Literature DB >> 12227921

Sources of influence on rate of cognitive change over time in Swedish twins: an application of latent growth models.

Chandra A Reynolds1, Deborah Finkel, Margaret Gatz, Nancy L Pedersen.   

Abstract

The use of latent growth models to examine influence on individual differences on ability level versus rate of change were examined for measures of fluid ability, memory, and perceptual speed in a sample of twins from the Swedish Adoption/Twin Study of Aging. Results indicated a larger amount of individual variation for average ability level (i.e., intercept) than rate of change (i.e., slope) for all three traits: Block Design, Thurstone's Picture Memory, and Symbol Digit. Generally, genetic influences were of greater importance to individual variation in ability level whereas variation for rate of change exhibited a larger environmental component. These findings support theories of increasing environmental influences with age. When genetic and environmental sources of covariation between educational attainment and pulmonary function with latent growth parameters were considered, the sources of covariation between the latent cognitive growth model parameters (i.e., intercept and slope) and both covariates were primarily genetic for ability level (intercepts) but environmental for rate of change (slopes). Such findings suggest that the forces important to timing or entry into cognitive decline may reflect stochastic processes or external environmental factors, primarily nonshared, that may differentially hasten cognitive decline in twins. These same forces may overlap with those that influence higher or lower educational attainment or those leading to better or worse pulmonary functioning.

Mesh:

Year:  2002        PMID: 12227921     DOI: 10.1080/03610730290103104

Source DB:  PubMed          Journal:  Exp Aging Res        ISSN: 0361-073X            Impact factor:   1.645


  19 in total

1.  Both odor identification and ApoE-ε4 contribute to normative cognitive aging.

Authors:  Deborah Finkel; Chandra A Reynolds; Maria Larsson; Margaret Gatz; Nancy L Pedersen
Journal:  Psychol Aging       Date:  2011-04-25

2.  Cognitive engagement and cognitive aging: is openness protective?

Authors:  Emily Schoenhofen Sharp; Chandra A Reynolds; Nancy L Pedersen; Margaret Gatz
Journal:  Psychol Aging       Date:  2010-03

Review 3.  Genetic architecture of declarative memory: implications for complex illnesses.

Authors:  Carrie E Bearden; Katherine H Karlsgodt; Peter Bachman; Theo G M van Erp; Anderson M Winkler; David C Glahn
Journal:  Neuroscientist       Date:  2011-08-10       Impact factor: 7.519

4.  [Genetic aspects of cognitive abilities across the life span].

Authors:  F Poustka; W Maier
Journal:  Nervenarzt       Date:  2009-11       Impact factor: 1.214

5.  Etiology of Stability and Growth of Internalizing and Externalizing Behavior Problems Across Childhood and Adolescence.

Authors:  Alexander S Hatoum; Soo Hyun Rhee; Robin P Corley; John K Hewitt; Naomi P Friedman
Journal:  Behav Genet       Date:  2018-04-20       Impact factor: 2.805

6.  Does the direction and magnitude of cognitive change depend on initial level of ability?

Authors:  Timothy A Salthouse
Journal:  Intelligence       Date:  2012-03-07

Review 7.  Item response theory facilitated cocalibrating cognitive tests and reduced bias in estimated rates of decline.

Authors:  Paul K Crane; Kaavya Narasimhalu; Laura E Gibbons; Dan M Mungas; Sebastien Haneuse; Eric B Larson; Lewis Kuller; Kathleen Hall; Gerald van Belle
Journal:  J Clin Epidemiol       Date:  2008-05-05       Impact factor: 6.437

Review 8.  The impact of genetic research on our understanding of normal cognitive ageing: 1995 to 2009.

Authors:  Antony Payton
Journal:  Neuropsychol Rev       Date:  2009-09-19       Impact factor: 7.444

9.  A biometric latent curve analysis of memory decline in older men of the NAS-NRC twin registry.

Authors:  John J McArdle; Brenda L Plassman
Journal:  Behav Genet       Date:  2009-04-29       Impact factor: 2.805

10.  A random change point model for assessing variability in repeated measures of cognitive function.

Authors:  Annica Dominicus; Samuli Ripatti; Nancy L Pedersen; Juni Palmgren
Journal:  Stat Med       Date:  2008-11-29       Impact factor: 2.373

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