Population subgroup difference in aging trajectory and health: Methods and application

老龄化轨迹和健康状况的人口亚组差异：方法与应用

• 批准号: 10043031
• 负责人: Serkalem Demissie
• 金额: $ 25.8万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-10 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10043031
• 关键词: Accounting; Address; African American; Age; Age of Onset; Aging; Alaska Native; Algorithms; American Indians; Area; Asians; Biological; Biological Markers; Biology of Aging; Blood Pressure; Characteristics; Chronic Disease; Chronology; Creatinine; Data; Development; Disease; Disease Progression; Elderly; Electronic Health Record; Ethnic Origin; Future; Gender; Genomics; Goals; Health; Health Care Costs; Health behavior; Health trends; Healthcare; Healthcare Systems; Heterogeneity; Hispanics; Individual; Intervention; Investigation; Knowledge; Life Expectancy; Link; Longitudinal Studies; Measures; Medical; Methodology; Methods; Modeling; Morbidity - disease rate; NIH Program Announcements; Native Hawaiian; Not Hispanic or Latino; Onset of illness; Outcome; Pacific Island Americans; Phenotype; Physiological; Population; Population Group; Population Heterogeneity; Public Health; Quality of life; Race; Research; Research Design; Resources; Risk Factors; Serum; Societies; Socioeconomic Factors; Statistical Methods; Stress; Subgroup; System; Testing; Veterans; Woman; Work; age related; base; biological research; cohort; demographics; design; direct application; disability; epidemiology study; ethnic difference; follow-up; functional decline; health care needs assessment; health difference; human old age (65+); implementation strategy; improved; insight; men; middle age; novel strategies; potential biomarker; prevent; public health relevance; risk prediction model; study population; tool; young adult

SUMMARY: Despite the substantial increase in healthcare spending and increase in life expectancy among older adults, more than two-thirds live with multiple age-related chronic diseases. Chronic diseases account for 75% of the health care costs and resource utilization. Estimates show that the number of older adults (age ≥65) in the U.S. will almost double and become considerably more diverse by 2060. Despite the projected demographic changes, and the implications for public health and the health care system, our understanding of aging and the mechanisms that link aging to age-related conditions, and how they differ by gender, chronological age (CA) (in the young-adult, middle-age, young-old, the old, and the oldest-old), and race- ethnicity remains incomplete. Improved insights into aging and health, and differences in population subgroups are therefore essential. The long-term goal of our proposed work is to improve the quality of life among older adults by reducing age-related disability and morbidity. While CA is the main risk factor for many chronic illnesses, there is clear evidence that the rate of aging, manifested in decline of function in physiological systems and referred to as biological age (BA), differs significantly between individuals of the same CA. Thus, researching BA is essential. BA is not directly measureable, but inferred from potential biomarkers of aging. Although various approaches exist to quantify BA, accurate estimation remains a challenge. There are methodological gaps and clear opportunities for improvement. For example, Klemera–Doubal's model, the most widely used tool, assumes linear relationships between biomarkers and age and its application for longitudinal data and heterogeneous population subgroups is unexplored. The objectives of this proposed study are to develop an improved method for BA estimation, and examine differences in aging trajectory and its determinants and outcomes by gender, age, and race-ethnicity. Our central hypothesis is that we will achieve significant improvement in BA estimation by employing generalized additive models that allow modeling a broad class of linear and nonlinear relationships, using a longitudinal study design, and accommodating population subgroup differences. This, in turn, will permit a more effective investigation of aging and its risk factors and outcomes. We will test the central hypothesis using two specific aims. Aim 1: Develop a new and improved algorithm for more accurate estimation of BA; Aim 2: Quantify aging and evaluate potential determinants of accelerated aging according to key demographics. The ability to estimate BA accurately can have profound implications, including a direct application in the investigation of aging mechanisms and prediction of future onset of age-related conditions. Our findings in diverse population subgroups can improve the scope of our understanding of health trends and differences among older adults, and inform population-specific health care needs assessment and implementation strategies.

摘要：尽管医疗保健支出大幅增加并且预期寿命延长 在老年人中，三分之二以上患有多种与年龄相关的慢性疾病。 75%的医疗保健费用和资源利用的估计显示，老年人的数量（年龄）。 到 2060 年，美国的人口数量将几乎翻倍，并且变得更加多样化。尽管预计 人口变化，以及对公共卫生和医疗保健系统的影响，我们对 衰老以及将衰老与年龄相关疾病联系起来的机制，以及它们在性别上的差异， 实际年龄（CA）（青壮年、中年、青壮年、老年和最年老）和种族 对老龄化和健康以及人口亚群体差异的深入了解仍然不完整。 因此，我们提出的工作的长期目标是改善老年人的生活质量。 通过减少与年龄相关的残疾和发病率来改善成年人的健康，而 CA 是许多慢性病的主要危险因素。 疾病，有明确的证据表明衰老的速度，表现为生理功能的衰退 系统并称为生物年龄（BA），同一 CA 的个体之间存在显着差异。 研究 BA 是至关重要的。 BA 不能直接测量，而是从潜在的衰老生物标志物中推断出来。 尽管存在多种量化 BA 的方法，但准确估计仍然是一个挑战。 方法上的差距和明确的改进机会，例如，Klemera-Doubal 模型， 最广泛使用的工具，假设生物标志物和年龄之间的线性关系及其应用 纵向数据和异质人口亚组尚未探讨该提议的目标。 研究的目的是开发一种改进的 BA 估计方法，并检查老化轨迹和 性别、年龄和种族的决定因素和结果我们的中心假设是我们会。 通过采用广义相加模型实现 BA 估计的显着改进，该模型允许 使用纵向研究设计对广泛的线性和非线性关系进行建模，以及 反过来，这将允许更有效地调查人口亚组差异。 我们将使用两个具体目标来检验中心假设： 开发一种新的改进算法，以更准确地估计 BA；目标 2：量化老化和 根据关键人口统计数据评估加速老龄化的潜在决定因素。 BA 准确地可以产生深远的影响，包括直接应用于衰老研究 我们在不同人群中的研究结果。 亚组可以提高我们对老年人健康趋势和差异的理解， 并为特定人群的医疗保健需求评估和实施策略提供信息。