Racial/Ethnic Disparities in the Alzheimer's Disease Link with Heart Disease and Stroke

摘要： 阿尔茨海默病(AD)是痴呆的主要亚型，占#年痴呆病例的60%-80% 美国(US)。随着发达国家预期寿命的增加，阿尔茨海默病正在成为主要的 在生命的后期阶段的问题。心脏病和中风事件是另两个日益增长的问题 老年人口。越来越多的文献将心脏病和中风作为危险因素。 对于阿尔茨海默病，突出细胞水平上的重要途径。然而，还需要进一步研究 心脏病、中风与阿尔茨海默病的关系有助于提高我们对流行病学的认识 这种联系的特征，这可能会让我们识别出可能处于不利地位的高危亚群 这样的依赖关系。夏威夷的人口是美国最多元化的种族人口之一，存在着 在这一多族裔人口中存在着显著的种族/民族健康差距。特别是，夏威夷原住民和 太平洋岛民(NHPI)是众所周知的许多疾病的高危群体，包括 心血管疾病和中风。心脏功能障碍与中风在AD发病中的联系 NHPI可能是AD的高危人群。我们提出了一项研究，以探索65岁和65岁以上患者的AD风险 根据夏威夷医疗保险数据库，高于那些有重大心脏事件和中风的人。建议数 工作将在事件发生时间多状态模型框架下进行，同时考虑竞争风险 用于获取无偏估计和推论。2009年至2017年夏威夷医疗保险九年数据 将用于收集拟议工作的重要活动时间细节，这使我们能够进行 从心脏病或中风进展到AD的多个方面的综合事件发生时间分析 阿尔茨海默病的死亡率；心脏病和中风风险。拟议研究的一个主要特点是调查 种族/民族对阿尔茨海默病、心脏病和中风的依赖。我们还建议开发机器 基于受试者档案预测过渡和死亡率的学习驱动的预测模型。

Abstract: Alzheimer’s disease (AD) is the major subtype of dementia, which accounts for 60-80% of dementia cases in the United States (US). With the increased life expectancy in developed countries, AD is becoming a major issue at the late stage of life. Heart disease and stroke events are another two growing issues among the elderly population. There is an expanding body of literature implicating heart disease and stroke as risk factors for AD, highlighting significant pathways at the cellular level. However, further research is needed on the association between heart, stroke, and development of AD to improve our understanding of epidemiological features of this link, which could lead us to identify high-risk subgroups who potentially disadvantaged from such dependencies. Hawaii's population is one of the most diverse ethnic populations in the US and there exist significant racial/ethnic health disparities in this multiethnic population. Especially, Native Hawaiians and Pacific Islanders (NHPI) are a well-known high-risk group for many disease conditions, including cardiovascular conditions and stroke. Links between heart dysfunction and stroke on developing AD makes NHPI potentially a high-risk group for AD. We propose a study to explore the AD risk for patients age 65 and above those who had major heart events and stroke, based on the Hawaii Medicare database. The proposed work will be conducted under a time-to-event multistate model framework while accounting for competing risks for acquiring unbiassed estimations and inferencing. Nine years of Hawaii Medicare data from 2009 to 2017 will be utilized to gather important time-to-event details for the proposed work, which allows us to conduct comprehensive time-to-event analyses on several aspects: progression from heart disease or stroke to AD; AD mortality; heart disease and stroke risks for AD. A key feature of the proposed study is the investigation of racial/ethnic dependency on AD, heart disease, and stroke links. We also propose to develop machine learning-driven predictive models for predicting transitions and mortality based on subject profiles.