title: Epidemiological and clinical relevance of insomnia diagnosis algorithms according to the DSM-IV and the International Classification of Sleep Disorders (ICSD).
abstract: BACKGROUND
  Although the epidemiology of insomnia in the general population has received considerable attention in the past 20 years, few studies have investigated the prevalence of insomnia using operational definitions such as those set forth in the ICSD and DSM-IV, specifying what proportion of respondents satisfied the criteria to reach a diagnosis of insomnia disorder.
  
  
  METHODS
  This is a cross-sectional study involving 25,579 individuals aged 15 years and over representative of the general population of France, the United Kingdom, Germany, Italy, Portugal, Spain and Finland. The participants were interviewed on sleep habits and disorders managed by the Sleep-EVAL expert system using DSM-IV and ICSD classifications.
  
  
  RESULTS
  At the complaint level, too short sleep (20.2%), light sleep (16.6%), and global sleep dissatisfaction (8.2%) were reported by 37% of the subjects. At the symptom level (difficulty initiating or maintaining sleep and non-restorative sleep at least 3 nights per week), 34.5% of the sample reported at least one of them. At the criterion level, (symptoms+daytime consequences), 9.8% of the total sample reported having them. At the diagnostic level, 6.6% satisfied the DSM-IV requirement for positive and differential diagnosis. However, many respondents failed to meet diagnostic criteria for duration, frequency and severity in the two classifications, suggesting that multidimensional measures are needed.
  
  
  CONCLUSIONS
  A significant proportion of the population with sleep complaints do not fit into DSM-IV and ICSD classifications. Further efforts are needed to identify diagnostic criteria and dimensional measures that will lead to insomnia diagnoses and thus provide a more reliable, valid and clinically relevant classification.
authors.affiliation: Stanford Sleep Epidemiology Research Center, Stanford University School of Medicine, CA 94303, USA. mohayon@stanford.edu
authors.forename: Maurice M
authors.initials: MM
authors.lastname: Ohayon
authors.forename: Charles F
authors.initials: CF
authors.lastname: Reynolds
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D003430:Cross-Sectional Studies; D003663:Decision Trees; D003937:Diagnosis, Differential; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005060:Europe / Q000453:epidemiology; D005260:Female; D006306:Health Surveys; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015995:Prevalence; D012720:Severity of Illness Index; D007319:Sleep Initiation and Maintenance Disorders / Q000150:complications / Q000175:diagnosis* / Q000453:epidemiology*; D055815:Young Adult