Annika Rosengren1, Andrew Smyth2, Sumathy Rangarajan3, Chinthanie Ramasundarahettige3, Shrikant I Bangdiwala3, Khalid F AlHabib4, Alvaro Avezum5, Kristina Bengtsson Boström6, Jephat Chifamba7, Sadi Gulec8, Rajeev Gupta9, Ehi U Igumbor10, Romaina Iqbal11, Norhassim Ismail12, Philip Joseph3, Manmeet Kaur13, Rasha Khatib14, Iolanthé M Kruger15, Pablo Lamelas3, Fernando Lanas16, Scott A Lear17, Wei Li18, Chuangshi Wang18, Deren Quiang19, Yang Wang18, Patricio Lopez-Jaramillo20, Noushin Mohammadifard21, Viswanathan Mohan22, Prem K Mony23, Paul Poirier24, Sarojiniamma Srilatha25, Andrzej Szuba26, Koon Teo3, Andreas Wielgosz27, Karen E Yeates28, Khalid Yusoff29, Rita Yusuf30, Afzalhusein H Yusufali31, Marjan W Attaei3, Martin McKee32, Salim Yusuf3. 1. Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden. Electronic address: annika.rosengren@gu.se. 2. HRB Clinical Research Facility Galway, National University of Ireland, Galway, Ireland. 3. Population Health Research Institute, McMaster University, Hamilton Health Sciences Centre, Hamilton, ON, Canada. 4. Department of Cardiac Sciences, King Fahad Cardiac Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia. 5. Dante Pazzanese Institute of Cardiology and University Santo Amaro, São Paulo, Brazil. 6. R&D Centre Skaraborg Primary Care, Skövde, Sweden. 7. Department of Physiology, University of Zimbabwe College of Health Sciences, Harare, Zimbabwe. 8. Cardiology Department, Ankara University School of Medicine, Ankara, Turkey. 9. Eternal Heart Care Centre and Research Institute, Jaipur, India. 10. School of Public Health, University of the Western Cape, Bellville, South Africa. 11. Department of Community Health Sciences, Aga Khan University, Karachi, Pakistan. 12. Department of Community Health, Faculty of Medicine, University Kebangsaan Malaysia, Kuala Lumpur, Malaysia. 13. School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India. 14. Public Health Sciences, Stritch School of Medicine, Maywood, IL, USA. 15. Africa Unit for Transdisciplinary Health Research, North-West University, Potchefstroom, South Africa. 16. Universidad de La Frontera, Temuco, Chile. 17. Faculty of Health Sciences, Simon Fraser University, Vancouver, BC, Canada. 18. State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. 19. Wujin District Center for Disease Control and Prevention, Changzhou, China. 20. Research Institute, FOSCAL International Clinic, Bucaramanga, Colombia; Eugenio Espejo Medical School, Universidad UTE, Quito, Ecuador. 21. Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran. 22. Madras Diabetes Research Foundation and Dr Mohan's Diabetes Specialities Centre, Chennai, India. 23. St John's Medical College & Research Institute, Bangalore, India. 24. Faculté de pharmacie, Université Laval, Institut universitaire de cardiologie et de pneumologie de Québec, Québec City, QC, Canada. 25. Health Action by People, Kerala, India. 26. Division of Angiology, Wroclaw Medical University, Wroclaw, Poland. 27. Department of Medicine, The Ottawa Hospital, Ottawa, ON, Canada. 28. Department of Medicine, Queen's University, Kingston, ON, Canada. 29. Universiti Teknologi MARA, Selayang Campus, Selangor, Malaysia; UCSI University, Kuala Lumpur, Malaysia. 30. School of Life Sciences, Independent University, Dhaka, Bangladesh. 31. Hatta Hospital, Dubai Medical College, Dubai Health Authority, Dubai, United Arab Emirates. 32. London School of Hygiene & Tropical Medicine, London, UK.
Abstract
BACKGROUND: Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status-wealth and education-differ among high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management. METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family. FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries. INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education. FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
BACKGROUND: Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status-wealth and education-differ among high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management. METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family. FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries. INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education. FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
Authors: Salim Yusuf; Philip Joseph; Sumathy Rangarajan; Shofiqul Islam; Andrew Mente; Perry Hystad; Michael Brauer; Vellappillil Raman Kutty; Rajeev Gupta; Andreas Wielgosz; Khalid F AlHabib; Antonio Dans; Patricio Lopez-Jaramillo; Alvaro Avezum; Fernando Lanas; Aytekin Oguz; Iolanthe M Kruger; Rafael Diaz; Khalid Yusoff; Prem Mony; Jephat Chifamba; Karen Yeates; Roya Kelishadi; Afzalhussein Yusufali; Rasha Khatib; Omar Rahman; Katarzyna Zatonska; Romaina Iqbal; Li Wei; Hu Bo; Annika Rosengren; Manmeet Kaur; Viswanathan Mohan; Scott A Lear; Koon K Teo; Darryl Leong; Martin O'Donnell; Martin McKee; Gilles Dagenais Journal: Lancet Date: 2019-09-03 Impact factor: 79.321
Authors: Jee Won Park; Rachel Mealy; Ian J Saldanha; Eric B Loucks; Belinda L Needham; Mario Sims; Joseph L Fava; Akilah J Dulin; Chanelle J Howe Journal: Health Psychol Date: 2021-06-17 Impact factor: 4.267