title: Racial/ethnic and gender differences in individual workplace injury risk trajectories: 1988-1998.
abstract: OBJECTIVE
  I examined workplace injury risk over time and across racial/ethnic and gender groups to observe patterns of change and to understand how occupational characteristics and job mobility influence these changes.
  
  
  METHODS
  I used hierarchical generalized linear models to estimate individual workplace injury and illness risk over time ("trajectories") for a cohort of American workers who participated in the National Longitudinal Survey of Youth (1988-1998).
  
  
  RESULTS
  Significant temporal variation in injury risk was observed across racial/ethnic and gender groups. At baseline, White men had a high risk of injury relative to the other groups and experienced the greatest decline over time. Latino men demonstrated a pattern of lower injury risk across time compared with White men. Among both Latinos and non-Latino Whites, women had lower odds of injury than did men. Non-Latino Black women's injury risk was similar to Black men's and greater than that for both Latino and non-Latino White women. Occupational characteristics and job mobility partly explained these differences.
  
  
  CONCLUSIONS
  Disparities between racial/ethnic and gender groups were dynamic and changed over time. Workplace injury risk was associated with job dimensions such as work schedule, union representation, health insurance, job hours, occupational racial segregation, and occupational environmental hazards.
authors.affiliation: Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, Rockville, MD 20850, USA. terceira.berdahl@ahrq.hhs.gov
authors.forename: Terceira A
authors.initials: TA
authors.lastname: Berdahl
mesh_terms: D000062:Accidents, Occupational / Q000639:trends*; D001741:Black or African American / Q000706:statistics & numerical data*; D005260:Female; D054624:Health Status Disparities; D006306:Health Surveys; D006630:Hispanic or Latino / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D008913:Minority Groups / Q000706:statistics & numerical data; D009790:Occupations / Q000706:statistics & numerical data; D011159:Population Surveillance; D018570:Risk Assessment; D012307:Risk Factors; D017678:Sex Distribution; D011795:Surveys and Questionnaires; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D035862:Vulnerable Populations / Q000706:statistics & numerical data; D044465:White People / Q000706:statistics & numerical data*; D017132:Workplace / Q000706:statistics & numerical data*; D014947:Wounds and Injuries / Q000208:ethnology* / Q000209:etiology