Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-24T04:49:14.909Z Has data issue: false hasContentIssue false

Modeling cognitive reserve in healthy middle-aged and older adults: the Tasmanian Healthy Brain Project

Published online by Cambridge University Press:  23 September 2014

David D. Ward
Affiliation:
Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
Mathew J. Summers*
Affiliation:
Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia School of Medicine (Psychology), University of Tasmania, Launceston, Tasmania, Australia
Nichole L. Saunders
Affiliation:
Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia
James C. Vickers
Affiliation:
Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
*
Correspondence should be addressed to: Dr. Mathew J. Summers, School of Medicine (Psychology), Faculty of Health Science, University of Tasmania, Locked Bag 1342, Launceston, Tasmania 7250, Australia. Phone: +61-3-6324-3266; Fax: +61-3-6324-3168. Email: [email protected].

Abstract

Background:

Cognitive reserve (CR) is a protective factor that supports cognition by increasing the resilience of an individual's cognitive function to the deleterious effects of cerebral lesions. A single environmental proxy indicator is often used to estimate CR (e.g. education), possibly resulting in a loss of the accuracy and predictive power of the investigation. Furthermore, while estimates of an individual's prior CR can be made, no operational measure exists to estimate dynamic change in CR resulting from exposure to new life experiences.

Methods:

We aimed to develop two latent measures of CR through factor analysis: prior and current, in a sample of 467 healthy older adults.

Results:

The prior CR measure combined proxy measures traditionally associated with CR, while the current CR measure combined variables that had the potential to reflect dynamic change in CR due to new life experiences. Our main finding was that the analyses uncovered latent variables in hypothesized prior and current models of CR.

Conclusions:

The prior CR model supports multivariate estimation of pre-existing CR and may be applied to more accurately estimate CR in the absence of neuropathological data. The current CR model may be applied to evaluate and explore the potential benefits of CR-based interventions prior to dementia onset.

Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akbaraly, T. N. et al. (2009). Leisure activities and the risk of dementia in the elderly: results from the Three-City Study. Neurology, 73, 854861.Google Scholar
Ardila, A. (2007). Normal aging increases cognitive heterogeneity: analysis of dispersion in WAIS-III scores across age. Archives of Clinical Neuropsychology, 22, 10031011.Google Scholar
Barulli, D. and Stern, Y. (2013). Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends in Cognitive Sciences, 17, 502509.Google Scholar
Basu, R. (2012). Education and dementia risk: results from the Aging Demographics and Memory Study. Research on Aging, 35, 731.Google Scholar
Bernard, H. R., Killworth, P., Kronenfeld, D. and Sailer, L. (1984). The problem of informant accuracy: the validity of retrospective data. Annual Review of Anthropology, 13, 495517.Google Scholar
Bjelland, I., Dahl, A. A., Haug, T. T. and Neckelmann, D. (2002). The validity of the Hospital Anxiety and Depression Scale: an updated literature review. Journal of Psychosomatic Research, 52, 6977.CrossRefGoogle ScholarPubMed
Brayne, C. et al. (2010). Education, the brain and dementia: neuroprotection or compensation?: EClipSE collaborative members. Brain, 133, 22102216.Google Scholar
Brinch, C. N. and Galloway, T. A. (2012). Schooling in adolescence raises IQ scores. Proceedings of the National Academy of Sciences of the United States of America, 109, 425430.CrossRefGoogle ScholarPubMed
Ceci, S. J. (1991). How much does schooling influence general intelligence and its cognitive components? A reassessment of the evidence. Developmental Psychology, 27, 703722.CrossRefGoogle Scholar
Colom, R., Jung, R. E. and Haier, R. J. (2006). Distributed brain sites for the g-factor of intelligence. NeuroImage, 31, 13591365.Google Scholar
Deloitte Access Economics. (2011). Dementia Across Australia: 2011–2015. Canberra, Australia: Deloitte Access Economics, 15 pp.Google Scholar
Donnell, A. J., Pliskin, N., Holdnack, J., Axelrod, B. N. and Randolph, C. (2007). Rapidly administered short forms of the Wechsler Adult Intelligence Scale – 3rd edn. Archives of Clinical Neuropsychology, 22, 917924.Google Scholar
Foubert-Samier, A. et al. (2012). Education, occupation, leisure activities, and brain reserve: a population-based study. Neurobiology of Aging, 33, e415e425.Google Scholar
Fratiglioni, L. and Wang, H. X. (2007). Brain reserve hypothesis in dementia. Journal of Alzheimer's Disease, 12, 1122.Google Scholar
Galioto, R. M., Alosco, M. L., Spitznagel, M. B., Stanek, K. M. and Gunstad, J. (2013). Cognitive reserve preserves cognitive function in obese individuals. Aging, Neuropsychology, and Cognition, 116.Google Scholar
Green, R. E. A., Melo, B., Christensen, B., Ngo, L. A., Monette, G. and Bradbury, C. (2008). Measuring premorbid IQ in traumatic brain injury: an examination of the validity of the Wechsler Test of Adult Reading (WTAR). Journal of Clinical and Experimental Neuropsychology, 30, 163172.Google Scholar
Haier, R. J., Jung, R. E., Yeo, R. A., Head, K. and Alkire, M. T. (2004). Structural brain variation and general intelligence. NeuroImage, 23, 425433.CrossRefGoogle ScholarPubMed
Jones, R. N., Manly, J., Glymour, M. M., Rentz, D. M., Jefferson, A. L. and Stern, Y. (2011). Conceptual and measurement challenges in research on cognitive reserve. Journal of the International Neuropsychological Society, 17, 593601.CrossRefGoogle ScholarPubMed
Jurica, P. J., Leitten, C. L. and Mattis, S. (2001). Dementia Rating Scale-2 (DRS-2): Professional Manual. Odessa, RL: Psychological Assessment Resources.Google Scholar
Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141151.CrossRefGoogle Scholar
Karp, A., Andel, R., Parker, M. G., Wang, H. X., Winblad, B. and Fratiglioni, L. (2009). Mentally stimulating activities at work during midlife and dementia risk after age 75: follow-up study from the Kungsholmen Project. The American Journal of Geriatric Psychiatry, 17, 227236.Google Scholar
Katzman, R. et al. (1988). Clinical, pathological, and neurochemical changes in dementia. A subgroup with preserved mental status and numerous neocortical plaques. Annals of Neurology, 23, 138144.Google Scholar
Klekociuk, S. Z. and Summers, M. J. (2014). The learning profile of persisten mild cognitive impairment (MCI): a potential diagnostic marker of persistent amnestic MCI. European Journal of Neurology, 21, 470477.CrossRefGoogle Scholar
Kline, P. (2002). An Easy Guide to Factor Analysis. London: Routledge.Google Scholar
Landau, S. M. et al. (2012). Association of lifetime cognitive engagement and low β-amyloid deposition. Archives of Neurology, 69, 623629.Google Scholar
Liu, Y., Julkunen, V., Paajanen, T. and Westman, E. (2012). Education increases reserve against Alzheimer's disease: evidence from structural MRI analysis. Neuroradiology, 54, 929938.Google Scholar
Lo, R. Y. and Jagust, W. J. (2013). Effect of cognitive reserve markers on Alzheimer's pathological progression. Alzheimer's Disease and Associated Disorders, 27, 343350.Google Scholar
Meng, X. and D’Arcy, C. (2012). Apolipoprotein E gene, environmental risk factors, and their interactions in dementia among seniors. International Journal of Geriatric Psychiatry, 28, 10051014.Google Scholar
Norton, M. C. et al. (2012). Lifestyle behavior pattern is associated with different levels of risk for incident dementia and Alzheimer's disease: the Cache County Study. Journal of the American Geriatrics Society, 60, 405412.Google Scholar
Ott, A. et al. (1995). Prevalence of Alzheimer's disease and vascular dementia: association with education. The Rotterdam Study. BMJ, 318, 970973.Google Scholar
Perneczky, R. et al. (2009). Education attenuates the effect of medial temporal lobe atrophy on cognitive function in Alzheimer's disease: the MIRAGE Study. Journal of Alzheimer's Disease, 17, 855862.Google Scholar
Querbes, O. et al. (2009). Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve. Brain, 132, 20362047.CrossRefGoogle ScholarPubMed
Rentz, D. M. et al. (2010). Cognition, reserve, and amyloid deposition in normal aging. Annals of Neurology, 67, 353364.Google Scholar
Richards, M. and Sacker, A. (2003). Lifetime antecedents of cognitive reserve. Journal of Clinical and Experimental Neuropsychology, 25, 614624.Google Scholar
Roid, G. H. and Ledbetter, M. F. (2006). WRAT4 Progress Monitoring Version: Professional Manual. Lutz, FL: Psychological Assessment Resources.Google Scholar
Sánchez, J. L., Torrellas, C., Martín, J. and Barrera, I. (2011). Study of socio-demographic variables linked to lifestyle and their possible influence on cognitive reserve. Journal of Clinical and Experimental Neuropsychology, 33, 874891.Google Scholar
Satz, P., Cole, M. A., Hardy, D. J. and Rassovsky, Y. (2011). Brain and cognitive reserve: mediator(s) and construct validity, a critique. Journal of Clinical and Experimental Neuropsychology, 33, 121130.Google Scholar
Scarmeas, N. et al. (2003). Association of life activities with cerebral blood flow in Alzheimer's disease. Archives of Neurology, 60, 359365.Google Scholar
Small, B. J., Dixon, R. A., McArdle, J. J. and Grimm, K. J. (2012). Do changes in lifestyle engagement moderate cognitive decline in normal aging? Evidence from the Victoria Longitudinal Study. Neuropsychology, 26, 144155.Google Scholar
Snaith, R. P. and Zigmond, A. S. (1994). The Hospital Anxiety and Depression Scale (HADS): Manual. London: GL Assessment.Google Scholar
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448460.Google Scholar
Stern, Y. et al. (2005). Brain networks associated with cognitive reserve in healthy young and old adults. Cerebral Cortex, 15, 394402.Google Scholar
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47, 20152028.Google Scholar
Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer's disease. The Lancet Neurology, 11, 10061012.Google Scholar
Stern, Y., Gurlund, B., Tatemichi, T. K., Tang, M. X., Wilder, D. and Mayeaux, R. (1994). Influence of education and occupation on the incidence of Alzheimer's disease. JAMA, 271, 10041010.Google Scholar
Strauss, E., Sherman, E. M. S. and Spreen, O. (2006). A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary. New York, NY: Oxford University Press.Google Scholar
Summers, M. J. and Saunders, N. L. J. (2012). Neuropsychological measures predict decline to Alzheimer's dementia from mild cognitive impairment. Neuropsychology, 26, 498508.Google Scholar
Summers, M. J. et al. (2013). The Tasmanian Healthy Brain Project (THBP): a prospective longitudinal examination of the effect of university-level education in older adults preventing age-related cognitive decline and reducing the risk of dementia. International Psychogeriatrics, 25, 11451155.Google Scholar
Suo, C. et al. (2012). Supervisory experience at work is linked to low rate of hippocampal atrophy in late life. NeuroImage, 63, 15421551.Google Scholar
Teipel, S. J. et al. (2009). White matter microstructure in relation to education in aging and Alzheimer's disease. Journal of Alzheimer's Disease, 17, 571583.Google Scholar
The Psychological Corporation. (2001). Wechsler Test of Adult Reading. San Antonio, TX: Harcourt Assessment.Google Scholar
Tucker, M. A. and Stern, Y. (2011). Cognitive reserve in aging. Current Alzheimer's Research, 8, 354360.Google Scholar
Valenzuela, M. J. and Sachdev, P. (2006). Brain reserve and cognitive decline: a non-parametric systematic review. Psychological Medicine, 36, 10651073.Google Scholar
Valenzuela, M. J. and Sachdev, P. (2007). Assessment of complex mental activity across the lifespan: development of the Lifetime of Experiences Questionnaire (LEQ). Psychological Medicine, 37, 10151025.Google Scholar
Valenzuela, M. J., Sachdev, P., Wen, W., Chen, X. and Brodaty, H. (2008). Lifespan mental activity predicts diminished rate of hippocampal atrophy. PloS one, 3, 16.Google Scholar
Vemuri, P. et al. (2011). Cognitive reserve and Alzheimer's disease biomarkers are independent determinants of cognition. Brain, 134, 14791492.CrossRefGoogle ScholarPubMed
Wang, H.-X. et al. (2012). Late life leisure activities and risk of cognitive decline. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 68, 205213.Google Scholar
Wilson, R. S. et al. (2010). Cognitive activity and the cognitive morbidity of Alzheimer's disease. Neurology, 75, 990996.Google Scholar
Supplementary material: File

Ward Supplementary Material

Figure S3

Download Ward Supplementary Material(File)
File 649.4 KB