Comparative Assessment of Modifying Social Determinants to Reduce Cardiovascular Disease Burden and Disparities

项目总结/摘要 尽管在预防和治疗心血管疾病（CVD）方面取得了进展，但财政限制仍然存在。 促使联邦和州的决策者在相互竞争的政策决定中做出艰难的选择， 没有有效性的证据。一个比较有效的方法，或在缺乏实验的情况下， 数据，一种比较评估方法，比较修改暴露的估计影响 利用观测数据，可以为这一优先事项的确定过程提供重要信息。我们和其他人已经证明了 社会决定因素，上游社会因素，如收入不平等和社会资本/凝聚力， 包括CVD在内的疾病的关键预测因子。然而，重要的问题仍然存在， 对CVD负担的影响最大。此外，我们缺乏关于哪些亚群和 各国受影响最大。尽管有人呼吁进行比较评估/提高战略的有效性， 人口健康和预防CVD，包括NIH，我们仍然缺乏对相对CVD负担的了解 以及与修改这些因素相关的经济影响。鉴于这些信息， 准确估计社会决定因素对心血管疾病风险的影响;将这些估计转化为政策- 设置工具，包括对CVD负担和成本的影响;并比较和对比 这些影响。我们的总体目标是提供第一个比较评估证据基础， 比较CVD负担和修改中年和老年人关键社会决定因素的经济影响， 美国老人我们将通过使用数据实现以下具体目标来实现我们的总体目标 从两个大的，全国代表性的中年和老年人的样本，国家纵向 1979年青年调查（NLSY）和健康与退休研究（HRS），与社会和经济有关 按居住地区衡量，以及医疗保险索赔和死亡率数据库：目标#1）确定 哪些社会决定因素最能预测心血管疾病的发病率、死亡率和危险因素 在中年和老年人;目标#2）确定哪些亚群和地理状态是 最容易受到心血管疾病负担和风险因素的社会决定因素的影响;以及目标3） 为了确定哪些社会决定因素，如果修改，预计将产生最大的减少， CVD负担及其相关费用，包括总体和亚群。关于结果，我们的3- 一项为期一年的研究预计将确定最有希望的社会决定因素，据以进行干预， 改善成人CVD负担。我们将进一步确定脆弱性如何受地理和 亚群可以解释CVD差异。通过将我们的估计转化为人口健康和经济 我们将直接回应CVD中的比较评估和经济评估的要求， 预防研究。从长远来看，我们预计我们的项目将通过以下方式产生巨大的转化影响： 指导政策制定者的循证决策，以减少心血管疾病负担和不平等。

PROJECT SUMMARY/ABSTRACT Despite advancements in prevention and treatments for cardiovascular diseases (CVD), fiscal constraints have driven federal and state policymakers to make difficult choices among competing policy decisions, often without evidence of effectiveness. A comparative effectiveness approach, or in the absence of experimental data, a comparative assessment approach that compares the estimated impacts of modifying exposures using observational data, can critically inform this priority-setting process. We and others have demonstrated that social determinants, upstream social factors such as income inequality and social capital/cohesion, are key predictors of disease including CVD. Yet important questions remain about which social determinants have the biggest impacts on CVD burden. Furthermore, we lack knowledge on which subpopulations and states are most affected. In spite of calls for comparative assessments/effectiveness of strategies to improve population health and prevent CVD, including from NIH, we still lack knowledge on the relative CVD burden and economic impacts associated with modifying such factors. Given this information, there are critical needs to accurately estimate the impacts of social determinants on CVD risks; to translate these estimates into policy- setting tools including impacts on CVD burden and costs; and to compare and contrast the costs and sizes of these impacts. Our overall objective is to provide the first comparative assessment evidence base to compare the CVD burden and economic impacts of modifying key social determinants in middle-aged and older Americans. We will accomplish our overall objective by pursuing the following specific aims using data from two large, nationally-representative samples of middle-aged and older adults, the National Longitudinal Survey of Youths 1979 (NLSY) and the Health and Retirement Study (HRS), linked to social and economic measures by area of residence, and to Medicare claims and mortality databases: Aim #1) To determine which social determinants most strongly predict the risks of CVD incidence, mortality, and risk factors in middle-aged and older adults; Aim #2) To identify which subpopulations and geographic states are most vulnerable to the influences of social determinants on CVD burden and risk factors; and Aim #3) To determine which social determinants if modified are expected to yield the greatest reductions in CVD burden and its associated costs, both overall and by subpopulation. Regarding outcomes, our 3- year study is expected to identify the most promising social determinants on which to intervene to yield improvements in adult CVD burden. We will further establish how vulnerabilities to effects by geography and subpopulations may explain CVD disparities. By translating our estimates into population health and economic measures, we will directly respond to calls for comparative assessments and economic evaluations in CVD prevention research. Over the long term, we expect that our project will have high translational impact through guiding policymakers' evidence-based decisions to reduce CVD burden and inequities.