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

项目摘要/摘要 阿尔茨海默病和相关痴呆(ADRD)的患病率存在地理差异，但 造成这些差异的机制仍不清楚。两个最有可能也是非排他性的解释 ADRD的地理差异是：1.社会人口因素(例如农村居民)模式的差异 由于受教育程度较低，患ADRD的风险可能更大)和/或2.疾病的差异 发现率(例如，农村居民获得卫生保健服务的机会和质量可能减少，因此 更少的痴呆症诊断，无论真实的患病率如何)。由于农村地区报告的ADRD较低 与城市地区相比，尽管受教育程度较低(这应该会导致更高的教育水平)，但患病率仍高于城市地区 ADRD普及率)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ADRD在农村地区的患病率是否真的较低，或者 如果这是疾病检测的差异。这项建议的目标是评估#年ADRD的负担 阿巴拉契亚中部。通过使用地理特征来评估地理位置之间的关联 变化、社会人口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的诊断，以及该国哪些地区可能有 由于护理强度的差异，相对高估或低估了ADRD的患病率。1.我们会核实 用分层阴性法研究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患病率将较低， 阿巴拉契亚县分别相对于城市县和非阿巴拉契亚县。2.社会人口和 获得护理因素将被包括在现有的负二项模型中，以评估它们对 ADRD流行率的地区差异。工作假说：部分社会人口和准入因素 解释/减弱ADRD流行率的变化。该提案涉及PAS-19-391#年的目标。 几种方式：1.首席调查员(PI)是致力于ADRD的早期调查员；2.PI 有使用CMS数据、人口普查数据和其他现有聚合数据源的经验；以及3.PI 已经发表了使用这些数据来描述俄亥俄州ADRD流行率的地理差异。这个项目 将代表着更好地了解ADRD流行的地区差异的下一步，并提供 获得护理在评估ADRD流行率中的作用的关键数据。

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.