title: Heterogeneity of cognitive profiles in aging: successful aging, normal aging, and individuals at risk for cognitive decline.
abstract: Neuropsychological clinical decision-making is complicated by the fact that variability in test performance increases with advancing age. This research explores the presence of homogeneous subgroups in 120 neurologically healthy individuals, from 55 to 85 years of age. Subjects at risk for dementing diseases were diagnosed as Aging-Associated Cognitive Decline (AACD) and Mild Cognitive Impairment (MCI). Cluster analysis was applied on 11 neuropsychological variables assessing logical memory immediate recall and retention percentage, visual memory immediate recall and retention, conceptual thinking, naming, verbal fluency, constructional functions, motor speed, flexibility and finger tapping. Five clusters were extracted, one representing cognitively successfully aged, and two consisting of individuals with normal or average level of performance. One cluster was characterized by older subjects with difficulties in visual memory, visuoconstructional functions, and speed and attention, most of the younger subjects in the same cluster had a diagnosis of AACD or MCI. The fifth cluster represented individuals at risk for dementing diseases; most of them were diagnosed having AACD and more than half had a diagnosis of MCI. Age, activity and intellectual levels, and to a lesser degree education, were significantly related to the cluster solution. The present findings caution against treating samples of elderly individuals as homogeneous.
authors.affiliation: Neuropsychological Unit, Department of Clinical Neurosciences, P.O. Box 300, Helsinki University Central Hospital, Helsinki, Finland. raija.ylikoski@HUCH.fi
authors.forename: R
authors.initials: R
authors.lastname: Ylikoski
authors.forename: A
authors.initials: A
authors.lastname: Ylikoski
authors.forename: P
authors.initials: P
authors.lastname: Keskivaara
authors.forename: R
authors.initials: R
authors.lastname: Tilvis
authors.forename: R
authors.initials: R
authors.lastname: Sulkava
authors.forename: T
authors.initials: T
authors.lastname: Erkinjuntti
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology* / Q000523:psychology*; D016000:Cluster Analysis; D003071:Cognition / Q000502:physiology*; D003072:Cognition Disorders / Q000209:etiology* / Q000503:physiopathology / Q000523:psychology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D011597:Psychomotor Performance / Q000502:physiology; D012307:Risk Factors