Patterns and Predictors of Cognitive Decline

认知能力下降的模式和预测因素

Patterns and Predictors of Cognitive Decline Cognitive decline leading to mild cognitive impairments and dementia is an increasingly common and important cause of disability and decreased quality of life for older Americans. The expected growth in the number of older adults with cognitive impairment and dementia will also place an increasing burden on families, the health care system, and social programs, such as Medicare. Given this wide-ranging impact, it is important to understand the patterns and predictors of cognitive decline in older Americans. The proposed studies will: 1) provide new information on the longitudinal trajectories of cognitive decline over a 12-year period in a nationally representative sample of older Americans; and 2) identify risk factors from across the life span (childhood, middle-age, and older-age) that increase the likelihood for developing cognitive impairment and dementia as one ages. To perform these studies we will use unique linked population-based data from the NIA-funded Health and Retirement Study (MRS) (N~22,000; 1992 - 2004), the MRS supplemental Aging, Demographics, and Memory Study (ADAMS) (N=856, 2001 - 2005), as well as linked Medicare administrative data for ADAMS subjects (1986-2002). Latent growth curve modeling techniques using biennial MRScognitive tests from 1992 - 2004 will allow the identification of the longitudinal trajectory of cognitive decline among those diagnosed in the ADAMS with normal cognitive function, cognitive impairment, or dementia. Detailed data on: cardiovascular risk factors; acute medical events and surgical interventions; childhood and adult poverty, and the extent of social networks and social engagement will be used in nested case-control studies to test hypotheses regarding life-long risks for cognitive decline. These studies will provide a better understanding of the patterns and predictors of cognitive decline in a nationally representative sample of older adults and, therefore, allow more informed health care planning and policy-making. In addition, a better understanding of the relative importance of medical, behavioral, and socioeconomic factors that are risks for cognitive decline and dementia will help clinicians and policy-makers target high-risk groups, implement interventions to prevent or slow cognitive decline, and better assess the cost-effectiveness of current and future interventions.