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Cognitive Activities During Adulthood Are More Important than Education in Building Reserve

Published online by Cambridge University Press:  05 April 2011

Bruce R. Reed*
Affiliation:
Department of Neurology, School of Medicine, University of California, Davis, California Veterans Administration Northern California Health Care System, Martinez, California
Maritza Dowling
Affiliation:
Department of Biostatistics & Medical Informatics, School of Medicine & Public Health, University of Wisconsin, Madison, Wisconsin
Sarah Tomaszewski Farias
Affiliation:
Department of Neurology, School of Medicine, University of California, Davis, California
Joshua Sonnen
Affiliation:
Department of Pathology, University of Washington, Seattle, Washington
Milton Strauss
Affiliation:
Case Western Reserve University, Cleveland, Ohio
Julie A. Schneider
Affiliation:
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois
David A. Bennett
Affiliation:
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois
Dan Mungas
Affiliation:
Department of Neurology, School of Medicine, University of California, Davis, California
*
Correspondence and reprint requests to: Bruce R. Reed, PhD., UC Davis Alzheimer's Disease Center, 150 Muir Road (127a), Martinez, CA 94553. E-mail: [email protected]

Abstract

Cognitive reserve is thought to reflect life experiences. Which experiences contribute to reserve and their relative importance is not understood. Subjects were 652 autopsied cases from the Rush Memory and Aging Project and the Religious Orders Study. Reserve was defined as the residual variance of the regressions of cognitive factors on brain pathology and was captured in a latent variable that was regressed on potential determinants of reserve. Neuropathology variables included Alzheimer's disease markers, Lewy bodies, infarcts, microinfarcts, and brain weight. Cognition was measured with six cognitive domain scores. Determinants of reserve were socioeconomic status (SES), education, leisure cognitive activities at age 40 (CA40) and at study enrollment (CAbaseline) in late life. The four exogenous predictors of reserve were weakly to moderately inter-correlated. In a multivariate model, all except SES had statistically significant effects on Reserve, the strongest of which were CA40 (β = .31) and CAbaseline (β = .28). The Education effect was negative in the full model (β = –.25). Results suggest that leisure cognitive activities throughout adulthood are more important than education in determining reserve. Discrepancies between cognitive activity and education may be informative in estimating late life reserve. (JINS, 2011, 17, 615–624)

Type
Special Series
Copyright
Copyright © The International Neuropsychological Society 2011

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References

Akbaraly, T.N., Portet, F., Fustinoni, S., Dartigues, J.F., Artero, S., Rouaud, O., Berr, C. (2009). Leisure activities and the risk of dementia in the elderly: results from the Three-City Study. Neurology, 73(11), 854861.CrossRefGoogle ScholarPubMed
Andel, R., Vigen, C., Mack, W.J., Clark, L.J., Gatz, M. (2006). The effect of education and occupational complexity on rate of cognitive decline in Alzheimer's patients. Journal of the International Neuropsychological Society, 12(01), 147152.CrossRefGoogle ScholarPubMed
Bennett, D.A., Schneider, J.A., Arvanitakis, Z., Kelly, J.F., Aggarwal, N.T., Shah, R.C., Wilson, R.S. (2006). Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology, 66(12), 18371844.CrossRefGoogle ScholarPubMed
Bennett, D.A., Schneider, J.A., Bienias, J.L., Evans, D.A., Wilson, R.S. (2005). Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions. Neurology, 64(5), 834841.CrossRefGoogle ScholarPubMed
Bennett, D.A., Schneider, J.A., Buchman, A.S., Mendes de Leon, C., Bienias, J.L., Wilson, R.S. (2005). The Rush Memory and Aging Project: study design and baseline characteristics of the study cohort. Neuroepidemiology, 25(4), 163175.CrossRefGoogle ScholarPubMed
Bennett, D.A., Wilson, R.S., Schneider, J.A., Evans, D.A., Mendes de Leon, C.F., Arnold, S.E., Bienias, J.L. (2003). Education modifies the relation of AD pathology to level of cognitive function in older persons. Neurology, 60(12), 19091915.CrossRefGoogle ScholarPubMed
Borenstein, A.R., Copenhaver, C.I., Mortimer, J.A. (2006). Early-life risk factors for Alzheimer disease. Alzheimer Disease and Associated Disorders, 20(1), 6372.CrossRefGoogle ScholarPubMed
Browne, M., Cudek, R. (1993). Alternate ways of assessing model fit. In K. Bollen & J. Long (Eds.), Testing structural equation models (pp. 136162). Thousand Oaks, CA: Sage.Google Scholar
Crowe, M., Andel, R., Pedersen, N.L., Johansson, B., Gatz, M. (2003). Does participation in leisure activities lead to reduced risk of Alzheimer's disease? A prospective study of Swedish twins. Journal of Gerontology B Psychological Sciences and Social Sciences, 58(5), P249P255.CrossRefGoogle ScholarPubMed
Dowling, N.M., Tomaszewski Farias, S., Reed, B.R., Sonnen, J.A., Strauss, M.E., Schneider, J.A., Mungas, D. (2011). Neuropathological associates of multiple cognitive functions in two community-based cohorts of older adults. Journal of the International Neuropsychological Society (this issue).Google ScholarPubMed
Engvig, A., Fjell, A.M., Westlye, L.T., Moberget, T., Sundseth, Ø., Larsen, V.A., Walhovd, K.B. (2010). Effects of memory training on cortical thickness in the elderly. Neuroimage, 52(4), 16671676.CrossRefGoogle ScholarPubMed
Evans, D.A., Beckett, L.A., Albert, M.S., Hebert, L.E., Scherr, P.A., Funkenstein, H.H., Taylor, J.O. (1993). Level of education and change in cognitive function in a community population of older persons. Annals of Epidemiology, 3(1), 7177.CrossRefGoogle Scholar
Fratiglioni, L., Wang, H.X. (2007). Brain reserve hypothesis in dementia. Journal of Alzheimer's Disease, 12(1), 1122.CrossRefGoogle ScholarPubMed
Gatz, M., Prescott, C.A., Pedersen, N.L. (2006). Lifestyle risk and delaying factors. Alzheimer Disease and Associated Disorders, 20(3 Suppl. 2), S84S88.CrossRefGoogle ScholarPubMed
Hu, L.-T., Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 155.CrossRefGoogle Scholar
Hultsch, D.F., Hertzog, C., Small, B.J., Dixon, R.A. (1999). Use it or lose it: engaged lifestyle as a buffer of cognitive decline in aging? Psychology and Aging, 14(2), 245263.CrossRefGoogle ScholarPubMed
Jöreskog, K.G., Sörbom, D. (1996). LISREL 8: User's reference guide. Chicago: Scientific Software International.Google Scholar
Karp, A., Kareholt, I., Qiu, C., Bellander, T., Winblad, B., Fratiglioni, L. (2004). Relation of education and occupation-based socioeconomic status to incident Alzheimer's disease. American Journal of Epidemiology, 159(2), 175183.CrossRefGoogle ScholarPubMed
Knäuper, B., Wittchen, H.U. (1994). Diagnosing major depression in the elderly: evidence for response bias in standardized diagnostic interviews? Journal of Psychiatric Research, 28(2), 147164.CrossRefGoogle ScholarPubMed
Lachman, M.E., Agrigoroaei, S., Murphy, C., Tun, P.A. (2009). Frequent cognitive activity compensates for education differences in episodic memory. American Journal of Geriatric Psychiatry, 18(1), 410.CrossRefGoogle Scholar
Lindstrom, H.A., Fritsch, T., Petot, G., Smyth, K.A., Chen, C.H., Debanne, S.M., Friedland, R.P. (2005). The relationships between television viewing in midlife and the development of Alzheimer's disease in a case-control study. Brain and Cognition, 58(2), 157165.CrossRefGoogle ScholarPubMed
Muthén, B., Kaplan, D., Hollis, M. (1987). On structural equation modeling with data that are not missing completely at random. Psychometrika, 52(3), 431462.CrossRefGoogle Scholar
Muthén, L.K., Muthén, B.O. (1998) –2007). Mplus user's guide (5th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
Pratt, J.W. (1987). Dividing the indivisible: using simple symmetry to partition variance explained. In T. Pukkila & S. Puntanen (Eds.), Proceedings of the Second International Conference in Statistics (pp. 245260). Tampere, Finland: University of Tampere.Google Scholar
Reed, B.R., Mungas, D., Tomaszewski Farias, S., Harvey, D., Beckett, L., Widaman, K.F., DeCarli, C. (2010). Measuring cognitive reserve based on the decomposition of episodic memory variance. Brain, 133(Pt 8), 21962209.CrossRefGoogle ScholarPubMed
Schmand, B., Smit, J.H., Geerlings, M.I., Lindeboom, J. (1997). The effects of intelligence and education on the development of dementia. A test of the brain reserve hypothesis. Psychological Medicine, 27(6), 13371344.CrossRefGoogle ScholarPubMed
Schumacker, R.E., Lomax, R.G. (1996). A beginner's guide to structural equation modeling. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc.Google Scholar
Soricelli, R.L. (2006). Medicine and the arts. A series of self portraits by William Utermohlen. Commentary. Academic Medicine, 81(11), 996997.Google Scholar
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47(10), 20152028.CrossRefGoogle ScholarPubMed
Thomas, D.R., Hughes, E., Zumbo, B.D. (1998). On variable importance in linear regression. Social Indicators Research, 45, 253275.CrossRefGoogle Scholar
Thomas, D.R., Zhu, P., Decady, Y.J. (2007). Point estimates and confidence intervals for variable importance in multiple linear regression. Journal of Educational and Behavioral Statistics, 32, 6191.CrossRefGoogle Scholar
Valenzuela, M.J., Sachdev, P. (2006a). Brain reserve and cognitive decline: a non-parametric systematic review. Psychological Medicine, 36(8), 10651073.CrossRefGoogle ScholarPubMed
Valenzuela, M.J., Sachdev, P. (2006b). Brain reserve and dementia: a systematic review. Psychological Medicine, 36(4), 441454.CrossRefGoogle ScholarPubMed
Wilson, R.S., Barnes, L.L., Bennett, D.A. (2003). Assessment of lifetime participation in cognitively stimulating activities. Journal of Clinical and Experimental Neuropsychology, 25(5), 634642.CrossRefGoogle ScholarPubMed
Wilson, R.S., Beckett, L.A., Barnes, L.L., Schneider, J.A., Bach, J., Evans, D.A., Bennett, D.A. (2002). Individual differences in rates of change in cognitive abilities of older persons. Psychology and Aging, 17(2), 179193.CrossRefGoogle ScholarPubMed
Wilson, R.S., Bennett, D.A., Bienias, J.L., Mendes de Leon, C.F., Morris, M.C., Evans, D.A. (2003). Cognitive activity and cognitive decline in a biracial community population. Neurology, 61(6), 812816.CrossRefGoogle Scholar
Wilson, R.S., Bienias, J.L., Evans, D.A., Bennett, D.A. (2004). Religious orders study: overview and change in cognitive and motor speed. Neuropsychology and Cognition, 11(2–3), 280303.CrossRefGoogle Scholar
Wilson, R.S., Mendes De Leon, C.F., Barnes, L.L., Schneider, J.A., Bienias, J.L., Evans, D.A., Bennett, D.A. (2002). Participation in cognitively stimulating activities and risk of incident Alzheimer disease. Journal of the American Medical Association, 287(6), 742748.CrossRefGoogle ScholarPubMed
Wilson, R.S., Scherr, P.A., Hoganson, G., Bienias, J.L., Evans, D.A., Bennett, D.A. (2005). Early life socioeconomic status and late life risk of Alzheimer's disease. Neuroepidemiology, 25(1), 814.CrossRefGoogle ScholarPubMed