title: Predictors of sickness absence in college and university educated self-employed: a historic register study.
abstract: BACKGROUND
  Despite a large proportion of the workforce being self-employed, few studies have been conducted on risk factors for sickness absence in this population. The aim of this study is to identify risk factors for future sickness absence in a population of college and university educated self-employed.
  
  
  METHODS
  In a historic register study based on insurance company files risk factors were identified by means of logistic regression analysis. Data collected at application for private disability insurance from 634 applicants were related to subsequent sickness absence periods of 30 days or more during a follow-up period of 7.95 years. Variables studied were self-reported lifestyle variables, variables concerning medical history and present health conditions and variables derived from the general medical examination including blood tests and urinary analysis.
  
  
  RESULTS
  Results from analysis of data from 634 applicants for private disability insurance show that previous periods of sickness absence (OR 2.07), female gender (OR 2.04), health complaints listed in the health declaration (OR 1.88), elevated erythrocyte sedimentation rate (ESR) (OR 4.05) and the nature of the profession were related to a higher risk of sickness absence.
  
  
  CONCLUSIONS
  Sickness absence was found to be related to demographic variables (gender, profession), medical variables (health complaints and erythrocyte sedimentation rate) and to variables with both a medical and a behavioural component (previous sickness absence).
authors.affiliation: Department of Health Sciences, Community and Occupational Medicine, University Medical Center Groningen, University of Groningen, 1, 9713 AV, Groningen, The Netherlands. e.c.wijnvoord@umcg.nl.
authors.forename: Liesbeth E C
authors.initials: LE
authors.lastname: Wijnvoord
authors.forename: Jac J L
authors.initials: JJ
authors.lastname: Van der Klink
authors.forename: Michiel R
authors.initials: MR
authors.lastname: De Boer
authors.forename: Sandra
authors.initials: S
authors.lastname: Brouwer
mesh_terms: D000328:Adult; D000368:Aged; D001799:Blood Sedimentation; D006233:Persons with Disabilities / Q000706:statistics & numerical data; D004522:Educational Status; D004651:Employment; D005260:Female; D005544:Forecasting; D006262:Health; D006801:Humans; D018868:Insurance, Disability; D008019:Life Style; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009790:Occupations; D016017:Odds Ratio; D012307:Risk Factors; D012737:Sex Factors; D018582:Sick Leave / Q000706:statistics & numerical data; D014495:Universities; D055815:Young Adult