Risk factors associated with myocardial infarction in Africa: the INTERHEART Africa study

Krisela Steyn1, Karen Sliwa, Steven Hawken

  • 1Chronic Diseases of Lifestyle Unit, Medical Research Council, Tygerberg, South Africa.

Circulation
|December 7, 2005
PubMed

Insights

Modifiable cardiovascular disease risk factors explain nearly 90% of myocardial infarctions in sub-Saharan Africa. These findings highlight the importance of addressing risk factors like smoking, diabetes, and hypertension to prevent heart attacks in the region.

Area of Science:

  • Cardiology
  • Public Health
  • Epidemiology

Background:

  • Cardiovascular disease (CVD) incidence is increasing in low-income nations.
  • Limited data exists on modifiable CVD risk factors and myocardial infarction (MI) in sub-Saharan Africa (SSA).

Purpose of the Study:

  • To investigate the association between known CVD risk factors and acute myocardial infarction (AMI) in SSA.
  • To compare findings in African populations with the broader INTERHEART study.

Main Methods:

  • A case-control study involving 578 first-time AMI patients and 785 matched controls across 9 SSA countries.
  • Analysis of risk factors including smoking, diabetes, hypertension, abdominal obesity, and apolipoprotein ratios.
  • Comparison of risk factor associations within ethnic subgroups (black, colored, European/other Africans) and against the overall INTERHEART study.

Main Results:

  • Modifiable CVD risk factors showed similar associations with AMI in SSA as in the overall INTERHEART study.
  • Five key risk factors (smoking, diabetes, hypertension, abdominal obesity, ApoB/ApoA1 ratio) accounted for 89.2% of AMI cases.
  • Hypertension history indicated a higher MI risk in black Africans compared to the overall INTERHEART cohort.
  • Higher income and education correlated with increased AMI risk in black Africans, unlike other groups.

Conclusions:

  • Established CVD risk factors are responsible for approximately 90% of MI cases in African populations.
  • Socioeconomic gradients, risk factor profiles, and AMI risk varied across ethnic groups, suggesting different epidemiological transition stages.
Abstract

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