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Background Aging is associated with an increasing risk of decline in cognitive abilities. The decline is, however, not a homogeneous process. There are substantial differences across individuals although previous investigations have identified individuals with distinct cognitive trajectories. Evidence is accumulating that lifestyle contributes significantly to the classification of individuals into various clusters. How and whether genetically related individuals, like twins, change in a more similar manner is yet not fully understood. Methods In this study, we fitted growth mixture models to Mini Mental State Exam (MMSE) scores from participants of the Swedish OCTO twin study of oldest-old monozygotic and same-sex dizygotic twins with the purpose of investigating whether twin pairs can be assigned to the same class of cognitive change. Results We identified four distinct groups (latent classes) whose MMSE trajectories followed different patterns of change over time: two classes of high performing individuals who remained stable and declined slowly, respectively, a group of mildly impaired individuals with a fast decline and a small group of impaired individuals who declined more rapidly. Notably, our analyses show no association between zygosity and class assignment. Conclusions Our study provides evidence for a more substantial impact of environmental, rather than genetic, influences on cognitive change trajectories in later life. [ABSTRACT FROM AUTHOR]

Background Cognitive dispersion, or inconsistencies in performance across cognitive domains, has been posited as a cost-effective tool to predict conversion to dementia in older adults. However, there is a dearth of studies exploring cognitive dispersion in the oldest-old (>80 years) and its relationship to dementia incidence. Objective The main aim of this study was to examine whether higher cognitive dispersion at baseline was associated with dementia incidence within an 8-year follow-up of very old adults, while controlling for established risk factors and suggested protective factors for dementia. Methods Participants (n  = 468) were from the Origins of Variance in the Old-Old: Octogenarian Twins study, based on the Swedish Twin Registry. Cox regression analyses were performed to assess the association between baseline cognitive dispersion scores and dementia incidence, while controlling for sociodemographic variables, ApoEe4 carrier status, co-morbidities, zygosity and lifestyle engagement scores. An additional model included a composite of average cognitive performance. Results Cognitive dispersion and ApoEe4 were significantly associated with dementia diagnosis. These variables remained statistically significant when global cognitive performance was entered into the model. Likelihood ratio tests revealed that cognitive dispersion and cognitive composite scores entered together in the same model was superior to either predictor alone in the full model. Conclusions The study underscores the usefulness of cognitive dispersion metrics for dementia prediction in the oldest-old and highlights the influence of ApoEe4 on cognition in very late age. Our findings concur with others suggesting that health and lifestyle factors pose little impact upon cognition in very advanced age. [ABSTRACT FROM AUTHOR]

Background: vascular cognitive impairment no dementia (VCI-ND) defines a preclinical phase of cognitive decline associated with vascular disorders. The neuropsychological profile of VCI-ND may vary according to different vascular conditions. Objective: to determine the neuropsychological profile of individuals with no dementia and vascular disorders, including hypertension, peripheral vascular disease (PVD), coronary heart disease (CHD), diabetes and stroke. Risk of 2-year incident dementia in individuals with disease and cognitive impairment was also tested. Methods: participants were from the Cognitive Function and Ageing Study. At baseline, 13,004 individuals aged ≥65 years were enrolled into the study. Individuals were grouped by baseline disorder status (present, absent) for each condition. Cognitive performance was assessed using the Mini Mental State Examination (MMSE) and the Cambridge Cognitive Examination (CAMCOG). Dementia was assessed at 2 years. Results: in the cross-sectional analysis, hypertension, PVD and CHD were not associated with cognitive impairment. Stroke was associated with impaired global (MMSE) and CAMCOG sub-scale (including memory and non-memory) scores. Diabetes was associated with impairments in global cognitive function (MMSE) and abstract thinking. In the longitudinal analysis, cognitive impairments were associated with incident dementia in all groups. Conclusion: the neuropsychological profile in individuals with vascular disorders depends on the specific condition investigated. In all conditions cognitive impairment is a risk factor for dementia. A better understanding of which cognitive domains are affected in different disease groups could help improve operationalisation of the neuropsychological criteria for VCI-ND and could also aid with the development of dementia risk prediction models in persons with vascular disease. [ABSTRACT FROM AUTHOR]

Background: criteria for mild cognitive impairment (MCI) capture an intermediate cognitive state between normal ageing and dementia, associated with increased dementia risk. Whether criteria for MCI are applicable in the context of stroke and can be used to predict dementia in stroke cases is not known.Objectives: to determine the prevalence of MCI in individuals with stroke and identify predictors of 2-year incident dementia in stroke cases.Methods: individuals were from the Medical Research Council Cognitive Function and Ageing Study. MCI prevalence in individuals with stroke was determined. Logistic regression, with receiver operating characteristic curve analysis, was used to identify variables associated with risk of dementia in stroke cases including MCI criteria, demographic, health and lifestyle variables.Findings: of 2,640 individuals seen at the first assessment, 199 reported stroke with no dementia. In individuals with stroke, criteria for MCI are not appropriate, with less than 1% of stroke cases being classified as having MCI. However, in individuals with stroke two components of the MCI definition, subjective memory complaint and cognitive function (memory and praxis scores) predicted 2-year incident dementia (area under the curve = 0.85, 95% CI: 0.77–0.94, n = 113).Conclusion: criteria for MCI do not appear to capture risk of dementia in the context of stroke in the population. In stroke cases, subjective and objective cognitive performance predicts dementia and these variables could possibly be incorporated into dementia risk models for stroke cases. Identifying individuals with stroke at greatest risk of dementia has important implications for treatment and intervention. [ABSTRACT FROM AUTHOR]

Background: the investigation of cognitive decline in the older population has been hampered by analytical considerations. Most studies of older people over prolonged periods suffer from loss to follow-up, yet this has seldom been investigated fully to date. Such considerations limit our understanding of how basic variables such as education can affect cognitive trajectories. Methods: we examined cognitive trajectories in a population-based cohort study in Cambridge, UK, of people aged 75 and over in whom multiple interviews were conducted over time. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Socio-demographic variables were measured, including educational level and social class. An age-based quadratic latent growth model was fitted to cognitive scores. The effect of socio-demographic variables was examined on all latent variables and the probability of death and dropout. Results: at baseline, age, education, social class and mobility were associated with cognitive performance. Education and social class were not related to decline or its rate of change. In contrast, poor mobility was associated with lower cognitive performance, increased cognitive decline and increased rate of change of cognitive decline. Gender, age, mobility and cognitive ability predicted death and dropout Conclusions: contrary to much of the current literature, education was not related to rate of cognitive decline or change in this rate as measured by MMSE. Higher levels of education do not appear to protect against cognitive decline, though if the MMSE is used in the diagnostic process, individuals with less education may be diagnosed as having dementia somewhat earlier. [ABSTRACT FROM AUTHOR]