title: Costs differences across demographic groups and types of occupational injuries and illnesses.
abstract: BACKGROUND
  Little is known about cost differences for demographic groups or across occupational injuries and illnesses.
  
  
  METHODS
  In this incidence study of nationwide data for 1993, an analysis was conducted on fatal and non-fatal injury and illness data recorded in government data sets. Costs data were from workers' compensation records, estimates of lost wages, and jury awards.
  
  
  RESULTS
  The youngest (age < or = 17) and oldest (age > or = 65) workers had exceptionally high fatality costs. Whereas men's costs for non-fatal incidents were nearly double those for women, men's costs for fatal injuries were 10 times the costs for women. The highest ranking occupation for combined fatal and non-fatal costs--farming, forestry, and fishing--had costs-per-worker (5,163 US dollars) over 18 times the lowest ranking occupation-executives and managers (279 US dollars). The occupation of handlers, cleaners, and laborers, ranked highest for non-fatal costs. Gunshot wounds generated especially high fatal costs. Compared to whites, African-Americans had a lower percentage of costs due to carpal tunnel syndrome, circulatory, and digestive diseases.
  
  
  CONCLUSIONS
  Costs comparisons can be drawn across age, race, gender, and occupational groups as well as categories of injuries and illnesses.
authors.affiliation: Center for Health Services Research in Primary Care and Department of Public Health Sciences, University of California, Davis, California 95817, USA. pleigh@ucdavis.edu
authors.forename: J Paul
authors.initials: JP
authors.lastname: Leigh
authors.forename: Geetha
authors.initials: G
authors.lastname: Waehrer
authors.forename: Ted R
authors.initials: TR
authors.lastname: Miller
authors.forename: Stephen A
authors.initials: SA
authors.lastname: McCurdy
mesh_terms: D000288:Administrative Personnel / Q000191:economics; D000293:Adolescent; D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000367:Age Factors; D000368:Aged; D000383:Agriculture / Q000191:economics; D002423:Cause of Death; D003365:Costs and Cost Analysis / Q000706:statistics & numerical data; D005260:Female; D005398:Fisheries / Q000191:economics; D016468:Forestry / Q000191:economics; D006801:Humans; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000191:economics* / Q000453:epidemiology; D012456:Salaries and Fringe Benefits / Q000706:statistics & numerical data; D012737:Sex Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data; D014942:Workers' Compensation / Q000191:economics / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000191:economics* / Q000453:epidemiology; D014948:Wounds, Gunshot / Q000191:economics / Q000453:epidemiology