Dementia epidemiology, health service utilization and treatment costs among American Indian and Alaska Native Elders

项目摘要 随着美国人口老龄化，患有阿尔茨海默病的人数和 相关痴呆症（ADRD）预计到2050年将增加两倍。虽然预期寿命 美国印第安人和阿拉斯加原住民（AI/AN）比美国其他人口短得多， 在过去的几十年里，随着人工智能/人工智能老年人的扩大， 人口预计将继续。与大多数美国人口相比，AI/AN承担着 许多已确定的痴呆症可改变的风险因素，如 糖尿病肥胖和吸烟然而，我们对老年痴呆症的了解 仍然受到严格限制。到目前为止，只有少数研究检查了痴呆症， 在AI/AN中，提供关于该人群痴呆症患病率或发病率的可靠数据 是不存在的。鉴于我们对AI/AN中痴呆症的了解存在如此多的差距， 迫切需要进行系统的研究，以确定痴呆症在这方面的问题有多大。 人口及其对印度卫生系统的影响，以实现更精确的规划， 优先考虑支持相关保健政策所需的资源。在这里，利用16 印度卫生服务（IHS）数据项目提供的多年纵向数据， 现有IHS电子健康数据的近30%（约640，000 AI/AN），我们建议解决AI/AN中有关痴呆症的4个主要知识差距， 遵循以下具体目标：（1）估计痴呆症的患病率，发病率， 根据个人和社区特征，AI/AN老年人的共患病率，例如 年龄、性别、所在地和县级社会经济地位;（2）描述协会的特征 痴呆症和潜在的可改变的风险因素之间的联系，如糖尿病，肥胖，烟草 使用，酗酒，创伤性脑损伤和抑郁症;（3）评估的影响， 痴呆和共病状态对卫生服务利用模式的影响，包括住院， （四）医疗费用;（五）医疗费用;（六）医疗费用。 患有痴呆症的AI/AN，以及影响这些成本的因素，如合并症状态。我们 拟议的分析将提供一个相对准确和完整的流行病学情况 基于大规模和地理多样性的样本，在AI/AN中诊断出痴呆症， 有助于了解痴呆症和相关的卫生服务利用， 生活在弱势社区的人口得不到充分的服务。我们的发现保证 为未来的痴呆症研究奠定基础，以满足AI/AN和 其他类似的弱势群体。

PROJECT SUMMARY As the US population ages, the number of people living with Alzheimer’s Disease and related dementias (ADRD) is projected to triple by 2050. Although the life expectancy of American Indian and Alaska Natives (AI/ANs) is much shorter than that of other US populations, it has dramatically increased in the last few decades, with the expansion of the AI/AN elder population expected to continue. Compared to most US populations, AI/ANs bear a disproportionate burden of many established modifiable risk factors for dementia, such as diabetes, obesity, and smoking. However, our knowledge about dementia in this population remains to be severely limited. So far, only a handful of studies have examined dementia among AI/ANs, with reliable data on the prevalence or incidence of dementia in this population being nonexistent. Given so many gaps in our knowledge about dementia among AI/ANs, a systematic investigation is urgently needed to identify how problematic dementia is in this population and its impact on the Indian health system to enable more precise planning and prioritization of resources needed to support relevant health care policy. Here, leveraging on 16 years of longitudinal data available in the Indian Health Service (IHS) Data Project, a synthesis of existing IHS electronic health data for nearly 30% of the IHS service population (~ 640,000 AI/ANs), we propose to address 4 major knowledge gaps about dementia among AI/ANs as guided by the following specific aims: (1) Estimate dementia prevalence, incidence, and comorbidity rates among AI/AN elders by individual and community characteristics, such as age, gender, location, and county level socioeconomic status; (2) Characterize the association between dementia and potentially modifiable risk factors, such as diabetes, obesity, tobacco use, binge drinking, traumatic brain injuries and depression; (3) Evaluate the influence of dementia and comorbidity status on health service utilization patterns, including inpatient, outpatient, and pharmacy services; and (4) Examine the costs of providing treatment among AI/ANs with dementia, and factors that influence these costs such as comorbidity status. Our proposed analyses will provide a relatively accurate and complete picture for the epidemiology of diagnosed dementia among AI/ANs based on a large and geographically diverse sample, and contribute to the understanding of dementia and associated health service utilization in an extremely underserved population living in disadvantaged communities. Our findings promise to lay groundwork for future studies on dementia to address both the needs of AI/ANs and those of other similarly underserved populations.