Susceptibility and adverse health outcomes related to climate-sensitive events among older Medicare beneficiaries with Alzheimer and Dementia

患有阿尔茨海默症和痴呆症的老年医疗保险受益人与气候敏感事件相关的易感性和不良健康结果

• 批准号: 10607424
• 负责人: Michelle L Bell
• 金额: $ 237.85万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10607424
• 关键词: Address; Affect; Age; Aging; Air Pollutants; Air Pollution; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Area; Burn injury; Charge; Chronic; Climate; Code; Computer software; Data; Dementia; Dependence; Development; Elderly; Emergency Situation; Environmental Impact; Ethnic Origin; Event; Exposure to; Frequencies; Future; Goals; Health; Heat Waves; Hispanic Americans; Home; Hospitalization; Hospitals; Imagery; Individual; Knowledge; Late Onset Alzheimer Disease; Link; Literature; Machine Learning; Medicare; Methodology; Methods; Modeling; Monitor; Nitrogen Dioxide; Nursing Homes; Outcome; Ozone; Patient-Focused Outcomes; Persons; Physiological; Population; Predisposition; Public Health; Race; Racial Segregation; Readiness; Recovery; Regulation; Reporting; Research; Risk Estimate; Science; Series; Smoke; Socioeconomic Status; Statistical Data Interpretation; Subgroup; Symptoms; Time; Vulnerable Populations; Weather; Wildfire; Work; World Health Organization; beneficiary; brain health; climate change; climate impact; cohort; community-level factor; design; effective intervention; environmental health disparity; environmental justice; extreme heat; extreme temperature; fine particles; frailty; health management; hospital readmission; land use; loved ones; machine learning algorithm; meteorological data; mortality; mortality risk; multiple chronic conditions; novel; response; sex; spatiotemporal; structural determinants

The WHO listed air pollution and climate change as two of the top ten threats in 2019, and earlier research indicates links between climate change exposures and brain health. Further, the burden of older persons with Alzheimer’s disease (AD) and related dementias (ADRD) is expected to double by 2060, with the largest increase for Hispanic Americans. Simultaneously, wildfires are increasing in frequency, intensity, and duration. In summary, the environmental impact of climate change could become a brain health emergency that we are unprepared to tackle. To date, little is known regarding impacts of heat or air pollution, including wildfire smoke, on the elderly with AD/ADRD. Most studies on climate change related vulnerability investigated a single factor at a time rather than the real-world settings characterized by multiple factors (co-occurring air pollution and heat, socio-economic status, frailty, chronic conditions, race/ethnicity). Further, previous studies have not leveraged recent developments in satellite imagery, machine learning, and causal inference methods, which can increase the rigor and validity of statistical analysis. We propose to address these scientific gaps using a large, validated cohort of US Medicare beneficiaries (>65y) with AD/ADRD (approx. 10 million for the period 2000-2019) and spatially resolved weather data combined with state-of-the-science machine learning for estimates of air pollution exposure, which leverages satellite imagery, land use data, and monitors. Our long- term goals are to characterize the vulnerability and health impacts of climate change-related exposures within a large cohort of older adults with AD/ADRD. First, we will estimate the impacts of short-term exposure to heat and heatwaves on cause-specific hospital admissions, readmissions, mortality, and a novel patient-centered outcomes of days-at-home, and develop machine learning algorithms to identify which subpopulations with AD/ADRD are most vulnerable with respect to several individual- and community-level factors (e.g., sex, chronic conditions, race/ethnicity, frailty). Next, we will estimate vulnerability of older persons with AD/ADRD to air pollution including wildfire smoke using our state-of-the-science approach to estimate air pollution and wildfire smoke exposure. We then estimate the impacts and vulnerabilities from co-occurring heat and air pollution (including heat waves and wildfire smoke) by developing Bayesian hierarchical spatio-temporal models to quantify synergistic effects. Finally, we will disseminate all methods, exposure data, and statistical software, making them publicly available free of charge. Characterizing the factors that increase vulnerability for older persons with AD/ADRD will allow decisionmakers to design effective interventions. Findings will inform impact assessments of climate change, which is anticipated to increase heat and air pollution including wildfires, and for understanding environmental health disparities (i.e., environmental justice). Our results will have implications for management of health during co-occurring heat and air pollution events, including wildfires, and increase knowledge on weather and air pollution preparedness, response, and recovery.

世界卫生组织将空气污染和气候变化列为2019年十大威胁之二，此前的研究 此外，还表明了气候变化暴露与大脑健康之间的联系。 预计到 2060 年，阿尔茨海默病 (AD) 和相关痴呆症 (ADRD) 将翻一番，其中最大的 与此同时，拉美裔美国人的野火频率、强度和持续时间也在增加。 总之，气候变化对环境的影响可能会成为我们正在面临的大脑健康紧急情况 迄今为止，人们对高温或空气污染（包括野火烟雾）的影响知之甚少。 大多数关于气候变化相关脆弱性的研究都调查了单一因素。 一次而不是具有多种因素（同时发生的空气污染和 此外，之前的研究并未 利用卫星图像、机器学习和因果推理方法的最新发展， 可以提高统计分析的严谨性和有效性。我们建议使用以下方法来解决这些科学差距。 大量经过验证的美国医疗保险受益人（>65 岁）患有 AD/ADRD（同期约 1000 万） 2000-2019）以及空间分辨的天气数据与最先进的机器学习相结合 空气污染暴露的估计，利用卫星图像、土地利用数据和监测。 长期目标是描述气候变化相关暴露的脆弱性和健康影响 首先，我们将评估短期暴露在高温下的影响。 和热浪对特定原因入院、再入院、死亡率的影响，以及一种以患者为中心的新型方法 在家的日子的结果，并开发机器学习算法来识别哪些亚人群 AD/ADRD 最容易受到一些个人和社区层面的因素（例如性别、 接下来，我们将评估患有 AD/ADRD 的老年人的脆弱性。 空气污染，包括野火烟雾，使用我们最先进的方法来估计空气污染和 然后，我们评估同时发生的热量和空气的影响和脆弱性。 通过开发贝叶斯分层时空模型来污染（包括热浪和野火烟雾） 最后，我们将传播所有方法、暴露数据和统计数据。 软件，使它们免费公开，描述增加漏洞的因素。 对于患有 AD/ADRD 的老年人，研究结果将使决策者能够设计有效的干预措施。 为气候变化的影响评估提供信息，预计气候变化将增加热量和空气污染，包括 野火，并了解环境健康差异（即环境正义）。 对同时发生的高温和空气污染事件期间的健康管理产生影响，包括 野火，并增加有关天气和空气污染准备、响应和恢复的知识。