Impact of Interventions on Future Trends in Subnational Burden of Cardiovascular Diseases in the US

干预措施对美国地方心血管疾病负担未来趋势的影响

• 批准号: 10471773
• 负责人: Gregory Andrew Roth
• 金额: $ 80.4万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-22 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10471773
• 关键词: Address; Age; Age-Years; Aging; Air Pollution; Antihypertensive Agents; Aortic Aneurysm; Behavior Therapy; Blood Pressure; Body mass index; Cardiovascular Diseases; Cardiovascular Models; Categories; Cause of Death; Cessation of life; Cholesterol; Chronic Kidney Failure; Chronic Obstructive Pulmonary Disease; Complex; Computer Simulation; Data; Death Rate; Diet; Education; Ethnic Origin; Ethnic group; Future; Geography; Glucose; Goals; Health; Health Policy; Health Status; Health system; Healthy People 2020; Heart; Heart failure; Hydroxymethylglutaryl-CoA Reductase Inhibitors; Incidence; Income; Individual; Intervention; LDL Cholesterol Lipoproteins; Life Cycle Stages; Link; Longitudinal trends; Masks; Methods; Minnesota; Modeling; Myocardial Ischemia; Obesity; Oklahoma; Past Trends; Pattern; Peripheral Vascular Diseases; Pharmaceutical Preparations; Pharmacotherapy; Plasma; Policies; Population; Population trends; Primary Prevention; Race; Reporting; Risk; Risk Factors; Risk Reduction; Role; Source; Stroke; Surveys; Testing; Time; Variant; Weight Gain; Work; adherence rate; age group; base; blood pressure reduction; burden of illness; cardiometabolic risk; cardiometabolism; cardiovascular disorder prevention; cardiovascular disorder risk; computer infrastructure; computing resources; data infrastructure; data resource; design; diabetes prevention program; disability-adjusted life years; disease disparity; econometrics; epidemiological model; evidence base; exhaustion; geographic difference; geographic disparity; health care availability; health data; health disparity; improved; intervention program; medication compliance; migration; models and simulation; mortality; outreach; population based; population health; premature; prevent; preventive intervention; programs; racial and ethnic; racial and ethnic disparities; sex; surveillance data; trend; webinar; young adult

PROJECT SUMMARY 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.

项目摘要 心血管疾病（CVD）的地理和种族/种族分布 - 死亡的主要原因 美国 - 仍然很大。自2010年以来，许多州的CVD死亡率不再下降，对于某些州来说 群体，死亡率正在增加。减少CVD差异是美国卫生政策的主要既定目标，但是 国家一级策略，例如2020年健康人和百万心运动，并不直接 解决了各州之间CVD的这些较大的地理差异。美国富含当地健康数据，但 整合不足，因此选择时几乎没有证据可以指导各州或当地卫生系统 在主要预防干预措施和政策中。健康政策模型是整合的重要方法 风险暴露和疾病伯恩的复杂模式与其他人口趋势，包括收入， 教育，老龄化，移民和医疗保健。以前的CVD预测和政策模型具有 仅产生单个地理 - 主要国家 - 估计，该估计无法提供所需的证据 地址地理分布。这项研究的总体目标将是：系统分析CVD 在美国，模式因年龄，性别，种族/种族和国家而异；这种变化将如何导致未来的分歧 CVD死亡率；然后，类似的降低风险策略将对不同的不同影响 美国州。对于这项工作，我们将通过 利用全球疾病负担的大量数据和计算资源。 AIM 1是CVD 人口健康预测将估计每个美国国家的CVD未来烧伤，按年龄，性别和 种族/种族。使用CVD中观察到的过去趋势和主要可修改的因果风险因素，我们将投射 CVD造成的健康损失，包括残疾调整后的终身年份（DALYS），直到2040年，每个州。我们 将将现有健康监视数据的多种来源与州级健康的结果相结合 考试调查。估计将由性别和5岁年龄段分别产生，四个 CVD的详尽种族/民族类别，以及分别用于缺血性心脏病，心力衰竭， 中风，周围血管疾病，主动脉瘤和慢性肾脏疾病。 AIM 2是一组新的CVD 估计每种干预措施内影响的影响以改善交付的影响 降低血压和LDL-胆固醇的药物疗法。 AIM 3是一组新的CVD健康政策 估计显示降低CVD风险因素的行为干预措施影响的模型。预测和 CVD的政策模型是减少美国健康差异的必要步骤。我们的结果将能够 指导当地决策者考虑一系列政策选择，以减少CVD的伯恩。然后我们会 实施广泛的传播计划，旨在扩大我们的工作的影响 受众，向卫生部门和其他利益相关者提供网络研讨会，政策报告和宣传 积极从事关键州的政策工作。

项目成果

Open Data Challenge to Examine the Impact of Social Determinants of Health on Stroke.

开放数据挑战赛旨在检验健康的社会决定因素对中风的影响。

• DOI: 10.1161/strokeaha.123.042645
• 发表时间: 2023
• 期刊: Stroke
• 影响因子: 8.3
• 作者: Hall,JenniferL;Roth,GregoryA
• 通讯作者: Roth,GregoryA

Impact of the COVID-19 Pandemic on Cardiovascular Health in 2020: JACC State-of-the-Art Review.

• DOI: 10.1016/j.jacc.2022.06.008
• 发表时间: 2022-08-09
• 期刊: JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
• 影响因子: 24
• 作者: Roth, Gregory A.;Vaduganathan, Muthiah;Mensah, George A.
• 通讯作者: Mensah, George A.

Fatal police violence by race and state in the USA, 1980-2019: a network meta-regression.

• DOI: 10.1016/s0140-6736(21)01609-3
• 发表时间: 2021-10-02
• 期刊: Lancet (London, England)
• 作者: GBD 2019 Police Violence US Subnational Collaborators

Life Expectancy for White, Black, and Hispanic Race/Ethnicity in U.S. States: Trends and Disparities, 1990 to 2019.

• DOI: 10.7326/m21-3956
• 发表时间: 2022-08
• 期刊: Annals of internal medicine
• 影响因子: 39.2
• 作者: Johnson CO;Boon-Dooley AS;DeCleene NK;Henny KF;Blacker BF;Anderson JA;Afshin A;Aravkin A;Cunningham MW;Dieleman JL;Feldman RG;Gakidou E;Mokdad AH;Naghavi M;Spencer CN;Whisnant JL;York HW;Zende RR;Zheng P;Murray CJL;Roth GA
• 通讯作者: Roth GA