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Cardiovascular disease risk prediction in sub-Saharan African populations - Comparative analysis of risk algorithms

Daniel Boateng1, Charles Agyemang2, Erik Beune2

  • 1Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, The Netherlands; School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

International Journal of Cardiology
|February 7, 2018
PubMed

Insights

Cardiovascular disease risk prediction varies between Ghanaian migrants and those in Ghana. Current risk equations are not interchangeable and require validation for African populations.

Area of Science:

  • Cardiology
  • Public Health
  • Epidemiology

Background:

  • Validated absolute risk equations are standard for cardiovascular disease (CVD) risk stratification.
  • Consensus on appropriate CVD risk equations for Sub-Saharan African populations is lacking.
  • This study assesses agreement between different CVD risk equations in Ghanaian populations.

Purpose of the Study:

  • To evaluate the agreement between Framingham (laboratory and non-laboratory) and Pooled Cohort Equations (PCE) for 10-year CVD risk.
  • To compare risk stratification in Ghanaian migrants versus home populations.
  • To determine the interchangeability of different CVD risk algorithms in this demographic.

Main Methods:

  • Calculated 10-year CVD risks for 3586 Ghanaians (aged 40-70) in Ghana and Europe using Framingham and PCE algorithms.
  • Classified participants into low (<10%), moderate (10-20%), and high (>20%) risk categories.
  • Assessed algorithm agreement using kappa and correlation coefficients.

Main Results:

  • High 10-year CVD risk prevalence varied: 19.4% (Framingham non-lab), 12.3% (Framingham lab), and 5.8% (PCE).
  • Concordance between PCE and Framingham non-lab was higher in Ghana than among migrants.
  • Concordance between PCE and Framingham lab was higher among migrants than in Ghana.

Conclusions:

  • CVD risk prediction differs between Ghanaian migrant and home populations using the same algorithm.
  • Limited interchangeability exists between Framingham laboratory and non-laboratory algorithms.
  • Further validation against actual CVD outcomes is crucial for selecting appropriate risk algorithms for African ancestry populations.
Abstract

Keywords:
Cardiovascular diseaseFraminghamPooled cohort equationPrimary preventionRODAM studyRisk assessmentRisk predictionRisk scoreSub-Saharan Africa

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