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      Socio-Economic Differences in Cardiovascular Health: Findings from a Cross-Sectional Study in a Middle-Income Country


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          A relatively consistent body of literature, mainly from high-income countries, supports an inverse association between socio-economic status (SES) and risk of cardiovascular disease (CVD). Data from low- and middle-income countries are scarce. This study explores SES differences in cardiovascular health (CVH) in the Republic of Srpska (RS), Bosnia and Herzegovina, a middle-income country.


          We collected information on SES (education, employment status and household’s relative economic status, i.e. household wealth) and the 7 ideal CVH components (smoking status, body mass index, physical activity, diet, blood pressure, total cholesterol, and fasting blood glucose) among 3601 participants 25 years of age and older, from the 2010 National Health Survey in the RS. Based on the sum of all 7 CVH components an overall CVH score (CVHS) was calculated ranging from 0 (all CVH components at poor levels) to 14 (all CVH components at ideal levels). To assess the differences between groups the chi-square test, t-test and ANOVA were used where appropriate. The association between SES and CVHS was analysed with multivariate linear regression analyses. The dependent variable was CVHS, while independent variables were educational level, employment status and wealth index.


          According to multiple linear regression analysis CVHS was independently associated with education attainment and employment status. Participants with higher educational attainment and those economically active had higher CVHS (b = 0.57; CI = 0.29–0.85 and b = 0.27; CI = 0.10–0.44 respectively) after adjustment for sex, age group, type of settlement, and marital status. We failed to find any statistically significant difference between the wealth index and CVHS.


          This study presents the novel information, since CVHS generated from the individual CVH components was not compared by socio-economic status till now. Our finding that the higher overall CVHS was independently associated with a higher education attainment and those economically active supports the importance of reducing socio-economic inequalities in CVH in RS.

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          The social determinants of health: coming of age.

          In the United States, awareness is increasing that medical care alone cannot adequately improve health overall or reduce health disparities without also addressing where and how people live. A critical mass of relevant knowledge has accumulated, documenting associations, exploring pathways and biological mechanisms, and providing a previously unavailable scientific foundation for appreciating the role of social factors in health. We review current knowledge about health effects of social (including economic) factors, knowledge gaps, and research priorities, focusing on upstream social determinants-including economic resources, education, and racial discrimination-that fundamentally shape the downstream determinants, such as behaviors, targeted by most interventions. Research priorities include measuring social factors better, monitoring social factors and health relative to policies, examining health effects of social factors across lifetimes and generations, incrementally elucidating pathways through knowledge linkage, testing multidimensional interventions, and addressing political will as a key barrier to translating knowledge into action.
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            Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.

            Recent recommendations from the American Heart Association aim to improve cardiovascular health by encouraging the general population to meet 7 cardiovascular health metrics: not smoking; being physically active; having normal blood pressure, blood glucose and total cholesterol levels, and weight; and eating a healthy diet. To examine time trends in cardiovascular health metrics and to estimate joint associations and population-attributable fractions of these metrics in relation to all-cause and cardiovascular disease (CVD) mortality risk. Study of a nationally representative sample of 44,959 US adults (≥20 years), using data from the National Health and Nutrition Examination Survey (NHANES) 1988-1994, 1999-2004, and 2005-2010 and the NHANES III Linked Mortality File (through 2006). All-cause, CVD, and ischemic heart disease (IHD) mortality. Few participants met all 7 cardiovascular health metrics (2.0% [95% CI, 1.5%-2.5%] in 1988-1994, 1.2% [95% CI, 0.8%-1.9%] in 2005-2010). Among NHANES III participants, 2673 all-cause, 1085 CVD, and 576 IHD deaths occurred (median follow-up, 14.5 years). Among participants who met 1 or fewer cardiovascular health metrics, age- and sex-standardized absolute risks were 14.8 (95% CI, 13.2-16.5) deaths per 1000 person-years for all-cause mortality, 6.5 (95% CI, 5.5-7.6) for CVD mortality, and 3.7 (95% CI, 2.8-4.5) for IHD mortality. Among those who met 6 or more metrics, corresponding risks were 5.4 (95% CI, 3.6-7.3) for all-cause mortality, 1.5 (95% CI, 0.5-2.5) for CVD mortality, and 1.1 (95% CI, 0.7-2.0) for IHD mortality. Adjusted hazard ratios were 0.49 (95% CI, 0.33-0.74) for all-cause mortality, 0.24 (95% CI, 0.13-0.47) for CVD mortality, and 0.30 (95% CI, 0.13-0.68) for IHD mortality, comparing participants who met 6 or more vs 1 or fewer cardiovascular health metrics. Adjusted population-attributable fractions were 59% (95% CI, 33%-76%) for all-cause mortality, 64% (95% CI, 28%-84%) for CVD mortality, and 63% (95% CI, 5%-89%) for IHD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of total and CVD mortality, but the prevalence of meeting all 7 cardiovascular health metrics was low in the study population.
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              Socioeconomic status and cardiovascular disease: risks and implications for care.

              Socioeconomic status (SES) refers to an individual's social position relative to other members of a society. Low SES is associated with large increases in cardiovascular disease (CVD) risk in men and women. The inverse association between SES and CVD risk in high-income countries is the result of the high prevalence and compounding effects of multiple behavioral and psychosocial risk factors in people of low SES. However, strong and consistent evidence shows that parental SES, childhood and early-life factors, and inequalities in health services also contribute to elevated CVD risk in people of low SES who live in high-income countries. In addition, place of residence can affect CVD risk, although the data on the influence of wealth distribution and work-related factors are inconsistent. Studies on the effects of SES on CVD risk in low-income and middle-income countries is scarce, but evidence is emerging that the increasing wealth of these countries is beginning to lead to replication of the patterns seen in high-income countries. Clinicians should address the association between SES and CVD by incorporating SES into CVD risk calculations and screening tools, reducing behavioral and psychosocial risk factors via effective and equitable primary and secondary prevention, undertaking health equity audits to assess inequalities in care provision and outcomes, and by use of multidisciplinary teams to address risk factors over the life course.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                29 October 2015
                : 10
                : 10
                : e0141731
                [1 ]Institute of Social Medicine, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
                [2 ]Center for European Integration and Public Management, Faculty of Economics, Finance and Administration, Singidunum University, Belgrade, Serbia
                [3 ]Institute of Public Health, Banja Luka, Republic of Srpska, Bosnia and Herzegovina
                [4 ]Institute of Medical Statistics and Informatics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
                [5 ]Institute of Epidemiology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
                Hunter College, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JJ JM SJ DS. Performed the experiments: DS SJ. Analyzed the data: JM ME JJ. Contributed reagents/materials/analysis tools: ME DS. Wrote the paper: JJ SJ JM. Approved the final version to be published and agreed to be accountable for all aspects of the work: all authors.

                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                : 5 May 2015
                : 11 October 2015
                Page count
                Figures: 1, Tables: 4, Pages: 14
                The 2010 National Health Survey was supported by the World Bank and Ministry of Health and Social Welfare of the Republic of Srpska. Funding for this work was obtained from the Ministry of Education, Science and Technological Development of the Republic of Serbia (project No. 175025). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Custom metadata
                Data are from the 2010 National Health Survey in Republic of Srpska and due to ethical restrictions are not freely available. However, the raw de-identified, participant-level dataset is available upon request from the Ethics Committee of the Public Health Institute of Republic of Srpska at: info@ 123456phi.rs.ba or janjabojanic@ 123456gmail.com . Additionally, Dragana Stojisavljevic, the coauthor of this manuscript, can provide the data underlying the conclusions of this study, by contact email address: dada.bl@ 123456hotmail.com .



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