title: If smoking increases absences, does quitting reduce them?
abstract: OBJECTIVE
  This study examined the impact of smoking, quitting, and time since quit on absences from work.
  
  
  METHODS
  Data from the nationally representative Tobacco Use Supplements of the 1992/93, 1995/96, and 1998/99 Current Population Surveys were used. The study included full time workers aged between 18-64 years, yielding a sample size of 383 778 workers. A binary indicator of absence due to sickness in the last week was analysed as a function of smoking status including time since quit for former smokers. Extensive demographic variables were included as controls in all models.
  
  
  RESULTS
  In initial comparisons between current and former smokers, smoking increased absences, but quitting did not reduce them. However, when length of time since quit was examined, it was discovered that those who quit within the last year, and especially the last three months, had a much greater probability of absences than did current smokers. As the time since quitting increased, absences returned to a rate somewhere between that of never and current smokers. Interactions between health and smoking status significantly improved the fit of the model.
  
  
  CONCLUSIONS
  Smokers who quit reduced their absences over time but increase their absences immediately after quitting. Quitting ill may account for some but not all of this short run impact.
authors.affiliation: Department of Epidemiology and Public Health, Yale University, New Haven, Connecticut, USA.
authors.forename: J L
authors.initials: JL
authors.lastname: Sindelar
authors.forename: N
authors.initials: N
authors.lastname: Duchovny
authors.forename: T A
authors.initials: TA
authors.lastname: Falba
authors.forename: S H
authors.initials: SH
authors.lastname: Busch
mesh_terms: D000041:Absenteeism; D000293:Adolescent; D000328:Adult; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011159:Population Surveillance / Q000379:methods; D012044:Regression Analysis; D012907:Smoking / Q000453:epidemiology* / Q000523:psychology; D016540:Smoking Cessation / Q000523:psychology / Q000706:statistics & numerical data*; D013997:Time Factors; D014481:United States / Q000453:epidemiology