Skip to main content Accessibility help

The “SuperAgers” construct in clinical practice: neuropsychological assessment of illiterate and educated elderly

  • Everton Balduino (a1), Brian Alvarez Ribeiro de Melo (a2), Larissa de Sousa Mota da Silva (a1), José Eduardo Martinelli (a1) and Juliana Francisca Cecato (a1)...



The demographic transition is a global event intensified during the last decades that represents population aging. Thus, the studies directed to the elderly 80 years of age or more with preserved cognitive functions (named SuperAgers) emerges as a possible path to full comprehension of the health of those aging with acceptable levels of functionality and independency.


To evaluate the cognitive performance of the elderly over 80 years old, associating the results to their educational level.


We evaluated 144 healthy elders with 80 years or more through the following cognitive tests Mini-Mental State Examination (MMSE), Cambridge Cognitive Examination (CAMCOG), Clock Drawing Test (CDT), and Verbal Fluency Test (VF) and compared the tests’ scores with their educational level segmented in years of formal education, being the groups ILLITR (<1 year of schooling), 1TO4 (from 1 to 4 years of schooling), and 5MORE (>5 years of schooling).


There was positive influence of educational level on the cognitive tests’ score, which indicates higher cognitive reserve of the elderly with higher educational levels.


The functionality and independence of the so-called SuperAgers is determined by the cognitive reserve acquired throughout life, mainly developed by the years of formal education.


Corresponding author

Correspondence should be addressed to: Juliana Francisca Cecato, Geriatrics Division, Faculty of Medicine of Jundiaí, Prudente de Moraes St., 111, 13201-004, Jundiaí, Brazil. Phone/Fax: +55 11 4587 9161. Email:


Hide All
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Association.
Aprahamian, I., Martinelli, J.E., Cecato, J., Izbicki, R. and Yassuda, M. S. (2011b). Can the CAMCOG be a good cognitive test for patients with Alzheimer’s disease with low levels of education? International Psychogeriatrics, 23, 96101. doi: 10.1017/S104161021000116X.
Aprahamian, I., Martinelli, J. E., Cecato, J. and Yassuda, M. S. (2011a). Screening for Alzheimer’s Disease among illiterate elderly: accuracy analysis for multiple instruments. Journal of Alzheimer’s Disease, 26, 221229. doi: 10.3233/JAD-2011-110125.
Ardila, A. et al. (2010). Illiteracy: the neuropsychology of cognition without reading. Archives of Clinical Neuropsychology, 25, 689712. doi: 10.1093/arclin/acq079.
Barulli, D. and Stern, Y. (2013). Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends in Cognitive Sciences, 17, 502509. doi: 10.1016/j.tics.2013.08.012.
Bessi, V. et al. (2018). From subjective cognitive decline to Alzheimer’s Disease: the predictive role of neuropsychological assessment, personality traits, and cognitive reserve. A 7-year follow-up study. Journal of Alzheimer’s Disease, 63, 15231535. doi: 10.3233/JAD-171180.
Bottino, C. M. et al. (2008). Estimate of dementia prevalence in a community sample from São Paulo, Brazil. Dementia and Geriatric Cognitive Disorders, 26, 291299. doi: 10.1159/000161053.
Brito, T. R. P., Nunes, D. P., Duarte, Y. A. O. and Lebrão, M. L. (2018). Social network and older people’s functionality: health, well-being, and aging (SABE) study evidences. Revista Brasileira de Epidemiologia, 21(Suppl. 2), e180003. doi: 10.1590/1980-549720180003.supl.2.
Brucki, S. M. D. and Nitrini, R. (2008). Cancellation task in very low educated people. Archives of Clinical Neuropsychology, 23, 139147. doi: 10.1016/j.acn.2007.11.003.
Brucki, S. M. D., Nitrini, R., Caramelli, P., Bertolucci, P. H. F. and Okamoto, I. H. (2003). Sugestões para o uso do mini-exame do estado mental no Brasil. Arquivos de Neuropsiquiatria, 61, 777781. doi: 10.1590/S0004-282X2003000500014.
Causse, M., Peysakhovich, V. and Fabre, E. F. (2016). High working memory load impairs language processing during a simulated piloting task: an ERP and pupillometry study. Frontiers in Human Neuroscience, 10, 240. doi: 10.3389/fnhum.2016.00240.
Chapko, D., Sandu, A. L., McNeil, C. and Murray, A. (2017). Early brain development and cognitive ageing - A global challenge. Neuro Central, published online June 12th, 2017. Retrieved September 5, 2018, from
Core Team, R.C.T.R. (2013). R: A Language and Environment for Statistical Computing. Vienna: R Foundation for statistical computing.
Craik, F. I. and Bialystok, E. (2006). Cognition through the lifespan: mechanisms of change. Trends in Cognitive Sciences. 10, 131138. doi: 10.1016/j.tics.2006.01.007.
Dekhtyar, S., Wang, H. X., Fratiglioni, L. and Herlitz, A. (2016). Childhood school performance, education and occupational complexity: a life-course study of dementia in the Kungsholmen Project. International Journal of Epidemiology, 45, 12071215. doi: 10.1093/ije/dyw008.
Elkana, O., Soffer, S., Eisikovits, O. R., Oren, N., Bezalel, V., and Ash, E. L. (2019). WAIS Information Subtest as an indicator of crystallized cognitive abilities and brain reserve among highly educated older adults: a three-year longitudinal study. Applied Neuropsychology: Adult, 17. doi: 10.1080/23279095.2019.1575219.
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). Mini mental state. A practical method for grading the cognitive state of patients for the clinician. Journal Psychiatric Research, 12, 189198.
Garibotto, V. et al. (2008). Education and occupation as proxies for reserve in aMCI converters and AD FDG-PET evidence. Neurology, 71, 13421349. doi: 10.1212/01.wnl.0000327670.62378.c0.
Gu, L. et al. (2018). Cognitive reserve modulates attention processes in healthy elderly and amnestic mild cognitive impairment: an event-related potential study. Clinical Neurophysiology, 129, 198207. doi: 10.1016/j.clinph.2017.10.030.
Instituto Brasileiro de Geografia e Estatística [IBGE]. (2013). Projeção da população do Brasil por sexo e idade: 2000-2060. Retrieved September 5, 2018, from Instituto Brasileiro de Geografia e Estatística [IBGE],
Instituto Brasileiro de Geografia e Estatística [IBGE]. (2015). Mudança Demográfica no Brasil no Início do Século XXI: subsídios para as projeções da população. Retrieved September 5, 2018, from Instituto Brasileiro de Geografia e Estatística [IBGE],
Instituto Brasileiro de Geografia e Estatística [IBGE] (2017). Diretoria de Pesquisas, Coordenação de Trabalho e Rendimento, Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD) 2016-2017. Retrieved April 16, 2019, from
Instituto Brasileiro de Geografia e Estatística [IBGE] (2019). IBGE, em parceria com os Órgãos Estaduais de Estatística, Secretarias Estaduais de Governo e Superintendência da Zona Franca de Manaus ‐ SUFRAMA. Retrieved April 22, 2019, from Instituto Brasileiro de Geografia e Estatística [IBGE],
Johnson, R. A. and Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (Vol. 5, No. 8). Upper Saddle River, NJ: Prentice Hall.
Kemppainen, N. M. et al. (2008). Cognitive reserve hypothesis: Pittsburgh compound B and fluorodeoxyglucose positron emission tomography in relation to education in mild Alzheimer’s disease. Annals of Neurology, 63, 112118. doi: 10.1002/ana.21212.
Kremen, W. S. et al. (2019). Influence of young adult cognitive ability and additional education on later-life cognition. PNAS, 116, 20212026. doi: 10.1073/pnas.1811537116.
Kumar, S. et al. (2017). Extent of dorsolateral prefrontal cortex plasticity and its association with working memory in patients with Alzheimer disease. JAMA Psychiatry, 74, 12661274. doi: 10.1001/jamapsychiatry.2017.3292.
Livingston, G. et al. (2017). Dementia prevention, intervention, and care. The Lancet, 390, 26732734. doi: 10.1016/s0140-6736(17)31363-6.
Matsuda, O., Saito, M., Kato, M., Azami, H. and Shido, E. (2015). Wechsler Adult Intelligence Scale-III profile in the early stages of Alzheimer’s disease: performance in subtests sensitive to and resistant to normal decline with ageing. Psychogeriatrics, 15, 16. doi: 10.1111/psyg.12066.
Mazzeo, S. et al. (2019). The dual role of cognitive reserve in subjective cognitive decline and mild cognitive impairment: a 7-year follow-up study. Journal of Neurology, 111. doi: 10.1007/s00415-018-9164-5.
McKhann, G. M. et al. (2011). The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 7, 263269. doi: 10.1016/j.jalz.2011.03.005.
Mendez, M. F., Ala, T. and Underwood, K. (1992). Development of scoring criteria for the clock drawing task in Alzheimer’s Disease. Journal of the American Geriatrics Society, 40, 10951099. doi: 10.1111/j.1532-5415.1992.tb01796.x.
Meng, X. and D’Arcy, C. (2012). Education and dementia in the context of the cognitive reserve hypothesis: a systematic review with meta-analyses and qualitative analyses. PLoS One, 7, e38268. doi: 10.1371/journal.pone.0038268.
Ministério da Educação ‐ Instuto Nacional de Estudos e Pesquisas Educacionais (INEP). (2017). Censo Escolar 2017. Available from IBGE Retrieved January 12, 2019, from Ministério da Educação ‐ Instuto Nacional de Estudos e Pesquisas Educacionais (INEP),
Moreira, I. F. H., Lourenço, R. A., Soares, C., Engelhardt, E. and Laks, J. (2009). Cambridge Cognitive Examination: performance of healthy elderly Brazilians with low education levels. Cadernos de Saúde Pública, 25(8), 17741780. doi: 10.1590/S0102-311X2009000800013.
Nasri, F. (2008). O envelhecimento populacional no Brasil. einstein, 6(Suppl. 1), S4S6.
Naumczyk, P. et al. (2018). Cognitive predictors of cortical thickness in healthy aging. Advances in experimental medicine and biology, 1116, 5162. doi: 10.1007/5584_2018_265.
Perneczky, R. et al. (2006). Schooling mediates brain reserve in Alzheimer’s disease: findings of fluoro-deoxy-glucose-positron emission tomography. Journal of Neurology, Neurosurgery & Psychiatry, 77, 10601063. doi: 10.1136/jnnp.2006.094714.
Petersson, K. M., Reis, A. and Ingvar, M. (2001). Cognitive processing in literate and illiterate subjects: a review of some recent behavioral and functional neuroimaging data. Scandinavian Journal of Psychology, 42, 251267. doi: 10.1111/1467-9450.00235.
Pettigrew, C. and Soldan, A. (2019). Defining cognitive reserve and implications for cognitive aging. Current Neurology and Neuroscience Reports, 1 9, 1. doi: 10.1007/s11910-019-0917-z.
Pfeffer, R. I., Kurosaki, T. T., Harrah, C. H. J., Chance, J. M. and Filos, S. (1982). Measurement of functional activities in older adults in the community. Journal Gerontology, 37, 323329. doi: 10.1093/geronj/37.3.323.
Pollock, M. E. (2005). Intelligent technology for an aging population: the use of AI to assist elders with cognitive impairment. AI Magazine, 26, 924. doi: 10.1609/aimag.v26i2.1810.
Rajji, T. (2018). Neurophysiology and cognitive reserve: a promising path. Clinical Neurophysiology, 129, 286287. doi: 10.1016/j.clinph.2017.12.
Resende, E. P. F. et al. (2018). White matter microstructure in illiterate and low-literate elderly Brazilians: preliminary findings. Cognitive and Behavioral Neurology, 31, 193200. doi: 10.1097/WNN.0000000000000173.
Rimkus, C. M. et al. (2018). The protective effects of high-education levels on cognition in different stages of multiple sclerosis. Multiple Sclerosis and Related Disorders, 22, 4148. doi: 10.1016/j.msard.2018.03.001.
Rogalski, E. J. et al. (2013). Youthful memory capacity in old brains: anatomic and genetic clues from the Northwestern SuperAging Project. Journal of Cognitive Neuroscience, 25, 2936. doi: 10.1162/jocn_a_00300.
Rogalski, E. J. et al. (2018). Cognitive trajectories and spectrum of neuropathology in SuperAgers: the first 10 cases. Hippocampus. doi: 10.1002/hipo.22828.
Rosenberg-Lee, M., Barth, M. and Menon, V. (2011). What difference does a year of schooling make? NeuroImage, 57, 796808. doi: 10.1016/j.neuroimage.2011.05.013.
Roth, M. et al. (1986). CAMDEX. A standardized instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. British Journal of Psychiatry, 149, 698709.
Scarmeas, N. and Stern, Y. (2003). Cognitive reserve and lifestyle. Journal of Clinical and Experimental Neuropsychology, 25, 625633. doi: 10.1076/jcen.25.5.625.14576.
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448460. doi: 10.1017.S1355617701020240.
Stern, Y. (2006). Cognitive reserve and Alzheimer disease. Alzheimer Disease & Associated Disorders, 20, 112117. doi: 10.1097/01.wad.0000213815.20177.19.
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47, 20152028. doi: 10.1016/j.neuropsychologia.2009.03.004.
Stern, Y., Gurland, B., Tatemichi, T. K., Tang, M. X., Wilder, D., and Mayeux, R. (1994). Influence of education and occupation on the incidence of Alzheimer’s Disease. JAMA, 271, 10041010. doi: 10.1001/jama.1994.03510370056032.
United Nations. (2017). Word Population Prospects: the 2017 revision. Retrieved August 31, 2018, from Department of Economic and Social Affairs, Population Division,
Verde, P. et al. (2016). Domain-specific interference tests on navigational working memory in military pilots. Aerospace Medicine and Human Performance, 87, 528533. doi: 10.3357/AMHP.4521.2016.
Wechsler, D. (1997). Wechsler Adult Intelligence Scale — Third Edition. San Antonio, TX: The Psychological Corporation.
Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence (WASI). San Antonio, TX: The Psychological Corporation.
Yesavage, J. A. et al. (1983). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research, 17, 3749. doi: 10.1016/0022-3956(82)90033-4.


Related content

Powered by UNSILO

The “SuperAgers” construct in clinical practice: neuropsychological assessment of illiterate and educated elderly

  • Everton Balduino (a1), Brian Alvarez Ribeiro de Melo (a2), Larissa de Sousa Mota da Silva (a1), José Eduardo Martinelli (a1) and Juliana Francisca Cecato (a1)...


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.