Latent Growth Curve Models of Cognitive Aging

认知衰老的潜在增长曲线模型

• 批准号: 6761731
• 负责人: Duane F Alwin
• 金额: $ 25.59万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-30 至 2006-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6761731
• 关键词: academic achievement; aging; clinical research; cognition; developmental psychology; functional ability; human data; human middle age (35-64); human old age (65+); longitudinal human study; mathematical model; model design /development; performance

DESCRIPTION (provided by applicant): This research applies strategies of latent growth curve (LGC) modeling with a structural equation framework to examine intra-individual change in trajectories of cognitive performance in old age and its correlates, particularly age, education, health, and physical and sensory functioning. The proposed work focuses explicitly on the following objectives: to confirm patterns of decline with age across a broad spectrum of mental abilities using both crosssectional and longitudinal assessments of cognitive performance in nationally representative samples of the older population; to ascertain the extent to which cross-sectional age-differences in cognitive functioning are spuriously due to cohort-related factors, such as level of schooling, or other age-related phenomena, e.g., comorbidity and sensory functioning; to assess the age-related intra-individual trajectories of several measures of cognitive functioning as well as age-linked covariates such as comorbidity, other social and physical functioning, and sensory functioning using longitudinal data over periods of time of up to seven years; to assess the extent to which age-related declines in sensory impairment and health explain the link between aging and cognitive functioning in middle-aged and older adults, net of education and comorbidity; and to assess how patterns of cognitive decline and its covariates differ by sex and race/ethnicity in older adults. We investigate these issues using two innovative nationally-representative panel surveys of middle-aged and older adults: the original HRS (Health and Retirement Study) national panel study of preretirement men and women aged 51-61 assessed in 1992 (n=9,824) and reinterviewed in 1994, 1996, 1998 and 2000, and the parallel AHEAD (Study of Asset and Health Dynamics Among the Oldest Old) national panel study which interviewed adults aged 70 and above in 1993 (n=7,443) and reinterviewed in 1995, 1998 and 2000. The key elements of our design allow us to: (1) generalize to a national population of middle-aged and older individuals sampled using probability methods; (2) assess differences between birth cohorts in the processes studied; (3) assess occasion-based age changes in the population to estimate the nature and shape of intra-individual change; (4) assess inter-individual and inter-cohort differences in intra-individual change; (5) build synthetic cohort models of accelerated age-based change using the multiple cohort feature of the panel design; (6) assess the effects of fixed covariates and appropriately lagged timevarying covariates on individual differences in age-related change; and (7) assess the extent of bias in these aging functions introduced by problems of sample attrition and/or mortality.

描述(申请人提供)：这项研究应用潜在成长曲线(LGC)建模的策略和结构方程框架来研究老年人认知表现轨迹的个体内变化及其相关因素，特别是年龄、教育、健康以及身体和感觉功能。拟议的工作明确侧重于以下目标：使用对具有全国代表性的老年人口样本的认知表现的横断面和纵向评估，确认各种智力能力随年龄的下降模式；确定与队列有关的因素，如教育水平，或其他与年龄有关的现象，如共病和感觉功能，在多大程度上虚假地造成了认知功能的横断面年龄差异；使用长达七年的纵向数据，评估一些认知功能指标以及与年龄相关的协变量，如共病、其他社会和身体功能以及感觉功能的与年龄有关的个人内部轨迹；评估与年龄有关的感觉损害和健康下降在多大程度上解释了中老年人衰老和认知功能之间的联系，扣除教育和共病；以及评估老年人的认知衰退模式及其协变量如何因性别和种族/族裔而不同。 我们使用了两个具有全国代表性的创新的中老年人小组调查来调查这些问题：最初的HRS(健康和退休研究)国家小组研究，对51-61岁的退休前男性和女性进行评估(n=9824)，并于1994年、1996年、1998年和2000年重新采访，以及平行的AHEAD(最年长老年人的资产和健康动态研究)国家小组研究，该研究在1993年访问了70岁及以上的成年人(n=7,443)，并于1995年、1998年和2000年重新采访。我们设计的关键要素允许我们：(1)使用概率方法将抽样的中老年个体推广到全国人群；(2)在研究的过程中评估出生队列之间的差异；(3)评估人口中基于时机的年龄变化，以估计个体内变化的性质和形状；(4)评估个体内变化的个体间和队列间的差异；(5)利用小组设计的多队列特征，建立加速基于年龄的变化的合成队列模型；(6)评估固定协变量和适当滞后的时变协变量对年龄相关变化的个体差异的影响；以及(7)评估样本损耗和/或死亡率问题在这些老化函数中引入的偏差程度。