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The contribution of educational class in improving accuracy of cardiovascular risk prediction across European regions: The MORGAM Project Cohort Component
  1. Marco M Ferrario1,
  2. Giovanni Veronesi1,
  3. Lloyd E Chambless2,
  4. Hugh Tunstall-Pedoe3,
  5. Kari Kuulasmaa4,
  6. Veikko Salomaa4,
  7. Anders Borglykke5,
  8. Nigel Hart6,
  9. Stefan Söderberg7,
  10. Giancarlo Cesana8,
  11. for the MORGAM Project
  1. 1Dipartimento di Medicina Clinica e Sperimentale, Centro Ricerche EPIMED—Epidemiologia e Medicina Preventiva, Università degli Studi dell'Insubria, Varese, Italy
  2. 2Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
  3. 3Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, Dundee, UK
  4. 4Department of Chronic Disease Prevention, THL-National Institute for Health and Welfare, Helsinki, Finland
  5. 5Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
  6. 6Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
  7. 7Department of Public Health and Clinical Medicine, Cardiology and Heart Centre, Umeå University, Umeå, Sweden
  8. 8Centro Studi e Ricerche in Sanità Pubblica (CESP), Università degli Studi di Milano-Bicocca, Monza, Italy
  1. Correspondence to Professor Marco M Ferrario, Centro Ricerche EPIMED, Dipartimento di Medicina Clinica e Sperimentale, Università degli studi dell'Insubria, Via O. Rossi, Varese 9-21100, Italy; marco.ferrario{at}


Objective To assess whether educational class, an index of socioeconomic position, improves the accuracy of the SCORE cardiovascular disease (CVD) risk prediction equation.

Methods In a pooled analysis of 68 455 40–64-year-old men and women, free from coronary heart disease at baseline, from 47 prospective population-based cohorts from Nordic countries (Finland, Denmark, Sweden), the UK (Northern Ireland, Scotland), Central Europe (France, Germany, Italy) and Eastern Europe (Lithuania, Poland) and Russia, we assessed improvements in discrimination and in risk classification (net reclassification improvement (NRI)) when education was added to models including the SCORE risk equation.

Results The lowest educational class was associated with higher CVD mortality in men (pooled age-adjusted HR=1.64, 95% CI 1.42 to 1.90) and women (HR=1.31, 1.02 to 1.68). In men, the HRs ranged from 1.3 (Central Europe) to 2.1 (Eastern Europe and Russia). After adjustment for the SCORE risk, the association remained statistically significant overall, in the UK and Eastern Europe and Russia. Education significantly improved discrimination in all European regions and classification in Nordic countries (clinical NRI=5.3%) and in Eastern Europe and Russia (NRI=24.7%). In women, after SCORE risk adjustment, the association was not statistically significant, but the reduced number of deaths plays a major role, and the addition of education led to improvements in discrimination and classification in the Nordic countries only.

Conclusions We recommend the inclusion of education in SCORE CVD risk equation in men, particularly in Nordic and East European countries, to improve social equity in primary prevention. Weaker evidence for women warrants the need for further investigations.

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