Linked Lives, Linked Health: Health Trajectories of Persons with Cognitive Impairment and Their Caregivers' Health

生命相连，健康相连：认知障碍患者及其护理人员的健康轨迹

• 批准号: 10301140
• 负责人: Emma Xiaolu Zang
• 金额: $ 22.39万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-05 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10301140
• 关键词: Address; Affect; Aging; Alzheimer' s Disease; Caregivers; Caring; Characteristics; Clinical; Cognition; Cognitive; Coupled; Data; Dementia; Development; Diagnosis; Distant; Emotional; Foundations; Health; Health Status; High Prevalence; Impaired cognition; Impaired health; Impairment; Joints; Knowledge; Linear Regressions; Link; Long-Term Care; Medicare claim; Modeling; Nature; Outcome; Pattern; Persons; Policies; Population; Population Study; Preparation; Probability; Prognosis; Quality of Care; Research; Research Personnel; Time; Well in self; base; care costs; care giving burden; care recipients; caregiving; cognitive function; cognitive testing; cost; design; effective intervention; experience; follow-up; health care service utilization; health service use; human old age (65+); improved; mild cognitive impairment; physical conditioning; population based; social disadvantage; sociodemographics; trend

Project Summary More than 20% of people ≥65 years old living in the US are cognitively impaired, with diagnoses ranging from mild cognitive impairment (MCI) to dementia. Because of its progressive nature, as persons with cognitive impairment (hereafter “PCIs”) experience decline in cognitive function and other health outcomes, the health of their caregivers or care partners (CG) may also be negatively impacted due to factors such as increased caregiving burden and stress. Determining how the health trajectories of all PCIs affect CG health outcomes over the course of cognitive decline will build a scientific foundation to design effective policies to reduce caregiving cost and improve care quality. The proposed study will investigate the health trajectory patterns of PCIs and their relationships with CG health in the US. Data will be drawn from the annual National Health and Aging Trends Study in 2011–2019 coupled with data from the National Study of Caregiving in 2011, 2015, 2017, and potentially 2021 if available. We will consider general health status, physical health, and psychological well-being for both PCIs and CGs. Our unique contribution to the field of dementia research is threefold: 1) our proposed study is the first to examine both PCI and CG health using a trajectory approach; 2) we will use high-quality population data; 3) we will study the full spectrum of cognitive impairment, rather than only the most severe scenarios. We will first describe health trajectories among PCIs and examine how their trajectories predict CG health across time. For each health outcome, we will apply the single-trajectory Bayesian group-based trajectory model (BGBTM) to identify distinct trajectory groups for PCIs and apply linear regression models to predict CG health. We will also determine how PCI health trajectories are related to CG health trajectories. Applying the dual-trajectory BGBTM, we will visually demonstrate how PCI and CG health trajectories are parallel in time and estimate the probability of one trajectory pattern among CGs conditional upon one pattern among PCIs. Second, we will determine how the relationships examined above are moderated by caregiving and sociodemographic characteristics of CGs. We hypothesize that a distant relationship with PCIs, high-intensity caregiving, a heavy caregiving burden, and social disadvantage are associated with adverse health outcomes and trajectories among CGs, and that these characteristics moderate the association between PCI health trajectories and CG health outcomes and trajectories. Finally, we will determine joint trajectories in PCI cognition and other health outcomes, as well as the impact of PCI cognitive trajectories on CG health. Findings of this study will assist policymakers in understanding the health consequences of caregiving for PCIs, which will build a scientific foundation for the development of effective interventions to improve the quality of care and reduce long-term care cost. Further, understanding the prognosis for various types of PCI and CG health trajectories may enable better preparation of caregiving and ultimately higher quality care.

项目摘要 在生活在美国的65岁的人中，超过20%的人有认知障碍，诊断结果不一 从轻度认知障碍(MCI)到痴呆症。因为它的进步性，作为有认知能力的人 认知功能障碍(以下简称PCI)会导致认知功能和其他健康后果的下降， 他们的照顾者或护理伙伴(CG)也可能由于以下因素而受到负面影响 照顾他人的负担和压力。确定所有PCI的健康轨迹如何影响CG健康结果 在认知衰退的过程中将建立科学的基础，以设计有效的政策来减少 降低护理成本，提高护理质量。 拟议的研究将调查PCI的健康轨迹模式及其与CG的关系 美国的健康状况。数据将来自2011-2019年年度全国健康和老龄化趋势研究 再加上2011、2015、2017年的全国护理研究数据，如果有的话，还可能在2021年。 我们将考虑PCI和CGs的一般健康状况、身体健康和心理健康。 我们对痴呆症研究领域的独特贡献有三个方面：1)我们提出的研究是第一个 使用轨迹方法检查PCI和CG运行状况；2)我们将使用高质量的人口数据；3)我们 将研究认知障碍的全部范围，而不仅仅是最严重的情况。 我们将首先描述PCI之间的健康轨迹，并检查它们的轨迹如何预测CG健康 跨越时间。对于每个健康结果，我们将应用基于组的单轨迹贝叶斯轨迹 识别PCI的不同轨迹组并应用线性回归模型预测CG的模型(BGBTM) 健康。我们还将确定冠状动脉介入治疗健康轨迹与CG健康轨迹之间的关系。应用 双轨迹BGBTM，我们将直观地演示PCI和CG的健康轨迹在时间上是平行的 并且根据PCI中的一个模式来估计CG中的一个轨迹模式的概率。 其次，我们将确定上述关系是如何通过照顾和照顾来调节的 社区人群的社会人口学特征。我们假设与PCI的疏远关系，高强度 照料、沉重的照料负担和社会劣势与不良的健康结局有关。 和CG之间的轨迹，这些特征缓和了冠状动脉介入治疗健康之间的关联 轨迹和CG健康结果和轨迹。最后，我们将确定在经皮冠状动脉介入治疗中的关节轨迹 认知和其他健康结果，以及冠状动脉介入治疗认知轨迹对CG健康的影响。 这项研究的结果将有助于政策制定者理解照顾老年人的健康后果 这将为制定有效的干预措施建立科学基础，以改善 提高护理质量，降低长期护理成本。此外，了解各种类型的冠状动脉介入治疗的预后 而CG健康轨迹可能会使护理准备工作更好，并最终实现更高质量的护理。