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Abstract(s)
Introdução: De acordo com a literatura, é possível atrasar ou prevenir 1/3 dos casos de demência. A contabilização dos fatores de risco é essencial para que se possam identificar as pessoas que mais beneficiam de programas de intervenção em que são diminuídos esses fatores de risco e trabalhados os fatores protetores. Usualmente, é feita recorrendo ao CAIDE Dementia Risk Score, um instrumento em que são considerados dados demográficos, biométricos e bioquímicos. Mas pouco se sabe acerca dos correlatos deste risco, tal como medido pelo CAIDE, a nível do funcionamento cerebral. Objetivo: Averiguar se a variação nas pontuações de risco de demência obtidas no CAIDE está associada a alterações no sinal elétrico captado pelo eletroencefalograma (EEG) no lobo frontal e com as medidas cognitivas em indivíduos normativos. Método: Amostra constituída por 38 participantes, com idades entre os 54 e 79 anos (M= 67.05; DP= 6.02). Dados recolhidos em dois momentos, através de provas papel e lápis e registos de EEG em repouso, canais Fp1 e Fp2. Os sinais EEG foram analisados recorrendo a uma Power Spectral Density. Resultados: Observou-se que a pontuação CAIDE está positivamente correlacionada à ativação da potência relativa da banda teta; r (38) = .347, p = .033 e negativamente correlacionada com a pontuação na prova cognitiva MMSE; r (38) = - .369, p= .023. Adicionalmente, variações no MMSE mostram-se relacionadas a algumas métricas EEG. Discussão: Os resultados obtidos contribuem para uma medida de validade convergente entre o CAIDE e o risco de declínio cognitivo, sugerindo que a pontuação CAIDE parece identificar as pessoas que, não tendo alterações cognitivas, apresentam já uma atividade cerebral análoga à encontrada nos indivíduos com demência. Estas descobertas sensibilizam para a monitorização e controlo destes fatores precocemente, por via a diminuir a incidência da demência.
Introduction: According to the literature, it is possible to delay or prevent 1/3 of dementia cases. Accounting for risk factors is essential to identify the people who benefit most from intervention programs in which these risk factors are reduced, and protective factors are worked on. This is usually done using the CAIDE Dementia Risk Score, an instrument which considers demographic, biometric and biochemical data. But little is known about the correlates of this risk, as measured by the CAIDE, in terms of brain function. Objective: To find out whether the variation in dementia risk scores obtained in the CAIDE is associated with changes in the electrical signal captured by the electroencephalogram (EEG) and with cognitive measures in normative individuals. Method: The sample consisted of 38 participants aged between 54 and 79 (M= 67.05; SD= 6.02). Data collected at two time points, using paper and pencil tests and EEG recordings at rest, channels Fp1 and Fp2. The EEG signals were analysed using Power Spectral Density. Results: It was observed that the CAIDE score is positively correlated with the relative power activation of the theta band; r (38) = .347, p = .033 and negatively correlated with the MMSE cognitive test score; r (38) = -.369, p = .023. Additionally, variations in the MMSE are found to be related to some EEG metrics. Discussion: The obtained results contribute to a measure of convergent validity between CAIDE and the risk of cognitive decline. The findings suggest that CAIDE scores seem to identify individuals who, without cognitive changes, already have brain activity like that found in people with dementia. These findings underscore the importance of early monitoring and control of these factors to reduce the incidence of dementia.
Introduction: According to the literature, it is possible to delay or prevent 1/3 of dementia cases. Accounting for risk factors is essential to identify the people who benefit most from intervention programs in which these risk factors are reduced, and protective factors are worked on. This is usually done using the CAIDE Dementia Risk Score, an instrument which considers demographic, biometric and biochemical data. But little is known about the correlates of this risk, as measured by the CAIDE, in terms of brain function. Objective: To find out whether the variation in dementia risk scores obtained in the CAIDE is associated with changes in the electrical signal captured by the electroencephalogram (EEG) and with cognitive measures in normative individuals. Method: The sample consisted of 38 participants aged between 54 and 79 (M= 67.05; SD= 6.02). Data collected at two time points, using paper and pencil tests and EEG recordings at rest, channels Fp1 and Fp2. The EEG signals were analysed using Power Spectral Density. Results: It was observed that the CAIDE score is positively correlated with the relative power activation of the theta band; r (38) = .347, p = .033 and negatively correlated with the MMSE cognitive test score; r (38) = -.369, p = .023. Additionally, variations in the MMSE are found to be related to some EEG metrics. Discussion: The obtained results contribute to a measure of convergent validity between CAIDE and the risk of cognitive decline. The findings suggest that CAIDE scores seem to identify individuals who, without cognitive changes, already have brain activity like that found in people with dementia. These findings underscore the importance of early monitoring and control of these factors to reduce the incidence of dementia.
Description
Keywords
Envelhecimento Risco de demência Eletroencefalograma Efeito de desaceleração Aging Risk of dementia Electroencephalogram Deceleration effect