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Fraser MA, Walsh EI, Shaw ME, Abhayaratna WP, Anstey KJ, Sachdev PS, Cherbuin N. Longitudinal trajectories of hippocampal volume in middle to older age community dwelling individuals. Neurobiol Aging 2020; 97:97-105. [PMID: 33190123 DOI: 10.1016/j.neurobiolaging.2020.10.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 09/04/2020] [Accepted: 10/12/2020] [Indexed: 12/11/2022]
Abstract
Understanding heterogeneity in brain aging trajectories is important to estimate the extent to which aging outcomes can be optimized. Although brain changes in late life are well-characterized, brain changes in middle age are not well understood. In this study, we investigated hippocampal change in a generally healthy community-living population of middle (n = 421, mean age 47.2 years) and older age (n = 411, mean age 63.0 years) individuals, over a follow-up of up to 12 years. Manually traced hippocampal volumes were analyzed using multilevel models and latent class analysis to investigate longitudinal aging trajectories and laterality and sex effects, and to identify subgroups that follow different aging trajectories. Hippocampal volumes decreased on average by 0.18%/year in middle age and 0.3%/year in older age. Men tended to experience steeper declines than women in middle age only. Three subgroups of individuals following different trajectories were identified in middle age and 2 in older age. Contrary to expectations, the subgroup containing two-thirds of older age participants maintained stable hippocampal volumes across the follow-up.
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Affiliation(s)
- Mark A Fraser
- Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia.
| | - Erin I Walsh
- Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia; Population Health Exchange, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Marnie E Shaw
- ANU College of Engineering & Computer Science, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Walter P Abhayaratna
- College of Health & Medicine, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Kaarin J Anstey
- Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia; Ageing Futures Institute, University of New South Wales, Sydney, New South Wales, Australia; Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
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Sagan A, Łapczyński M. SEM-Tree hybrid models in the preferences analysis of the members of Polish households. ADV DATA ANAL CLASSI 2020. [DOI: 10.1007/s11634-020-00414-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
AbstractThe purpose of the paper is to identify the dimensions of the strategy of resources allocation of Polish households members and test the hypothesis concerning risky shift effect in the relationship between strategy of family decision making and trade-off in family scarce resources allocation. These dimensions were identified on the basis of nationwide empirical data gathered on a representative sample of 1020 respondents nested in 410 households. SEM-Tree hybrid models are used in the analysis of the results, which combine the confirmatory structural equation models with exploratory and predictive classification and regression trees. This allows to apply structural modeling for the study of heterogeneous populations and to assess the hierarchical impact of exogenous predictors on the identification of segments with separate and unique model structural parameters. The approach combines the advantages of a model approach (at the stage of constructing hypotheses on structural relationships and specifications of measurement models) and exploration-based data (at the stage of recursive division of the sample).
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