title: Socioeconomic status and the occurrence of fatal and nonfatal injury in the United States.
abstract: OBJECTIVE
  This study examined the contribution of socioeconomic status (SES) to the risk of injury mortality and morbidity among working-age adults.
  
  
  METHODS
  The sample consisted of respondents to the National Health Interview Survey (1987-1994), and separate analyses were conducted for injury deaths to respondents by linking to the National Death Index. Proportional hazards regression models were used to analyze mortality. Logistic regression models were used to analyze morbidity.
  
  
  RESULTS
  The effects of SES varied substantially by cause of injury mortality and indicator of SES. In the multivariate models, blue-collar workers were at significantly increased odds of nonfatal injury. Education was unrelated to total injury morbidity, although associations were observed after stratification of the outcome by severity and place of occurrence. Black persons were at increased risk for homicide, and Black and Hispanic persons were at decreased risk for suicide and nonfatal injuries, after adjustment for SES.
  
  
  CONCLUSIONS
  SES is an important determinant of injury, although the effect depends on the indicator of SES and the cause and severity of injury.
authors.affiliation: Stanford Center for Research in Disease Prevention, Stanford University School of Medicine, Palo Alto, Calif. 94304-1825, USA. ccubbin@leland.stanford.edu
authors.forename: C
authors.initials: C
authors.lastname: Cubbin
authors.forename: F B
authors.initials: FB
authors.lastname: LeClere
authors.forename: G S
authors.initials: GS
authors.lastname: Smith
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data; D000328:Adult; D000367:Age Factors; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D006708:Homicide / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009026:Mortality; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D017678:Sex Distribution; D012959:Socioeconomic Factors; D013405:Suicide / Q000706:statistics & numerical data; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology*