Material and behavioral factors in the explanation of educational differences in incidence of acute myocardial infarction: the Globe study

Ann Epidemiol. 2002 Nov;12(8):535-42. doi: 10.1016/s1047-2797(01)00279-4.


Purpose: To quantify the contribution of material and behavioral factors to educational differences in the incidence of acute myocardial infarction (AMI), taking into account their interrelationship.

Methods: Self-reported information about educational level, behavioral factors (alcohol, smoking, physical inactivity, and obesity), and material factors (housing conditions, crowding, employment status, financial problems, and an income proxy) was obtained from 45 to 74 year old responders to the baseline measurement of the Dutch prospective GLOBE-study in 1991 (n = 9872). Incidence of AMI in study participants was determined by hospital admissions due to AMI between 1991 and 1998.

Results: The increased hazard ratio of AMI in the lowest compared to the highest educational group [hazard ratio (HR) = 1.85, 95% confidence interval (CI): 1.19; 2.88] decreased by 60% after adjustment for all four behavioral factors. Similarly, adjustment for housing conditions, employment status and the income proxy reduced the hazard ratio by 76%. Thirty-six percent of the contribution of behavioral factors to educational differences in AMI in the lowest compared to the highest educational group was the result of more often living in worse material circumstances in the first group.

Conclusions: Material factors contribute more to educational differences in incidence of AMI than behavioral factors. Improving material circumstances in lower educational groups may form an important strategy in the reduction of inequalities in AMI, partly because of its influence on unhealthy behavior.

Publication types

  • Comparative Study

MeSH terms

  • Aged
  • Educational Status*
  • Health Behavior*
  • Humans
  • Incidence
  • Middle Aged
  • Myocardial Infarction / epidemiology*
  • Myocardial Infarction / psychology
  • Netherlands / epidemiology
  • Patient Admission / statistics & numerical data
  • Proportional Hazards Models
  • Risk-Taking
  • Social Class
  • Socioeconomic Factors