title: The impact of psychiatric disorders on work loss days.
abstract: BACKGROUND
  To examine relationships between recent DSM-III-R psychiatric disorders and work impairment in major occupational groups in the US labour force.
  
  
  METHODS
  Data are from the US National Comorbidity Survey (NCS), a survey of respondents ages 15-54 in the US. Employed people are the focus of the report.
  
  
  RESULTS
  There is substantial variation across occupations in the 30-day prevalences of NCS/ DSM-III-R psychiatric disorders, with an average prevalence of 18.2% (range: 11.0-29.6%) for any disorder. The average prevalences of psychiatric work loss days (6 days per month per 100 workers) and work cutback days (31 days per month per 100 workers), in comparison, do not differ significantly across occupations. Work impairment is more strongly concentrated among the 3.7% of the workforce with co-morbid psychiatric disorders (49 work loss days and 346 work cutback days per month per 100 workers) than the 14.5% with pure disorders (11 work loss days and 66 work cutback days per month per 100 workers) or the 81.8% with no disorder (2 work loss days and 11 work cutback days per month per 100 workers). The effects of psychiatric disorders on work loss are similar across all occupations, while effects on work cutback are greater among professional workers than those in other occupations.
  
  
  CONCLUSIONS
  The results reported here suggest that work impairment is one of the adverse consequences of psychiatric disorders. The current policy debate concerning insurance coverage for mental disorders needs to take these consequences into consideration.
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, MA 02115, USA.
authors.forename: R C
authors.initials: RC
authors.lastname: Kessler
authors.forename: R G
authors.initials: RG
authors.lastname: Frank
mesh_terms: D000041:Absenteeism; D000293:Adolescent; D000328:Adult; D016000:Cluster Analysis; D015897:Comorbidity; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D004526:Efficiency; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000145:classification / Q000453:epidemiology*; D008875:Middle Aged; D015999:Multivariate Analysis; D009790:Occupations / Q000145:classification / Q000706:statistics & numerical data; D015995:Prevalence; D012044:Regression Analysis; D012494:Sampling Studies; D014481:United States / Q000453:epidemiology; D014937:Work / Q000523:psychology / Q000706:statistics & numerical data