4.6 Article

Socioeconomic status and risk of cardiovascular disease in 20 low-income, middle-income, and high-income countries: the Prospective Urban Rural Epidemiologic (PURE) study

期刊

LANCET GLOBAL HEALTH
卷 7, 期 6, 页码 E748-E760

出版社

ELSEVIER SCI LTD
DOI: 10.1016/S2214-109X(19)30045-2

关键词

-

资金

  1. Mary W Burke endowed chair of the Heart and Stroke Foundation of Ontario
  2. Population Health Research Institute
  3. Canadian Institutes of Health Research
  4. Heart and Stroke Foundation of Ontario
  5. Canadian Institutes of Health Research Strategy for Patient Oriented Research, through the Ontario SPOR Support Unit
  6. Ontario Ministry of Health and Long-Term Care
  7. AstraZeneca [Canada]
  8. Sanofi-Aventis [France]
  9. Sanofi-Aventis [Canada]
  10. Boehringer Ingelheim [Germany]
  11. Boehringer Ingelheim [Canada]
  12. Servier
  13. GlaxoSmithKline
  14. Colombia: Colciencias [6566-04-18062, 6517-777-58228]
  15. Malaysia: Ministry of Science, Technology and Innovation of Malaysia [100-IRDC/BIOTEK 16/6/21, 13/2007, 07-05-IFN-BPH 010]
  16. Ministry of Higher Education of Malaysia [600-RMI/LRGS/5/3 [2/2011]]
  17. Universiti Teknologi MARA, Universiti Kebangsaan Malaysia [UKM-Hejim-Komuniti-15-2010]
  18. Poland: Polish Ministry of Science and Higher Education [290/W-PURE/2008/0]
  19. Saudi Arabia: Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia [RG-1436-013]

向作者/读者索取更多资源

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 (p(interaction)<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 (p(interaction)<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 (p(interaction)<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. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据