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，预期寿命增加