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The role of literacy, occupation and income in dementia prevention: the São Paulo Ageing & Health Study (SPAH)

Published online by Cambridge University Press:  03 August 2010

Marcia Scazufca ,
Osvaldo P. Almeida  and
Paulo R. Menezes
Marcia Scazufca*
Affiliation:
University of São Paulo, Faculty of Medicine, Institute of Psychiatry and LIM-23, São Paulo, Brazil
Osvaldo P. Almeida
Affiliation:
University of Western Australia and Royal Perth Hospital, Western Australian Centre for Health and Ageing, Perth, Western Australia, Australia
Paulo R. Menezes
Affiliation:
University of São Paulo, Faculty of Medicine, Department of Preventive Medicine, São Paulo, Brazil
*
Correspondence should be addressed to: Marcia Scazufca, Rua Mario de Alencar 185, São Paulo, SP, Brazil, CEP 05436-090. Phone: +551130316193. Email: [email protected].
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Abstract

Background: Dementia is now a major public health issue in low- and middle-income countries, and strategies for primary prevention are needed. This study aimed to estimate the proportion of cases of dementia attributable to illiteracy, non-skilled occupation and low income, which are common, potentially modifiable social adversities that occur along the lifespan in low- and middle-income countries.

Methods: This report is based on data from the São Paulo Ageing & Health Study (SPAH) study (N = 2003). All individuals aged 65 years and older residing within pre-defined socially deprived areas of the city of São Paulo, Brazil, were included. The outcome of interest was prevalent dementia. Indicators of socioeconomic position (SEP) were literacy (distal indicator), highest occupational attainment (intermediate indicator), and monthly personal income (proximal indicator). We estimated the proportion of prevalent dementia attributable to each SEP indicator (illiteracy, non-skilled occupations and low income) by calculating their population attributable fractions (PAF).

Results: Dementia was more prevalent amongst participants who were illiterate, had non-skilled occupations and lower income. Illiteracy, poor occupational achievement and low income accounted for 22.0%, 38.5% and 38.5% of the cases of dementia, respectively. There was a cumulative effect of socioeconomic adversities during the lifespan, and nearly 50% of the prevalence of dementia could be potentially attributed to the combination of two or three of the socioeconomic adversities investigated.

Conclusions: Public policies aimed at improving education, occupational skills and income could potentially have a role in primary prevention of dementia. Governments should address this issue in a purposeful and systematic way.

Keywords

dementiapreventionepidemiologydeveloping countriesBrazil
Type
Focus on prevention in psychogeriatrics
Information
International Psychogeriatrics , Volume 22 , Special Issue 8: Focus on prevention in psychogeriatrics , December 2010 , pp. 1209 - 1215
Copyright
Copyright © International Psychogeriatric Association 2010

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References

American Psychiatric Association (1994). Diagnostic and Statistic Manual of Mental Disorders, 4th edition. Washington, DC: American Psychiatric Association.Google Scholar
Andel, R. et al. (2005). Complexity of work and risk of Alzheimer's disease: a population-based study of Swedish twins. Journal of Gerontology, Series B: Psychological Science and Social Science, 60, 251–258.CrossRefGoogle ScholarPubMed
Bibbins-Domingo, K. et al. (2010). Projected effect of dietary salt reductions on future cardiovascular disease. New England Journal of Medicine, 18, 590–599.CrossRefGoogle Scholar
Borysiewicz, L. K. (2010). Prevention is better than cure. Lancet, 375, 513–523.CrossRefGoogle ScholarPubMed
Brookmeyer, R., Johnson, E., Ziegler-Graham, K. and Arrighi, H. M. (2007). Forecasting the global burden of Alzheimer's disease. Alzheimer's and Dementia, 3, 186–91.CrossRefGoogle ScholarPubMed
Browner, W. S. and Newman, T. B. (1989). Sample size and power based on the population attributable fraction. American Journal of Public Health, 79: 1289–1294.CrossRefGoogle ScholarPubMed
Caamano-Isorna, F., Corral, M., Montes-Martinez, A. and Takkouche, B. (2006). Education and dementia: a meta-analytic study. Neuroepidemiology, 26, 226–232.CrossRefGoogle ScholarPubMed
Cohen, J. E. (2003). Human population: the next half century. Science, 302, 1172–1175.CrossRefGoogle ScholarPubMed
Copeland, J. R., Dewey, M. E. and Griffiths-Jones, H. M. (1986). A computerized psychiatric diagnostic system and case nomenclature for elderly subjects: GMS and AGECAT. Psychological Medicine, 16, 89–99.CrossRefGoogle ScholarPubMed
Dewey, M. E. and Copeland, J. R. (2001). Diagnosis of dementia from the history and aetiology schedule. International Journal of Geriatric Psychiatry, 16, 912–917.CrossRefGoogle ScholarPubMed
Ferri, C. P. et al. (2005). Global prevalence of dementia: a Delphi consensus study. Lancet, 366, 2112–2117.CrossRefGoogle ScholarPubMed
Fratiglioni, L. and Wang, H. X. (2007). Brain reserve hypothesis in dementia. Journal of Alzheimer's Disease, 12, 11–22.CrossRefGoogle ScholarPubMed
Greenland, S. and Robins, J. M. (1988). Conceptual problems in the the definition and interpretation of attributable fractions. American Journal of Epidemiology, 128, 1185–1197.CrossRefGoogle ScholarPubMed
Hall, K. S., Gao, S., Unverzagt, F. W. and Hendrie, H. C. (2000). Low education and childhood rural residence: risk for Alzheimer's disease in African Americans. Neurology, 54, 95–99.CrossRefGoogle ScholarPubMed
Instituto Brasileiro de Geografia e Estatística (2002). Perfil dos Idosos Responsáveis pelos Domicílios no Brasil. Estudos & Pesquisas. Informação Sociodemográfica e Socioeconômica 9. Rio de Janeiro: IBGE.Google 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. American Journal of Geriatric Psychiatry, 17, 227–236.CrossRefGoogle ScholarPubMed
Kivipelto, M., Ngandu, T., Laatikainen, T., Winblad, B., Soininen, H. and Tuomilehto, J. (2006). Risk score for the prediction of dementia risk in 20 years among middle aged people: a longitudinal, population-based study. Lancet Neurology, 5, 735–741.CrossRefGoogle ScholarPubMed
Murray, C. J. and Lopez, A. D. (1997). Alternative projections of mortality and disability by cause, 1990–2020: Global Burden of Disease Study. Lancet, 349, 1498–1504.CrossRefGoogle ScholarPubMed
Ngandu, T. et al. (2007). Education and dementia: what lies behind the association? Neurology, 69, 1442–1450.CrossRefGoogle ScholarPubMed
Prince, M., Acosta, D., Chiu, H., Scazufca, M. and Varghese, M. (2003). Dementia diagnosis in developing countries: a cross-cultural validation study. Lancet, 361, 909–917.CrossRefGoogle ScholarPubMed
Prince, M. et al. (2004). Effects of education and culture on the validity of the Geriatric Mental State and its AGECAT algorithm. British Journal of Psychiatry, 185, 429–436.CrossRefGoogle ScholarPubMed
Qiu, C., Karp, A., von, S. E., Winblad, B., Fratiglioni, L. and Bellander, T. (2003). Lifetime principal occupation and risk of Alzheimer's disease in the Kungsholmen project. American Journal of Industrial Medicine, 43, 204–211.CrossRefGoogle ScholarPubMed
Scazufca, M. et al. (2002). Epidemiological research on dementia in developing countries. Revista de Saúde Pública, 36, 773–778.CrossRefGoogle ScholarPubMed
Scazufca, M. et al. (2008a). Risk factors across the life course and dementia in a Brazilain population: results from the Sao Paulo Ageing & Health Study (SPAH). International Journal of Epidemiology, 37, 897–890.CrossRefGoogle Scholar
Scazufca, M. et al. (2008b). High prevalence of dementia among older adults from poor socio-economic background in Sao Paulo, Brazil. International Psychogeriatrics, 20, 394–405.CrossRefGoogle Scholar
Smith, K. et al. (2008). High prevalence of dementia and cognitive impairment in indigenous Australians. Neurology, 71, 1470–1473.CrossRefGoogle ScholarPubMed
United Nations Department of Economic and Social Affairs (2002). World Population Ageing 1950–2050. New York: United Nations.Google Scholar
United Nations Department of Economic and Social Affairs (2007). World Population Prospects: The 2006 Revision Population Dataset. New York: United Nations.Google Scholar
United Nations (2008). 2015 Millenium Development Goals. www.un.org/milleniumgoals/index.shtml. Last accessed 30 March 2010.Google Scholar
Weih, M., Wiltfang, J. and Kornhuber, J. (2007). Non-pharmacologic prevention of Alzheimer's disease: nutritional and life-style risk factors. Journal of Neural Transmission, 114, 1187–1197.CrossRefGoogle ScholarPubMed
Welsh, K. A. et al. (1994). The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part V. A normative study of the neuropsychological battery. Neurology, 44, 609–614.CrossRefGoogle Scholar
Whalley, L. J., Dick, F. D. and McNeill, G. (2006). A life-course approach to the aetiology of late-onset dementias. Lancet Neurology, 5, 87–96.CrossRefGoogle Scholar