ArticleJournal of the International Neuropsychological Society : JINS2018
Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.
Article in Journal of the International Neuropsychological Society : JINS, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 30 citations in OpenAlex.
- Cognitive aging across the life course in a low-income context: evidence from Malawi.International journal of epidemiology · 2026Article
- Cognitive profiles among dementia-free older adults and their associations with neuroimaging markers.Brain imaging and behavior · 2025Article
- Cognitive Trajectories and Associated Social and Behavioral Determinants Among Racial/Ethnic Minority Older Adults in the United States.The Gerontologist · 2024Article
- Place of care in the last three years of life for Medicare beneficiaries.BMC geriatrics · 2024Article
- Multimorbidity patterns in dementia and mild cognitive impairment.Frontiers in psychiatry · 2024Article
- Signatures of Neuropsychological Test Results in the Long Life Family Study: A Cluster Analysis.Journal of Alzheimer's disease : JAD · 2023Article
- Resilience resources may buffer some middle-aged and older Black Americans from memory decline despite experiencing discrimination.Social science & medicine (1982) · 2023Article
- Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods.Journal of Alzheimer's disease : JAD · 2022Article
- Using Mixture Modeling to Construct Subgroups of Cognitive Aging in the Wisconsin Longitudinal Study.The journals of gerontology. Series B, Psychological sciences and social sciences · 2021Article
- A coordinated analysis of the associations among personality traits, cognitive decline, and dementia in older adulthood.Journal of research in personality · 2021Article
- Latent Cognitive Class at Enrollment Predicts Future Cognitive Trajectories of Decline in a Community Sample of Older Adults.Journal of Alzheimer's disease : JAD · 2021Article
- Detecting biological heterogeneity patterns in ADNI amnestic mild cognitive impairment based on volumetric MRI.Brain imaging and behavior · 2020Article
- Extensive memory testing improves prediction of progression to MCI in late middle age.Alzheimer's & dementia (Amsterdam, Netherlands) · 2020Article
- Cognitive aging is not created equally: differentiating unique cognitive phenotypes in "normal" adults.Neurobiology of aging · 2019Article
- Subtypes Based on Neuropsychological Performance Predict Incident Dementia: Findings from the Rush Memory and Aging Project.Journal of Alzheimer's disease : JAD · 2019Article
- Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.Journal of Alzheimer's disease : JAD · 2018Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivesThe aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity.
methodsWe applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation.
resultsThe sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes.
conclusionsLC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).
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