Role of Geography on Alzheimer’s Disease and Related Dementias in Central Appalachia

项目总结/摘要 阿尔茨海默病和相关痴呆（ADRD）患病率存在地理差异，但 造成这些差异的机制仍然不明。两个最有可能的和非排他性的解释， ADRD的地理变异是：1。社会人口因素（如农村居民）模式的差异 由于教育程度较低，可能处于ADRD的更大风险中）和/或2.疾病差异 发现率（例如，农村居民获得保健服务的机会和质量可能减少， 更少的痴呆症诊断，无论真正的患病率）。由于农村地区报告的ADRD较低， 尽管受教育程度较低，但与城市地区相比， ADRD患病率），这表明在没有ADRD的地区，ADRD的真正负担可能被低估。 充足的检测资源。有必要了解农村地区ADRD患病率是否真的较低， 如果这是疾病检测差异。本提案的目的是评估ADRD的负担， 阿巴拉契亚中部。通过使用地理特征来评估地理特征之间的关联， 变异、社会人口统计学因素和获得护理的机会（例如，初级保健医生（PCP）、神经科医生） 我们将了解护理模式如何影响ADRD诊断，以及该国哪些地区可能存在ADRD。 由于护理强度的差异，ADRD患病率相对过高或低估。1.我们将核实 使用分层阴性法，阿巴拉契亚中部地区ADRD患病率的地区差异 二项回归模型工作假设：农村县的ADRD患病率较低， 阿巴拉契亚县相对于城市和非阿巴拉契亚县，分别。2.社会人口和 获得护理因素将被纳入现有的负二项模型，以评估其对 ADRD患病率的地区差异。工作假设：部分社会人口和准入因素 解释/减弱ADRD患病率的变化。本提案涉及PAS-19-391的目标， 几种方法：1.主要研究者（PI）是致力于ADRD的早期研究者; 2.的PI 具有使用CMS数据、人口普查数据和其他现有汇总数据源的经验; 3.的PI 已发表使用这些数据描述俄亥俄州ADRD患病率的地理差异。这个项目 将代表更好地了解ADRD患病率的地区差异的下一步，并提供 评估ADRD患病率中获得护理的关键数据。

Project Summary/Abstract Geographic variation in Alzheimer’s disease and related dementias (ADRD) prevalence exists, but the mechanisms driving these disparities remain unknown. The two most likely and non-exclusive explanations for geographic variation in ADRD are: 1. disparities in patterning of sociodemographic factors (e.g. rural residents may be at a greater risk of ADRD due to lower educational attainment) and/or 2. differences in disease detection rates (e.g. rural residents may have reduced access to and quality of health care services and thus fewer dementia diagnoses regardless of the true prevalence). As rural areas have lower reported ADRD prevalence compared to urban areas in spite of lower educational attainment (which should lead to higher ADRD prevalence) this argues that the true burden of ADRD in likely underestimated in areas without adequate detection resources. There is need to understand if ADRD prevalence is truly lower in rural areas, or if this is a disease detection difference. The objective of this proposal is to assess the burden of ADRD in Central Appalachia. By using geographic characteristics to assess the association between geographic variation, socio-demographic factors, and access to care (e.g. primary care physicians (PCPs), neurologists) we will understand how patterns of care influence ADRD diagnoses and which parts of the country may have relatively over- or underestimated ADRD prevalence due to differences in care intensity. 1. We will verify regional differences in ADRD prevalence across the Central Appalachian region using stratified negative binomial regression models. Working hypothesis: Rural counties will have lower ADRD prevalence, as will Appalachian counties relative to urban and non-Appalachian counties, respectively. 2. Socio-demographic and access to care factors will be included in existing negative binomial models to assess their contribution to regional differences in ADRD prevalence. Working hypothesis: socio-demographic and access factors partially explain/attenuate variations in ADRD prevalence. This proposal addresses the objectives of PAS-19-391 in several ways: 1. The Principal Investigator (PI) is an early stage investigator committed to ADRD; 2. The PI has experience with using CMS data, census data, and other existing aggregate data sources; and 3. The PI has published using these data in describing geographic differences in ADRD prevalence in Ohio. This project would represent the next step in better understanding of regional differences in ADRD prevalence and provide critical data toward the role of access to care in estimating ADRD prevalence.