Kaveh Hajifathalian1, Peter Ueda2, Yuan Lu2, Mark Woodward3, Alireza Ahmadvand4, Carlos A Aguilar-Salinas5, Fereidoun Azizi6, Renata Cifkova7, Mariachiara Di Cesare8, Louise Eriksen9, Farshad Farzadfar10, Nayu Ikeda11, Davood Khalili6, Young-Ho Khang12, Vera Lanska13, Luz León-Muñoz14, Dianna Magliano15, Kelias P Msyamboza16, Kyungwon Oh17, Fernando Rodríguez-Artalejo14, Rosalba Rojas-Martinez18, Jonathan E Shaw15, Gretchen A Stevens19, Janne Tolstrup7, Bin Zhou8, Joshua A Salomon2, Majid Ezzati8, Goodarz Danaei20. 1. Department of Global Health and Population, Harvard School of Public Health, Boston, MA, USA; Department of Internal Medicine, Cleveland Clinic, Cleveland, OH, USA. 2. Department of Global Health and Population, Harvard School of Public Health, Boston, MA, USA. 3. The George Institute for Global Health, Nuffield Department of Population Health, University of Oxford, Oxford, UK; The George Institute for Global Health, University of Sydney, Sydney, NSW, Australia; Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA. 4. MRC-PHE Centre for Environment and Health, Imperial College London, London, UK; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 5. Department of Endocrinology and Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición, Salvador Zubirán, Mexico City, Mexico. 6. Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 7. Department of Preventive Cardiology, Thomayer Teaching Hospital, Prague, Czech Republic. 8. MRC-PHE Centre for Environment and Health, Imperial College London, London, UK; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. 9. National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark. 10. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 11. Center for International Collaboration and Partnership, National Institute of Health and Nutrition, Tokyo, Japan. 12. Institute of Health Policy and Management, Seoul National University College of Medicine, Seoul, South Korea. 13. Statistical Unit, Institute for Clinical and Experimental Medicine, Prague, Czech Republic. 14. Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/Idipaz, Madrid, Spain; CIBER of Epidemiology and Public Health, Madrid, Spain. 15. Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia. 16. WHO, Malawi Country Office, Lilongwe, Malawi. 17. Division of Health and Nutrition Survey, Korea Centers for Disease Control and Prevention, Cheongwon-gun, South Korea. 18. Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico. 19. Department of Health Statistics and Information Systems, WHO, Geneva, Switzerland. 20. Department of Global Health and Population, Harvard School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. Electronic address: gdanaei@hsph.harvard.edu.
Abstract
BACKGROUND: Treatment of cardiovascular risk factors based on disease risk depends on valid risk prediction equations. We aimed to develop, and apply in example countries, a risk prediction equation for cardiovascular disease (consisting here of coronary heart disease and stroke) that can be recalibrated and updated for application in different countries with routinely available information. METHODS: We used data from eight prospective cohort studies to estimate coefficients of the risk equation with proportional hazard regressions. The risk prediction equation included smoking, blood pressure, diabetes, and total cholesterol, and allowed the effects of sex and age on cardiovascular disease to vary between cohorts or countries. We developed risk equations for fatal cardiovascular disease and for fatal plus non-fatal cardiovascular disease. We validated the risk equations internally and also using data from three cohorts that were not used to create the equations. We then used the risk prediction equation and data from recent (2006 or later) national health surveys to estimate the proportion of the population at different levels of cardiovascular disease risk in 11 countries from different world regions (China, Czech Republic, Denmark, England, Iran, Japan, Malawi, Mexico, South Korea, Spain, and USA). FINDINGS: The risk score discriminated well in internal and external validations, with C statistics generally 70% or more. At any age and risk factor level, the estimated 10 year fatal cardiovascular disease risk varied substantially between countries. The prevalence of people at high risk of fatal cardiovascular disease was lowest in South Korea, Spain, and Denmark, where only 5-10% of men and women had more than a 10% risk, and 62-77% of men and 79-82% of women had less than a 3% risk. Conversely, the proportion of people at high risk of fatal cardiovascular disease was largest in China and Mexico. In China, 33% of men and 28% of women had a 10-year risk of fatal cardiovascular disease of 10% or more, whereas in Mexico, the prevalence of this high risk was 16% for men and 11% for women. The prevalence of less than a 3% risk was 37% for men and 42% for women in China, and 55% for men and 69% for women in Mexico. INTERPRETATION: We developed a cardiovascular disease risk equation that can be recalibrated for application in different countries with routinely available information. The estimated percentage of people at high risk of fatal cardiovascular disease was higher in low-income and middle-income countries than in high-income countries. FUNDING: US National Institutes of Health, UK Medical Research Council, Wellcome Trust.
BACKGROUND: Treatment of cardiovascular risk factors based on disease risk depends on valid risk prediction equations. We aimed to develop, and apply in example countries, a risk prediction equation for cardiovascular disease (consisting here of coronary heart disease and stroke) that can be recalibrated and updated for application in different countries with routinely available information. METHODS: We used data from eight prospective cohort studies to estimate coefficients of the risk equation with proportional hazard regressions. The risk prediction equation included smoking, blood pressure, diabetes, and total cholesterol, and allowed the effects of sex and age on cardiovascular disease to vary between cohorts or countries. We developed risk equations for fatal cardiovascular disease and for fatal plus non-fatal cardiovascular disease. We validated the risk equations internally and also using data from three cohorts that were not used to create the equations. We then used the risk prediction equation and data from recent (2006 or later) national health surveys to estimate the proportion of the population at different levels of cardiovascular disease risk in 11 countries from different world regions (China, Czech Republic, Denmark, England, Iran, Japan, Malawi, Mexico, South Korea, Spain, and USA). FINDINGS: The risk score discriminated well in internal and external validations, with C statistics generally 70% or more. At any age and risk factor level, the estimated 10 year fatal cardiovascular disease risk varied substantially between countries. The prevalence of people at high risk of fatal cardiovascular disease was lowest in South Korea, Spain, and Denmark, where only 5-10% of men and women had more than a 10% risk, and 62-77% of men and 79-82% of women had less than a 3% risk. Conversely, the proportion of people at high risk of fatal cardiovascular disease was largest in China and Mexico. In China, 33% of men and 28% of women had a 10-year risk of fatal cardiovascular disease of 10% or more, whereas in Mexico, the prevalence of this high risk was 16% for men and 11% for women. The prevalence of less than a 3% risk was 37% for men and 42% for women in China, and 55% for men and 69% for women in Mexico. INTERPRETATION: We developed a cardiovascular disease risk equation that can be recalibrated for application in different countries with routinely available information. The estimated percentage of people at high risk of fatal cardiovascular disease was higher in low-income and middle-income countries than in high-income countries. FUNDING: US National Institutes of Health, UK Medical Research Council, Wellcome Trust.
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