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Original Investigation |

Prevalence and Correlates of Nonrestorative Sleep Complaints FREE

Maurice M. Ohayon, MD, DSc, PhD
[+] Author Affiliations

Author Affiliation: Stanford Sleep Epidemiology Research Center, Stanford University School of Medicine, Stanford, Calif.


Arch Intern Med. 2005;165(1):35-41. doi:10.1001/archinte.165.1.35.
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Published online

Background  Nonrestorative sleep (NRS) has been little studied in the general population, even though this symptom has an important role in several medical conditions such as heart disease, fibromyalgia, and chronic fatigue syndrome, as well as various sleep disorders.

Methods  A total of 25 580 individuals (age range, 15-100 years) from the noninstitutionalized general population representative of 7 European countries (France, the United Kingdom, Germany, Italy, Portugal, Spain, and Finland) were interviewed by telephone using the Sleep-EVAL system. Nonrestorative sleep was analyzed in relationship to sociodemographic determinants, environmental factors, life habits, health, sleep-wake schedule, and psychological factors.

Results  The prevalence of NRS was 10.8% (95% confidence interval, 10.4%-11.2%) in the sample, was higher in women than in men (12.5% vs 9.0%; P<.001), and decreased with age. The United Kingdom (16.1%) and Germany (15.5%) had the highest prevalence of NRS and Spain (2.4%), the lowest. In multivariate analyses, several factors were positively associated with NRS. The most important were younger age, dissatisfaction with sleep, difficulty getting started in the morning, stressful life, presence of anxiety, bipolar or a depressive disorder, and having a physical disease. When compared with subjects who have difficulty initiating or maintaining sleep (without NRS), subjects with NRS reported more frequently a variety of daytime impairment (irritability, physical, and mental fatigue) and consulted a physician twice as frequently for their sleeping difficulties than did other subjects with insomnia.

Conclusions  Nonrestorative sleep is a frequent symptom in the general population, but its prevalence largely varies between countries. It is often associated with mental disorders and characteristics of sleep deprivation (such as extra sleep time on weekends). Nonrestorative sleep affected more frequently the active classes of the population and caused greater daytime impairment than difficulty initiating or maintaining sleep.

It has been documented that sleep disturbances cause nonrestorative sleep (NRS), which, in turn, is associated with greater daytime sleepiness and deterioration in performance. However, usually in community-based studies, the assessment of insomnia is limited to difficulty initiating or maintaining sleep.16

Nonrestorative sleep appeared as an insomnia symptom in the DSM-III-R of the American Psychiatric Association in 1987.7 It was also the first time that a chapter was devoted to sleep disorders in the DSM classification. It is described as the feeling that sleep is restless, light, or of poor quality even though the duration may appear normal.

However, epidemiological studies have been slow to include NRS. Outside of the works of Ohayon et al,810 virtually no community study has paid attention to this symptom. Therefore, little information exists about these subjects and the frequency and severity of daytime impairment in the general population.

There is growing evidence of the importance of NRS in various clinical conditions. It has been associated with a poor prognosis in women with coronary heart disease,11 obesity,12 fibromyalgia, and chronic fatigue syndrome.13 It is also associated with various sleep disorders such as obstructive sleep apnea syndrome, restless legs syndrome, and periodic limb movement disorders.14,15 However, these clinical findings have not been followed by general population surveys. This report presents the prevalence of NRS in 7 European countries and the factors associated with NRS.

DESIGN OF THE SAMPLES

This study involved 25 580 individuals from the noninstitutionalized general population representative of 7 European countries: France, the United Kingdom, Germany, Italy, Portugal, Spain, and Finland. These countries total 255.5 million Europeans 15 years or older.

In each country, the samples were drawn using a 2-stage procedure. At the first stage, telephone numbers were selected with respect to the distribution of the population according to the different states (or areas) and the size of the settlements of each studied country. National census data for each of these countries provided the necessary information on the population.

At the second stage, during the telephone contact, the Kish method16 was used to select 1 respondent in the household. This method allowed for selecting a respondent based on age and sex to maintain the representation of the sample according to these 2 parameters. It also limited the within-sampling unit noncoverage error. If the household member thus chosen refused to participate, the household was dropped but registered as a refusal. Another telephone number in the same area replaced it, and the process was repeated. Phone numbers were dialed at least 10 times at different times of the evening and on different days, including weekdays and weekends, before being replaced.

The interviews were conducted in the official language of each country. During the telephone contact, interviewers explained the goals of the study to potential participants and then requested verbal consent before proceeding to the interview. For subjects younger than 18 years, the verbal consent of 1 of the parents also was obtained. Participation was anonymous.

Subjects who declined to participate or who gave up before completing half the interview were classified as refusals. Excluded individuals were those who were not fluent in the national language, who had a hearing or speech impairment, or who had an illness that precluded being interviewed.

The participation rate was calculated by dividing the number of completed interviews by the number of eligible participants. All the countries, with the exception of Germany (68.1%), had a participation rate of 80% or higher. The overall participation rate for the 7 countries was 80.3%.

INSTRUMENT

Interviewers used the Sleep-EVAL knowledge-based expert system17,18 to conduct the interviews. This system was specially designed to perform epidemiological studies in the general population. This artificial intelligence tool possessed a causal reasoning mode enabling it to formulate a series of diagnostic hypotheses based on the responses provided by a subject. The nonmonotonic, level-2 inference engine of the system examined these hypotheses and confirmed or rejected them through further questions and deductions. Concurrent diagnoses were allowed in accordance with the DSM-IV19 and the Classification of Sleep Disorders or the International Classification of Sleep Disorders.20 The system terminated the interview once all diagnostic possibilities were exhausted.

The differential process was based on a series of key rules allowing or prohibiting the co-occurrence of 2 diagnoses. The questionnaire of the expert system was designed such that the decision about the presence of a symptom was based on the interviewee’s responses rather than on the interviewer’s judgment. This approach has been proven to yield better agreement between lay interviewers and psychiatrists on the diagnosis of minor psychiatric disorders.21

Studies performed in the general population and in clinical settings show that Sleep-EVAL is a valid instrument in the assessment of sleep disorders.22,23 The duration of the interviews ranged from 10 to 333 minutes, with a mean ± SD of 40 ± 20 minutes. The longest interviews involved subjects with multiple sleep and mental disorders. Interviews were completed over 2 or more sessions if the duration exceeded 60 minutes.

The questionnaire was translated from the English version to Finnish, German, Italian, Portuguese, and Spanish. Each translation was verified by at least 3 translators who were native speakers of the targeted language. In all translations, the questionnaire was translated back to English to verify that the questions remained with the same meaning.

VARIABLES

Nonrestorative sleep was assessed using the question “How frequently are you bothered by the following problem: Your sleep is not refreshing, you don’t feel rested even if the duration of your sleep is normal.” The subjects answered on the following frequency scale: daily, 5 to 6 times a week, 3 to 4 times a week, 1 to 2 times a week, 2 to 3 times a month, less than 1 time a month, never, or rarely. Nonrestorative sleep was considered present when it was reported to occur 3 to 4 times a week or more and lasted for at least 1 month.

Nonrestorative sleep was analyzed in association with 6 classes of variables:

  • Sociodemographic factors: age, sex, marital status, occupation, income, educational level, countries, and size of the settlement.

  • Environmental factors: quality of the bedroom (temperature, mattress, furniture, and noise level).

  • Life habit factors: use of alcohol, tobacco, caffeine, eating before going to bed, activities performed in bed before falling asleep, required objects or particular environment needed to fall asleep, doing physical exercise at least 3 times per week for at least 15 minutes per session.

  • Health factors: physical disease, body mass index, and the number of medical consultations in the previous year.

  • Psychological factors: level of stress, the occurrence of a stressful event during the previous year, satisfaction with one’s social network, depressive mood, anxious mood, DSM-IV depressive disorders, and anxiety disorders.

  • Sleep-wake factors: sleep-wake schedule, regularity of the bedtime and wake-up hours, sleep latency, sleep duration, and extra sleep on the weekend and days off. Global sleep dissatisfation,17 frequency of bad night’s sleep, nocturnal awakenings, and ease of getting started in the morning were also evaluated.

Consequences of NRS were also analyzed: tiredness upon awakening, daytime sleepiness, naps, accidents, and medical consultations for sleep problems.

STATISTICAL ANALYSIS

Prevalences of NRS are given with 95% confidence intervals (CIs). Bivariate analyses are performed using χ2 tests or analysis of variance, depending on the variables. Logistic regressions were used to compute the odds ratios (ORs) associated with NRS. Colinearity between variables was verified beforehand. The SUDAAN software (Research Triangle Institute, Research Triangle Park, NC), which allows an appropriate estimate of the standard errors from stratified samples by means of a Taylor series linearization method, was used to calculate the logistic regressions. Reported differences were significant at P≤.05.

SOCIODEMOGRAPHIC DETERMINANTS

Nonrestorative sleep was reported by 10.8% (95% CI, 10.4%-11.2%; n = 2756) of the sample. Table 1 gives the prevalence of NRS for each country. The prevalence was highest in the United Kingdom (16.1%) and Germany (15.5%) and the lowest in Spain (2.4%), compared with all other countries.

Table Graphic Jump LocationTable 1. Prevalence of NRS by Subject Demographics

More women than men and more young subjects than older subjects (≥55 years) reported NRS (Table 1). Prevalence of NRS was higher among separated/divorced individuals, night shift workers, and subjects with 9 years or less of schooling (Table 1).

ENVIRONMENTAL FACTORS

Although almost all poor bedroom conditions with the exception of having a “too bright” bedroom were associated with NRS in bivariate analyses. Only sleeping in a too stuffy bedroom and sleeping in an uncomfortable bed made a significant independent contribution to NRS in the logistic regression model (Table 2).

Table Graphic Jump LocationTable 2. Prevalence of NRS and Associated Factors in Logistic Regression
LIFE HABIT FACTORS

Life habit factors included alcohol, tobacco, and caffeine intake as well as several other habits associated with poor sleep hygiene. The likelihood of reporting NRS significantly increased with smoking and with alcohol taken at bedtime (Table 2). Reading in bed before falling asleep appeared to be a protective factor of NRS in the multivariate model (OR, 0.84; 95% CI, 0.74-0.95; P<.001). Several life habits were significant in bivariate analyses but did not make an independent contribution to NRS in the multivariate analyses. These habits were daily coffee intake, daytime alcohol intake, eating before going to sleep, doing activities that required concentration in bed, and playing games in bed (eg, crossword puzzles).

HEALTH FACTORS

In the multivariate model, the presence of physical illnesses was significantly associated with NRS (18.2% vs 9.6%; P = .02) with an OR of 1.24 (95% CI, 1.04-1.46). As for the number of medical consultations, the categories 3 to 5 consultations (OR, 1.26; 95% CI, 1.06-1.49; P<.01) and 6 to 10 consultations (OR,1.26; 95% CI, 1.00-1.58; P = .05) were significantly associated with NRS. Body mass index was not significantly related to NRS.

SLEEP-WAKE FACTORS

Prevalence of NRS linearly increased with the length of the sleep latency (Table 2). As for nighttime sleep duration, the shorter the sleep duration, the higher the prevalence of NRS. Interestingly, in the multivariate model a short sleep duration (<6 hours) was a protective factor for NRS, whereas a long sleep duration (>9 hours) was associated with a greater likelihood of having NRS. This indicated that the association between short sleep and NRS was totally explained by other factors. The prevalence of NRS linearly increased with the length of the extra sleep time on weekends and/or days off, reaching 18.9% in those sleeping more than 3 hours extra compared with 7.9% in those keeping the same amount of sleep (Table 2).

Prevalence of NRS was 14 times higher in subjects globally dissatisfied with their sleep (Table 2). It also increased with the frequency of a bad night’s sleep and the frequency of nights when the subject awakened. In the morning, individuals with occasional or regular light to severe difficulty getting started clearly had a higher prevalence of NRS. Irregularity in sleep-wake schedule (ie, having about the same bedtime and wake up time <4 nights per week) and duration of time in bed once awakened were not significantly associated with NRS in the multivariate model (Table 2).

PSYCHOLOGICAL FACTORS

Individuals with mood disorders (depressive disorders and bipolar disorders) had a prevalence of NRS of more than 40%, compared with about 10% in those without a mood disorder. Mood disorders had the highest crude ORs. The adjusted ORs were still significant but much lower than the crude ones.

DAYTIME CONSEQUENCES ASSOCIATED WITH NRS

Subjects were asked if they experienced problems when they were sleeping poorly and to rate the intensity of the problems. Subjects with NRS were compared with those with other insomnia symptoms to determine if there was any difference between these 2 insomnia groups.

As seen in Table 3, one fifth of NRS subjects experienced physical fatigue or irritable mood. All daytime consequences were higher in NRS subjects compared with the other subjects with insomnia symptoms.

Table Graphic Jump LocationTable 3. Daytime Functioning in NRS and Other Subjects With Insomnia

The same observation was true for excessive daytime sleepiness. Of NRS subjects, 33.1% reported moderate to severe daytime sleepiness, whereas excessive daytime sleepiness was 11.3% in other subjects with insomnia symptoms (P<.001). Furthermore, NRS subjects more frequently consulted a physician about their sleep problems (16.0%) and were more likely to take sleep medication (16.6%) compared with other subjects with insomnia symptoms (9.9% and 11.3%, respectively; P<.001).

This study is the first, to my knowledge, to evaluate the factors associated with NRS in the general population. The study involved a large number of subjects (N = 25 580) from 7 European countries and assessed the prevalence of NRS on the basis of it occurring at least 3 to 4 times per week.

PREVALENCE OF NRS

As the results show, NRS affects more than 1 in 10 individuals, a prevalence comparable with difficulty initiating sleep (10.8%) and early morning awakenings (12.3%) but lower than for disrupted sleep (23.1%). Nonrestorative sleep occurred more frequently in young and middle-aged subjects than in those older than 55 years, whereas the prevalence of other insomnia symptoms increased with age.

We also observed important variations in the prevalence between the countries. Several explanations are possible: (1) One can observe a decrease in the prevalence following a North-South line, with the United Kingdom having the highest prevalence and Spain the lowest. (2) These differences could be attributed to the methodology or the questionnaire; however, this is unlikely because they were the same for all the countries. (3) Part of the explanation may reside in cultural differences related to sleeping habits. As my colleagues and I previously showed,24 German individuals are early wakers compared with other European countries and British individuals sleep the least. The variation of bedtime and wake-up hours are also more frequent in these 2 countries compared with the others.24 (4) The climate may also play a role, but this possibility remains to be further investigated. Spain, Portugal, and the south of Italy benefit from a milder climate relative to the United Kingdom and Germany.

CHARACTERISTICS OF NRS SUBJECTS AND RISK FACTORS

Beside the fluctuation in the prevalence of NRS, the profile of individuals with this symptom was fairly consistent in each country. Furthermore, “country effect” was considerably attenuated in the multivariate model. The only significant difference was a protective effect associated with Portugal and Spain.

Interestingly, “quality of the bedroom and the bed” made independent contributions to NRS. Effects of the room temperature on sleep architecture and sleep quality have been studied before. In humans and animals, increased temperature of the sleeping environment (±28°C) increased rapid eye movement sleep,2527 whereas elevated room temperature and high humidity caused more awakenings and lower sleep efficiency28 and room temperature below 28°C increased body movements.29

“Daytime alcohol intake” was not associated with NRS. However, alcohol taken at bedtime increased the likelihood of NRS. Alcohol is often taken as a sleeping aid. Even though alcohol at bedtime accelerates the sleep onset, it also increases the amount of slow-wave sleep, decreases the amount of REM sleep, and causes sleep disruption in the second half of the sleep period.30 It is therefore not so surprising that individuals who were drinking alcohol at bedtime felt unrefreshed on awakening.

Almost all “sleep-wake variables” were associated with NRS in the bivariate analyses. It is interesting to note that early wake-up time was associated with a higher prevalence of NRS. Harmful effects of early rising on sleep and daytime alertness have been previously observed in different working populations.31,32

“ Getting extra sleep on days of rest” was often observed in individuals who accumulated a sleep debt during the week. This was also more frequently observed in young and middle-aged subjects. In all countries, we observed an increase of the nighttime sleep when individuals retire (age between 55 and 65 years). The association with “global sleep dissatisfaction and light to severe regular difficulty getting started in the morning” obtained the highest ORs, indicating a close relationship between NRS, sleep dissatisfaction, and alertness on awakening.

As expected, “mental disorders” were associated with NRS. However, the huge difference between crude and adjusted ORs for each mental disorder indicates that the association between mental disorders and NRS can be explained in large part by other factors.

We also observed a linear increase in the prevalence of NRS with the number of “medical consultations” in the previous year. However, it should be underlined that this increase might be the result of other factors such as a physical illness or a mental disorder. This would explain why, in the multivariate model, only the categories 3 to 5 and 6 to 10 consultations were significantly associated with NRS.

It is noteworthy that NRS was associated more often with “daytime sleepiness and other daytime consequences” than were the other insomnia symptoms (difficulty initiating or maintaining sleep). Each consequence was reported at least twice as frequently by NRS subjects than by other subjects with insomnia symptoms

LIMITATIONS OF THE STUDY

The question of the reliability of sleep data collected by telephone in the population could be raised. Previous studies using this method for data collection indicate that, in general, telephone interviews are satisfactory, have good interrater reliability, and have provided comparable results with that of other interview techniques.33,34

Another limitation is that my colleagues and I did not have objective data on disturbed sleep. Our study, like most of community-based, epidemiological studies relies on self-reports and interview-based measures. Also, many sleep disorder diagnoses generally do not require polysomnographic recordings to be confirmed.

There was also a portion of the population that was impossible to reach because they were either homeless or without a telephone at home. According to the International Telecommunication Union,35 the proportion of households with a telephone varied between 91.5% (Germany) and 99% (Spain).

Nonrestorative sleep is a symptom that must be taken seriously. It is more likely to affect the active classes of the population (individuals younger than 55 years) and is also associated with excessive daytime sleepiness (a third of NRS subjects reported having average to severe daytime sleepiness compared with one tenth for other subjects with insomnia), mood swings, and cognitive impairments. Therefore, the societal costs are important in terms of decreased productivity and diminished quality of life. Nonrestorative sleep also puts these individuals at greater risk for work-related accidents or injuries.

Correspondence: Maurice M. Ohayon, MD, DSc, PhD, Stanford Sleep Epidemiology Research Center, Stanford University School of Medicine, 3430 W Bayshore Rd, Suite 102, Palo Alto, CA 94303 (mohayon@stanford.edu).

Accepted for Publication: September 9, 2004.

Financial Disclosure: Dr Ohayon has received grant support from Sanofi-Synthelabo and Pfizer.

Funding/Support: This research was supported by grant 971067 from the Fond de la Recherche en Santé du Québec and by an unrestricted grant from Pfizer and Sanofi-Synthelabo Group.

Ohayon  MM Epidemiology of insomnia: what we know and what we still need to learn. Sleep Med Rev 2002;697- 111
PubMed
Ancoli-Israel  SRoth  T Characteristics of insomnia in the United States: results of the 1991 National Sleep Foundation Survey, I. Sleep 1999;22 ((suppl 2)) S347- S353
PubMed
Mellinger  GDBalter  MBUhlenhuth  EH Insomnia and its treatment: prevalence and correlates. Arch Gen Psychiatry 1985;42225- 232
PubMed
Olson  LG A community survey of insomnia in Newcastle. Aust N Z J Public Health 1996;20655- 657
PubMed
Hetta  JBroman  JEMallon  L Evaluation of severe insomnia in the general population-implications for the management of insomnia: insomnia, quality of life and healthcare consumption in Sweden. J Psychopharmacol 1999;13 ((suppl 1)) S35- S36
PubMed
Hoffmann  G Evaluation of severe insomnia in the general population–implications for the management of insomnia: focus on results from Belgium. J Psychopharmacol 1999;13 ((suppl 1)) S31- S32
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition.  Washington, DC American Psychiatric Association1987;
Ohayon  MMRoth  T What are the contributing factors for insomnia in the general population? J Psychosom Res 2001;51745- 755
PubMed
Ohayon  MMHong  SC Prevalence of insomnia and associated factors in South Korea. J Psychosom Res 2002;53593- 600
PubMed
Ohayon  MMCaulet  MGuilleminault  C Complaints about nocturnal sleep: how a general population perceives its sleep, and how this relates to the complaint of insomnia. Sleep 1997;20715- 723
PubMed
Leineweber  CKecklund  GJanszky  IAkerstedt  TOrth-Gomer  K Poor sleep increases the prospective risk for recurrent events in middle-aged women with coronary disease: the Stockholm Female Coronary Risk Study. J Psychosom Res 2003;54121- 127
PubMed
Resta  OFoschino Barbaro  MPBonfitto  P  et al.  Low sleep quality and daytime sleepiness in obese patients without obstructive sleep apnoea syndrome. J Intern Med 2003;253536- 543
PubMed
Moldofsky  H Fibromyalgia, sleep disorder and chronic fatigue syndrome. Ciba Found Symp 1993;173262- 271
PubMed
Mendelson  WB The relationship of sleepiness and blood pressure to respiratory variables in obstructive sleep apnea. Chest 1995;108966- 972
PubMed
Montplaisir  JBoucher  SGosselin  APoirier  GLavigne  G Persistence of repetitive EEG arousals (K-alpha complexes) in RLS patients treated with L-DOPA. Sleep 1996;19196- 199
PubMed
Kish  L Survey Sampling.  New York, NY John Wiley & Sons Inc1965;
Ohayon  MM Sleep-EVAL, Knowledge Based System for the Diagnosis of Sleep and Mental Disorders, Copyright Office, Canadian Intellectual Property Office [English, Finnish, French, German, Italian, Portuguese, and Spanish versions]. Ottawa, Ontario: Industry Canada; 1994
Ohayon  MM Improving decision making processes with the fuzzy logic approach in the epidemiology of sleep disorders. J Psychosom Res 1999;47297- 311
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition.  Washington, DC American Psychiatric Association1994;
 American Sleep Disorders Association.  International Classification of Sleep Disorders: Diagnostic and Coding Manual Rochester, Minn American Sleep Disorders Association1990;(revised in 1997)
Lewis  GPelosi  AJAraya  RDunn  G Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol Med 1992;22465- 486
PubMed
Ohayon  MMGuilleminault  CZulley  J  et al.  Validation of the Sleep-EVAL system against clinical assessments of sleep disorders and polysomnographic data. Sleep 1999;22925- 930
PubMed
Hosn  RShapiro  CMOhayon  MM Diagnostic concordance between sleep specialists and the sleep-EVAL system in routine clinical evaluations [abstract]. J Sleep Res 2000;9 ((suppl 1)) 86
Ohayon  M Petites Manies et grandes tendances. La Recherche 2000; ((Hors série No. 3)) 66- 69
Rosenthal  MSVogel  GW The effect of a 3-day increase of ambient temperature toward the thermoneutral zone on rapid eye movement sleep in the rat. Sleep 1993;16702- 705
PubMed
Dewasmes  GTelliez  FMuzet  A Effects of a nocturnal environment perceived as warm on subsequent daytime sleep in humans. Sleep 2000;23409- 413
PubMed
Franco  PScaillet  SValente  FChabanski  SGroswasser  JKahn  A Ambient temperature is associated with changes in infants' arousability from sleep. Sleep 2001;24325- 329
PubMed
Okamoto-Mizuno  KMizuno  KMichie  SMaeda  AIizuka  S Effects of humid heat exposure on human sleep stages and body temperature. Sleep 1999;22767- 773
PubMed
Ohnaka  TTochihara  YKanda  K Body movements of the elderly during sleep and thermal conditions in bedrooms in summer. Appl Human Sci 1995;1489- 93
PubMed
MacLean  AWCairns  J Dose-response effects of ethanol on young men. J Stud Alcohol 1982;43434- 444
PubMed
Kecklund  GAkerstedt  TLowden  A Morning work: effects of early rising on sleep and alertness. Sleep 1997;20215- 223
PubMed
Ohayon  MMLemoine  PArnaud-Briand  VDreyfus  M Prevalence and consequences of sleep disorders in a shift worker population. J Psychosom Res 2002;53577- 583
PubMed
Rohde  PLewinsohn  PMSeeley  JR Comparability of telephone and face-to-face interviews in assessing axis I and II disorders. Am J Psychiatry 1997;1541593- 1598
PubMed
Slutske  WSTrue  WRScherrer  JF  et al.  Long-term reliability and validity of alcoholism diagnoses and symptoms in a large national telephone interview survey. Alcohol Clin Exp Res 1998;22553- 558
PubMed
International Telecommunication Union, Yearbook of Statistics: Telecommunication Services 1991-2000.  Geneva, Switzerland International Telecommunication Union2001;

Figures

Tables

Table Graphic Jump LocationTable 1. Prevalence of NRS by Subject Demographics
Table Graphic Jump LocationTable 2. Prevalence of NRS and Associated Factors in Logistic Regression
Table Graphic Jump LocationTable 3. Daytime Functioning in NRS and Other Subjects With Insomnia

References

Ohayon  MM Epidemiology of insomnia: what we know and what we still need to learn. Sleep Med Rev 2002;697- 111
PubMed
Ancoli-Israel  SRoth  T Characteristics of insomnia in the United States: results of the 1991 National Sleep Foundation Survey, I. Sleep 1999;22 ((suppl 2)) S347- S353
PubMed
Mellinger  GDBalter  MBUhlenhuth  EH Insomnia and its treatment: prevalence and correlates. Arch Gen Psychiatry 1985;42225- 232
PubMed
Olson  LG A community survey of insomnia in Newcastle. Aust N Z J Public Health 1996;20655- 657
PubMed
Hetta  JBroman  JEMallon  L Evaluation of severe insomnia in the general population-implications for the management of insomnia: insomnia, quality of life and healthcare consumption in Sweden. J Psychopharmacol 1999;13 ((suppl 1)) S35- S36
PubMed
Hoffmann  G Evaluation of severe insomnia in the general population–implications for the management of insomnia: focus on results from Belgium. J Psychopharmacol 1999;13 ((suppl 1)) S31- S32
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition.  Washington, DC American Psychiatric Association1987;
Ohayon  MMRoth  T What are the contributing factors for insomnia in the general population? J Psychosom Res 2001;51745- 755
PubMed
Ohayon  MMHong  SC Prevalence of insomnia and associated factors in South Korea. J Psychosom Res 2002;53593- 600
PubMed
Ohayon  MMCaulet  MGuilleminault  C Complaints about nocturnal sleep: how a general population perceives its sleep, and how this relates to the complaint of insomnia. Sleep 1997;20715- 723
PubMed
Leineweber  CKecklund  GJanszky  IAkerstedt  TOrth-Gomer  K Poor sleep increases the prospective risk for recurrent events in middle-aged women with coronary disease: the Stockholm Female Coronary Risk Study. J Psychosom Res 2003;54121- 127
PubMed
Resta  OFoschino Barbaro  MPBonfitto  P  et al.  Low sleep quality and daytime sleepiness in obese patients without obstructive sleep apnoea syndrome. J Intern Med 2003;253536- 543
PubMed
Moldofsky  H Fibromyalgia, sleep disorder and chronic fatigue syndrome. Ciba Found Symp 1993;173262- 271
PubMed
Mendelson  WB The relationship of sleepiness and blood pressure to respiratory variables in obstructive sleep apnea. Chest 1995;108966- 972
PubMed
Montplaisir  JBoucher  SGosselin  APoirier  GLavigne  G Persistence of repetitive EEG arousals (K-alpha complexes) in RLS patients treated with L-DOPA. Sleep 1996;19196- 199
PubMed
Kish  L Survey Sampling.  New York, NY John Wiley & Sons Inc1965;
Ohayon  MM Sleep-EVAL, Knowledge Based System for the Diagnosis of Sleep and Mental Disorders, Copyright Office, Canadian Intellectual Property Office [English, Finnish, French, German, Italian, Portuguese, and Spanish versions]. Ottawa, Ontario: Industry Canada; 1994
Ohayon  MM Improving decision making processes with the fuzzy logic approach in the epidemiology of sleep disorders. J Psychosom Res 1999;47297- 311
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition.  Washington, DC American Psychiatric Association1994;
 American Sleep Disorders Association.  International Classification of Sleep Disorders: Diagnostic and Coding Manual Rochester, Minn American Sleep Disorders Association1990;(revised in 1997)
Lewis  GPelosi  AJAraya  RDunn  G Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol Med 1992;22465- 486
PubMed
Ohayon  MMGuilleminault  CZulley  J  et al.  Validation of the Sleep-EVAL system against clinical assessments of sleep disorders and polysomnographic data. Sleep 1999;22925- 930
PubMed
Hosn  RShapiro  CMOhayon  MM Diagnostic concordance between sleep specialists and the sleep-EVAL system in routine clinical evaluations [abstract]. J Sleep Res 2000;9 ((suppl 1)) 86
Ohayon  M Petites Manies et grandes tendances. La Recherche 2000; ((Hors série No. 3)) 66- 69
Rosenthal  MSVogel  GW The effect of a 3-day increase of ambient temperature toward the thermoneutral zone on rapid eye movement sleep in the rat. Sleep 1993;16702- 705
PubMed
Dewasmes  GTelliez  FMuzet  A Effects of a nocturnal environment perceived as warm on subsequent daytime sleep in humans. Sleep 2000;23409- 413
PubMed
Franco  PScaillet  SValente  FChabanski  SGroswasser  JKahn  A Ambient temperature is associated with changes in infants' arousability from sleep. Sleep 2001;24325- 329
PubMed
Okamoto-Mizuno  KMizuno  KMichie  SMaeda  AIizuka  S Effects of humid heat exposure on human sleep stages and body temperature. Sleep 1999;22767- 773
PubMed
Ohnaka  TTochihara  YKanda  K Body movements of the elderly during sleep and thermal conditions in bedrooms in summer. Appl Human Sci 1995;1489- 93
PubMed
MacLean  AWCairns  J Dose-response effects of ethanol on young men. J Stud Alcohol 1982;43434- 444
PubMed
Kecklund  GAkerstedt  TLowden  A Morning work: effects of early rising on sleep and alertness. Sleep 1997;20215- 223
PubMed
Ohayon  MMLemoine  PArnaud-Briand  VDreyfus  M Prevalence and consequences of sleep disorders in a shift worker population. J Psychosom Res 2002;53577- 583
PubMed
Rohde  PLewinsohn  PMSeeley  JR Comparability of telephone and face-to-face interviews in assessing axis I and II disorders. Am J Psychiatry 1997;1541593- 1598
PubMed
Slutske  WSTrue  WRScherrer  JF  et al.  Long-term reliability and validity of alcoholism diagnoses and symptoms in a large national telephone interview survey. Alcohol Clin Exp Res 1998;22553- 558
PubMed
International Telecommunication Union, Yearbook of Statistics: Telecommunication Services 1991-2000.  Geneva, Switzerland International Telecommunication Union2001;

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