The overall goal of this project is to examine whether cognitive status and cognitive change in middle age are predictive of rate of subsequent decline. While stability is the normative pattern for most mental abilities in midlife, longitudinal studies of normal aging have reported subgroups of middle-aged adults who show reliable decline or improvement on specific cognitive abilities. Adults who exhibit early decline in midlife on select abilities may be at higher risk for an accelerated rate of cognitive decline in old age. Study participants (N = 698) are members from the Seattle Longitudinal Study (SLS) with longitudinal cognitive data obtained during midlife. Midlife cognitive change data has been used to identify patterns of change and to develop Midlife Cognitive Risk criteria for three domains: Episodic memory. Executive functioning, and Processing Speed. The impact of midlife cognition is being studied for two cohorts. For the Older Cohort (b1914 - 1941;M age = 77;N = 270), cognitive data are available in midlife and also in old age. For the Middle Age cohort (b1942 - 1969);N = 428;M age = 59) cognitive change data are available in midlife and early old age. The sample is further characterized by neuropsychological assessment, APO-E genotyping, and health histories. To examine the association of brain volume and cognitive change, rate of atrophy in the hippocampus, entorhinal cortex, prefrontal cortex and frontal white matter are being assessed by structural MRI at.four occasions..Xongitudinal..data.on.participants'engagement in stimulating cognitive activities is also being studied as a mediator of cognitive change.
This study examines factors associates with the long preclinical phases of dementia. Earlier detection of individuals at risk for cognitive impairment would potentially beneift not only those individuals but also society who bears the cost for care of the cognitively impaired.
|de Frias, Cindy M; Schaie, K Warner; Willis, Sherry L (2014) Hypertension moderates the effect of APOE on 21-year cognitive trajectories. Psychol Aging 29:431-9|
|Madhyastha, Tara M; Grabowski, Thomas J (2014) Age-related differences in the dynamic architecture of intrinsic networks. Brain Connect 4:231-41|
|Borghesani, Paul R; Madhyastha, Tara M; Aylward, Elizabeth H et al. (2013) The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging. Neuropsychologia 51:1435-44|
|Zanjani, Faika; Downer, Brian G; Kruger, Tina M et al. (2013) Alcohol effects on cognitive change in middle-aged and older adults. Aging Ment Health 17:12-23|
|Gerstorf, Denis; Ram, Nilam; Hoppmann, Christiane et al. (2011) Cohort differences in cognitive aging and terminal decline in the Seattle Longitudinal Study. Dev Psychol 47:1026-41|
|Hoppmann, Christiane A; Gerstorf, Denis; Willis, Sherry L et al. (2011) Spousal interrelations in happiness in the Seattle Longitudinal Study: considerable similarities in levels and change over time. Dev Psychol 47:1-8|
|Borghesani, Paul R; Weaver, Kurt E; Aylward, Elizabeth H et al. (2010) Midlife memory improvement predicts preservation of hippocampal volume in old age. Neurobiol Aging :|
|Schaie, K Warner (2009) "When does age-related cognitive decline begin?" Salthouse again reifies the "cross-sectional fallacy". Neurobiol Aging 30:528-9;discussion 530-33|
|Willis, Sherry L; Schaie, K Warner (2009) Cognitive training and plasticity: theoretical perspective and methodological consequences. Restor Neurol Neurosci 27:375-89|
|Revell, Andrew J; Caskie, Grace I L; Willis, Sherry L et al. (2009) Factor structure and invariance of the Quality of Life in Alzheimer's Disease (QoL-AD) Scale. Exp Aging Res 35:250-67|
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