title: Sick leaves in four factories--do characteristics of employees and work conditions explain differences in sickness absence between workplaces?
abstract: OBJECTIVE
  The study explored whether differences in sickness absence between four factories of a food industry company were explained by common determinants of sickness absence, such as employee health, sociodemographic characteristics, and physical and psychosocial work conditions.
  
  
  METHODS
  Survey responses of 582 employees were linked to the records of short-term (1-3 days) and long-term (>3 days) absence, as well as to records of absences due to musculoskeletal diagnoses. Multilevel models were applied in assessing the between-factory absence differences.
  
  
  RESULTS
  Compared with the levels in the factory with the lowest sickness absence, in one factory the levels of short-term [rate ratio (RR) 1.72], long-term (RR 1.96), and musculoskeletal (rate ratio 2.93) absence were significantly higher. Another factory also had higher levels of long-term and musculoskeletal absence (RR 2.17 and 2.52, respectively). Adjustment for the background factors explained 35% of the difference in short-term absence, 3-9% of the differences in long-term absence, and 18-12% of the differences in musculoskeletal absence, but the between-factory differences were still highly significant.
  
  
  CONCLUSIONS
  This study showed large differences in sickness absence between factories that were only partly explained by common determinants. Moreover, economic factors and formal control were unlikely explanatory factors, as the study was conducted within a single company. These results justify further research on local absence practices and cultures, including those of health service organizations and professionals.
authors.affiliation: Tampere School of Public Health, University of Tampere, Finland. pekka.j.virtanen@uta.fi
authors.forename: Pekka
authors.initials: P
authors.lastname: Virtanen
authors.forename: Anna
authors.initials: A
authors.lastname: Siukola
authors.forename: Tiina
authors.initials: T
authors.lastname: Luukkaala
authors.forename: Minna
authors.initials: M
authors.lastname: Savinainen
authors.forename: Heikki
authors.initials: H
authors.lastname: Arola
authors.forename: Clas-Håkan
authors.initials: CH
authors.lastname: Nygård
authors.forename: Mika
authors.initials: M
authors.lastname: Kivimäki
authors.forename: Hans
authors.initials: H
authors.lastname: Helenius
authors.forename: Jussi
authors.initials: J
authors.lastname: Vahtera
mesh_terms: D000328:Adult; D005260:Female; D005387:Finland / Q000453:epidemiology; D005525:Food-Processing Industry; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009140:Musculoskeletal Diseases / Q000453:epidemiology / Q000517:prevention & control; D009784:Occupational Diseases / Q000453:epidemiology / Q000517:prevention & control*; D012307:Risk Factors; D018582:Sick Leave / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D017132:Workplace