symptoms, emotional inhibition

and an inability to discharge anger characterizes individuals

with insomnia [16–18,20,22]. Our study was innovative

in its use of the NEO-FFI, which provided an over-

view of emotional, attitudinal, and motivational styles,

rather than simply an assessment of symptoms of mental

health disorder.

Individuals with insomnia (i.e., symptoms or syndrome)

reported higher arousal predisposition than good sleepers,

suggesting that they were more psychologically aroused, not

only at bedtime but as a general trait feature. Those with

insomnia symptoms and syndrome also reported higher

scores on the PSS and on the CISS emotion-coping subscale

than good sleepers. These findings are consistent with our

previous study [21], which also showed that individuals

with insomnia presented higher levels of bedtime arousal,

perceived their lives as more stressful and relied more on

emotion-focused coping strategies than good sleepers.

Collectively, these findings support the model suggesting

that the relationship between daytime stress and nighttime

sleep is mediated by bedtime arousal [21]. Nonetheless, it is

only through prospective longitudinal studies that the

hypothesis that increased arousal is a predisposing factor

for insomnia development may be confirmed.

Lastly, we found that a previous episode of insomnia was

among the best predictors of sleep status group membership,

a finding also reported by Klink et al. [14]. The rate of prior

history of insomnia among the insomnia syndrome (51%)

was similar to those observed in previous studies (44% [62];

56% [14]). Thus, these results would indicate that insomnia

is a recurrent problem for most people. Unlike previous

studies [31,32] however, there was no relation between

family history of insomnia and presence of insomnia

symptoms and syndrome.

This research has some limitations, including its cross-

sectional nature, which precludes any definite conclusions

about the direction of the relation between insomnia and its

correlates. Do psychological factors and health-related

quality of life play a role in the development of sleep

difficulties as predisposing factors, precipitating factors or

consequences? Personal and family history of insomnia,

arousal predisposition, and personality traits are generally

conceptualized as predisposing factors to insomnia,

whereas health-related quality of life is usually considered

as a consequence of insomnia. However, further longitudi-

nal studies are needed to corroborate those hypotheses. The

lack of differentiation between primary insomnia and

insomnia secondary to a mental, medical, or other sleep

disorder also warrants a cautious interpretation of the

results. Significant physical and mental health problems are

frequently associated with insomnia and may have been

confounding factors in the observed associations between

sleep status and the variables measured. Insomnia could be

the consequence or a symptom of another difficulty, such as

depression or a chronic disease, and the fact that we did not

document the presence of physical and mental health

disorders with standardized diagnostic procedures restricts

the interpretation of our results. For example, the finding

that bodily pain and physical conditions are important

variables in predicting group membership could be

explained by secondary insomnia, or on the other hand,

those two variables could simply reflect insomnia con-

sequences. Also, new independent variables like genetic,

cultural, environmental, lifestyle, and health-related varia-

bles (e.g., medical disorders, medication utilization) should

be further explored as potential insomnia correlates. Finally,

although the current sample was population-based, the

proportion of women and individuals dissatisfied with their

sleep was higher than in the general population, limiting

the generalization of the results.

Despite these limitations, this study sheds new light on

the topic of insomnia correlates. Firstly, with a population-

based sample that included both good sleepers and

individuals with different degree of insomnia severity, this

study may have captured a more accurate representation of

the association between sleep quality and psychological and

health-related quality of life correlates. The inclusion of

individuals with insomnia symptoms suggested that sleep

quality may be best illustrated by a continuum rather than

dichotomously and that insomnia correlates (e.g., depressive

symptoms and anxiety) may also follow the same pattern.

Psychological distress and quality-of-life impairment

increased with insomnia severity. Those results could also

guide the development of effective early intervention

programs to prevent chronic insomnia or the development

of other mental health disorders (e.g., major depression) as

soon as the first insomnia symptoms are noticed. Secondly,

this study focuses attention on the importance of rigorous

definition of insomnia with the utilization of a well-

operationalized algorithm, based on insomnia diagnostic

criteria from DSM-IV-TR [35] and ICD-10 [36], to deter-

mine the quality of participants’ sleep. Moreover, significant

between-group differences, both on the PSQI and the ISI,

support our sleep status classification algorithm, with scores

obtained on these two measures following a linear gradation

of sleep difficulties.

Longitudinal research is needed to assess the relative

contribution of those factors in the first onset and evolution

of insomnia over time. With repeated follow-up assess-

ments, we may also be able to identify risk factors for

insomnia and predictors or moderating variables of insom-

nia remission and relapse.

References

[1] Morin CM, LeBlanc M, Daley M, Gregoire JP, Merette C.

Epidemiology of insomnia: prevalence, self-help treatments, con-

sultations, and determinants of help-seeking behaviors. Sleep Med

2006;7:123–30.

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166 165

[2] Ohayon MM. Epidemiology of insomnia: what we know and what we

still need to learn. Sleep Med Rev 2002;6:97–111.

[3] Lichstein KL, Durrence HH, Taylor DJ, Bush AJ, Riedel BW.

Quantitative criteria for insomnia. Behav Res Ther 2003;427–45.

[4] Ancoli-Israel S, Roth T. Characteristics of insomnia in the United

States: results of the 1991 National Sleep Foundation Survey. I. Sleep

1999;22:347–53.

[5] Leger D, Guilleminault C, Dreyfus JP, Delahaye C, Paillard M.

Prevalence of insomnia in a survey of 12,778 adults in France. J Sleep

Res 2000;9:35–42.

[6] Mellinger GD, Balter MB, Uhlenhuth EH. Insomnia and its treatment.

Prevalence and correlates. Arch Gen Psychiatry 1985;42:225–32.

[7] Ohayon MM. Prevalence of DSM-IV diagnostic criteria of insomnia:

distinguishing insomnia related to mental disorders from sleep

disorders. J Psychiatr Res 1997;31:333–46.

[8] Ohayon MM, Caulet M, Guilleminault C. How a general population

perceives its sleep and how this relates to the complaint of insomnia.

Sleep 1997;20:715–23.

[9] Ohayon MM, Smirne S. Prevalence and consequences of insomnia

disorders in the general population of Italy. SleepMed 2002;3:115–20.

[10] Taylor DJ, Lichstein KL, Durrence H, Riedel BW, Bush AJ.

Epidemiology of insomnia, depression, and anxiety. Sleep 2005;28:

1457–64.

[11] Lindberg E, Janson C, Gislason T, Bjornsson E, Hetta J, Boman G.

Sleep disturbances in a young adult population: can gender differences

be explained by differences in psychological status? Sleep 1997;

20:381–7.

[12] Foley DJ, Monjan AA, Brown SL, Simonsick EM, Wallace RB,

Blazer DG. Sleep complaints among elderly persons: an epidemio-

logic study of three communities. Sleep 1995;18:425–32.

[13] Foley D, Ancoli-Israel S, Britz P, Walsh J. Sleep disturbances and

chronic disease in older adults: results of the 2003 National Sleep

Foundation Sleep in America Survey. J Psychosom Res 2004;56:

497–502.

[14] Klink ME, Quan SF, Kaltenborn WT, Lebowitz MD. Risk factors

associated with complaints of insomnia in a general adult population

Influence of previous complaints of insomnia. Arch Intern Med

1992;152:1634–7.

[15] Ohayon MM, Morselli PL, Guilleminault C. Prevalence of nightmares

and their relationship to psychopathology and daytime functioning in

insomnia subjects. Sleep 1997;20:340–8.

[16] Edinger JD, Stout AL, Hoelscher TJ. Cluster analysis of insomniacs’

MMPI profiles: relation of subtypes to sleep history and treatment

outcome. Psychosom Med 1988;50:77–87.

[17] Kales A, Caldwell AB, Preston TA, Healey S, Kales JD. Personality

patterns in insomnia. Theoretical implications. Arch Gen Psychiatry

1976;33:1128–34.

[18] Kales A, Caldwell AB, Soldatos CR, Bixler EO, Kales JD. Biopsy-

chobehavioral correlates of insomnia. II. Pattern specificity and

consistency with the Minnesota Multiphasic Personality Inventory.

Psychosom Med 1983;45:341–56.

[19] Monroe LJ, Marks PA. MMPI differences between adolescent poor

and good sleepers. J Consult Clin Psychol 1977;45:151–2.

[20] Shealy RC, Lowe JD, Ritzler BA. Sleep onset insomnia: personality

characteristics and treatment outcome. J Consult Clin Psychol

1980;48:659–61.

[21] Morin CM, Rodrigue S, Ivers H. Role of stress, arousal, and coping

skills in primary insomnia. Psychosom Med 2003;65:259–67.

[22] Schneider-Helmert D. Twenty-four-hour sleep-wake function and

personality patterns in chronic insomniacs and healthy controls. Sleep

1987;10:452–62.

[23] Vollrath M, Wicki W, Angst J. The Zurich study. VIII. Insomnia:

association with depression, anxiety, somatic syndromes, and course

of insomnia. Eur Arch Psychiatry Neurol Sci 1989;239:113–24.

[24] Coren S. Prediction of insomnia from arousability predisposition

scores: scale development and cross-validation. Behav Res Ther

1988;26:415–20.

[25] Espie CA. The psychological treatment of insomnia. Chischester

(UK)7 Wiley, 1991.

[26] Kales A, Kales JD. Evaluation and treatment of insomnia. New York7

Oxford University Press, 1984.

[27] Morin CM. Insomnia: psychological assessment and management.

New York7 The Guilford Press, 1993.

[28] Harvey AG. Pre-sleep cognitive activity: a comparison of sleep-

onset insomniacs and good sleepers. Br J Clin Psychol 2000;39:

275–86.

[29] Kales JD, Kales A, Bixler EO, Soldatos CR, Cadieux RJ, Kashurba GJ,

Vela-Bueno A. Biopsychobehavioral correlates of insomnia, V: clinical

characteristics and behavioral correlates. Am J Psychiatry 1984;141:

1371–6.

[30] Leger D, Scheuermaier K, Philip P, Paillard M, Guilleminault C.

SF-36: evaluation of quality of life in severe and mild insomniacs

compared with good sleepers. Psychosom Med 2001;63:49–55.

[31] Zammit GK, Weiner J, Damato N, Sillup GP, McMillan CA. Quality

of life in people with insomnia. Sleep 1999;22(Suppl 2):379–85.

[32] Bastien CH, Morin CM. Familial incidence of insomnia. J Sleep Res

2000;9:49–54.

[33] Dauvilliers Y, Morin C, Cervena K, Carlander B, Touchon J, Besset A,

Billiard M. Family studies in insomnia. J Psychosom Res 2005;58:

271–8.

[34] Hauri P, Olmstead E. Childhood-onset insomnia. Sleep 1980;3:

59–65.

[35] Kish L. Survey sampling. New York7 John Wiley and Sons Inc, 1965.

[36] American Psychiatric Association. Diagnostic and Statistical Manual

of Mental Disorders. Washington (DC)7 American Psychiatric

Association, 2000.

[37] World Health Organization. The ICD-10 classification of mental and

behavioral disorder: diagnostic criteria for research (10th revision).

Geneva7 World Health Organization, 1992.

[38] Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The

Pittsburgh Sleep Quality Index: a new instrument for psychiatric

practice and research. Psychiatry Res 1989;28:193–213.

[39] Bastien CH, Vallieres A, Morin CM. Validation of the Insomnia

Severity Index as an outcome measure for insomnia research. Sleep

Med 2001;2:297–307.

[40] Blais FC, Gendron L, Mimeault V, Morin CM. Evaluation

de l’insomnie: validation de trois questionnaires [Assessment of

insomnia: validation of three questionnaires]. Encephale 1997;

23:447–53.

[41] Beck A, Steer RA, Brown GK. Manuel de l’Inventaire de

Depression de Beck. Toronto (Ontario, Canada)7 The Psychological

Corporation, 1996.

[42] Spielberger CD. Manual for the State-Trait Anxiety Inventory (STAI).

Palo Alto (Calif)7 Consulting Psychologists Press, 1983.

[43] Gauthier J, Bouchard S. Adaptation canadienne-francaise de la forme

revisee du State-Trait Anxiety Inventory de Spielberger. Can J Behav

Sci 1993;25:559–78.

[44] Cohen S, Kamarck T, Mermelstein R. A global measure of perceived

stress. J Health Soc Behav 1983;24:385–96.

[45] Endler NS, Parker JD. Stress and anxiety: conceptual and assessment

issues. Stress Med 1990;6:243–8.

[46] Endler NS, Parker JD. Multidimensional assessment of coping: a

critical evaluation. J Pers Soc Psychol 1990;58:844–54.

[47] Coren S, Mah KB. Prediction of physiological arousability: a

validation of the Arousal Predisposition Scale. Behav Res Ther

1993;31:215–9.

[48] Costa P, McCrae RR. Revised NEO Personality Inventory (NEO-PI-

R) and NEO Five-Factor Inventory (NEO-FFI) professional manual.

Odessa (Fla)7 Psychological Assessment Resources, Inc, 1992.

[49] Digman JM. Personality structure: emergence of the Five-Factor

Model. Annu Rev Psychol 1990;41:417–40.

[50] Holden RR, Fekken GC. The NEO FiveFactor Inventory in a

Canadian context: psychometric properties for a sample of university

women. Pers Individ Dif 1994;17:441–4.

M. LeBlanc et al. / Journal of Psychosomatic Research 63 (2007) 157–166166

[51] Sabourin S, Lussier Y. Traduction francaise de l’inventaire de

personnalite NEO-FFI [A French translation of the NEO-FFI].

Unpublished manuscript. 1992.

[52] Ware J, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey:

construction of scales and preliminary tests of reliability and validity.

Med Care 1996;34:220–33.

[53] Ware JE, Kosinski M, Turner-Bowker DM, Gandek B. How to score

version 2 of the SF-12 health survey. Lincoln (NE)7 QualityMetric

Incorporated, 2002.

[54] Gardner RC. Psychological statistics using SPSS for windows. Upper

Saddle River (NJ)7 Prentice Hall, 2000.

[55] Macdonald PLG, Gardner RC. Type I error rate comparisons of post

hoc procedures for I�J chi-square tables. Educ Psychol Meas 2000;

60:735–54.

[56] VassarStats: website for statistical computation [homepage on the

internet]. Poughkeepsie, New York7 Lowry R, c1998-2006 [cited 2005

Aug 5]. Vassar College, Professor of Psychology; Available from:

http://faculty.vassar.edu/lowry/tabs.html#csq.

[57] Kirk RE. Experimental design. Procedures for the behavioral sciences.

Pacific Grove (Calif)7 Brooks/Cole Publishing Company, 1995.

[58] Baron RM, Kenny DA. The moderator–mediator variable distinction

in social psychological research: conceptual, strategic, and statistical

considerations. J Pers Soc Psychol 1986;51:1173–82.

[59] Agresti A. Categorical data analysis. NewYork7 JohnWiley& Sons, 1990.

[60] Allison PD. Logistic regression using the SAS System: theory and

application. Cary (NC)7 SAS Institute, 1999.

[61] Ford DE, Kamerow DB. Epidemiologic study of sleep disturbances

and psychiatric disorders. An opportunity for prevention? JAMA

1989;262:1479–84.

[62] Bixler EO, Kales A, Soldatos CR, Kales JD, Healey S. Prevalence of

sleep disorders in the Los Angeles metropolitan area. Am J Psychiatry

1979;136:1257–62.