US Cardiovascular Health Disparities

Geographic and racial/ethnic disparities in cardiovascular diseases (CVD) – the leading cause of death in the U.S. – remain large. Since 2010, CVD death rates are no longer declining in many states, and for some groups, mortality is increasing. Reduction in CVD disparities is a major stated goal of U.S. health policy, but national-level strategies, such as Healthy People 2020 and the Million Hearts campaign, do not directly address these large geographic differences in CVD between states. The U.S. is rich in local health data, yet it is poorly integrated, so there is little evidence available to guide states or local health systems when selecting among primary prevention interventions and policies. Health policy models are an important way to integrate complex patterns of risk exposure and disease burden with other population trends including income, education, aging, migration, and health care access. Previous CVD forecasts and policy models have produced only single geography – primarily national – estimates, which cannot provide the evidence needed to address geographic disparities. The overarching goal for this study will be: a systematic analysis of why CVD patterns vary by age, sex, race/ethnicity, and state in the U.S.; how this variation will lead to future divergence in CVD mortality rates; and the variable impact that similar risk reduction strategies will then have on different U.S. states. For this work, we will adapt econometric, geospatial, and epidemiologic modelling methods by leveraging the large data and computational resources of the Global Burden of Disease Study. Aim 1 is a CVD population health projection that will estimate future burden of CVD for each U.S. state by age, sex, and race/ethnicity. Using observed past trends in CVD and major modifiable causal risk factors, we will project health loss due to CVD, including disability-adjusted life years (DALYs), through 2040 for each U.S. state. We will integrate multiple sources of existing health surveillance data with the results of state-level health examination surveys. Estimates will be produced separately by sex and 5-year age groups, for four collectively exhaustive race/ethnicity categories for CVD overall, and separately for ischemic heart disease, heart failure, stroke, peripheral vascular disease, aortic aneurysm, and chronic kidney disease. Aim 2 is a new set of CVD health policy models that estimate the impact within each state of interventions shown to improve the delivery of pharmacotherapies that lower blood pressure and LDL-cholesterol. Aim 3 is a new set of CVD health policy models that estimate the impact of behavioral interventions shown to reduce CVD risk factors. Projections and policy models for CVD are a necessary step in reducing U.S. health disparities. Our results will be able to guide local decision-makers considering a range of policy options to reduce the burden of CVD. We will then implement a broad dissemination plan designed to expand the impact of our work beyond academic audiences, providing webinars, policy reports, and outreach to health departments and other stakeholders actively engaged in policy work in key states.