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      Cardiovascular Disease Risk Assessment in the United States and Low- and Middle-Income Countries Using Predicted Heart/Vascular Age

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      Scientific Reports
      Nature Publishing Group UK

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          Abstract

          Almost 80% of the global burden of cardiovascular disease (CVD) occurs in low- and middle-income countries (LMICs). However, LMICs do not have well-established, low-technology ways to quantify and communicate CVD risk at population or individual levels. We examined predicted heart/vascular age (PHA) in six LMICs and the United States. Data were from CVD-free adults in World Health Organization Study on Global Aging and Adult Health (n = 29094) and US National Health and Nutritional Examination Survey (n = 6726). PHA was calculated using the non-laboratory Framingham CVD risk equation. High excess PHA (HEPHA) was defined as the differences between PHA and chronological age >5 years. Logistic regression models were used to identify factors associated with HEPHA. Age-standardized prevalence of HEPHA was higher in Russia 52%; China 56%; Mexico 59%; and South Africa 65% compared to the US 45%, Ghana 36%; and India 38%. In LMICs, higher income, being divorced/widowed, alcohol intake and abdominal obesity had higher odds of HEPHA; higher education, fruit intake and physical activity had lower odds of HEPHA. The use of PHA may offer a useful avenue to communicate CVD risk. Interventions tailored at socioeconomic and cultural factors that influence CVD risk factors may be necessary to prevent CVD in LMICs.

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

            The Framingham Heart Study produced sex-specific coronary heart disease (CHD) prediction functions for assessing risk of developing incident CHD in a white middle-class population. Concern exists regarding whether these functions can be generalized to other populations. To test the validity and transportability of the Framingham CHD prediction functions per a National Heart, Lung, and Blood Institute workshop organized for this purpose. Sex-specific CHD functions were derived from Framingham data for prediction of coronary death and myocardial infarction. These functions were applied to 6 prospectively studied, ethnically diverse cohorts (n = 23 424), including whites, blacks, Native Americans, Japanese American men, and Hispanic men: the Atherosclerosis Risk in Communities Study (1987-1988), Physicians' Health Study (1982), Honolulu Heart Program (1980-1982), Puerto Rico Heart Health Program (1965-1968), Strong Heart Study (1989-1991), and Cardiovascular Health Study (1989-1990). The performance, or ability to accurately predict CHD risk, of the Framingham functions compared with the performance of risk functions developed specifically from the individual cohorts' data. Comparisons included evaluation of the equality of relative risks for standard CHD risk factors, discrimination, and calibration. For white men and women and for black men and women the Framingham functions performed reasonably well for prediction of CHD events within 5 years of follow-up. Among Japanese American and Hispanic men and Native American women, the Framingham functions systematically overestimated the risk of 5-year CHD events. After recalibration, taking into account different prevalences of risk factors and underlying rates of developing CHD, the Framingham functions worked well in these populations. The sex-specific Framingham CHD prediction functions perform well among whites and blacks in different settings and can be applied to other ethnic groups after recalibration for differing prevalences of risk factors and underlying rates of CHD events.
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              Emerging epidemic of cardiovascular disease in developing countries.

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                Author and article information

                Contributors
                duke.appiah@ttuhsc.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                30 November 2017
                30 November 2017
                2017
                : 7
                : 16673
                Affiliations
                [1 ]GRID grid.449762.a, Department of Public Health, Texas Tech University Health Sciences Center, ; Abilene, TX USA
                [2 ]ISNI 0000 0001 1945 4190, GRID grid.263724.6, Statistical & Data Sciences, Smith College, ; Northampton, MA USA
                [3 ]ISNI 0000000419368657, GRID grid.17635.36, Division of Epidemiology and Community Health, University of Minnesota Minneapolis, ; Minneapolis, MN USA
                Article
                16901
                10.1038/s41598-017-16901-5
                5709399
                29192146
                0f4125e0-da78-4351-a7bb-109a7bbc1938
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 19 September 2017
                : 15 November 2017
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