Funded Research
Latent Growth Curve Models of Cognitive Aging
Source: NIH/NIA
Active: 9/1/2007 - 8/31/2010
Investigator(s):
Duane Alwin
Scott Hofer (Oregon State University)
Linda Wray
This project investigates the linkage between age-related cognitive change and indicators of health, health behaviors and disability in a set of nationally representative samples of community dwelling respondents in the U.S. population. The data used were obtained from the 1992-2006 Health and Retirement Study (HRS) national panel study of men and women in birth cohorts born pre-1900 through 1954. This project is a continuation of an R01 focusing on age-gradients, cohort effects, and the role of schooling for measures of cognitive status assessed in the HRS samples over several waves. We propose to use an HRS sample that includes two additional waves of repeated measures and to extend our prior focus to links between age-related cognitive scores, chronic disease, lifestyle behaviors, and functional disability status, and to investigate these issues by sex and race/ethnicity. Over-samples of African-American and Hispanic-American populations makes this possible. The use of growth modeling techniques permits the analysis of the processes of aging from approximately age 50 to 100 in these groups to: (1) confirm patterns of age-related change across a range of cognitive performance measures using more extensive longitudinal assessments of cognitive performance in nationally representative samples of middle-aged and older adults; (2) determine how patterns of cognitive change, as well as change in related variables, differ by sex and race/ethnicity in middle-aged and older adults; (3) test hypotheses regarding age-related trajectories of change in cognitive functioning for groups defined by chronic disease, e.g., type II diabetes, hypertension and stroke; (4) test hypotheses regarding age-related trajectories of cognitive change for various lifestyle behaviors, e.g., alcohol use, cigarette smoking, obesity, and sedentary behaviors; (5) examine models of correlated change with other age-linked outcomes, e.g., physical health, mental health, and activities of daily living (i.e., functional status); (6) assess models of cognitive change in other time-informative metrics, specifically, cognitive change with respect to mortality, e.g., cognitive change in the metric of time until death, or life expectancy; and (7) explore a range of methodological issues, e.g., selection issues, retest effects, censored regression models to handle floor effects, and other models for conceptualizing change.
