Mood is a key determinant of cognitive performance in community-dwelling older adults: a cross-sectional analysis
| Autor: | João José Cerqueira, J. Zihl, Adriana Sampaio, Joana Almeida Palha, Patrício Costa, Pedro Cunha, Osborne F. X. Almeida, Nuno Sousa, Jorge Cotter, Nadine Correia Santos |
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| Přispěvatelé: | Universidade do Minho, Faculdade de Psicologia e de Ciências da Educação |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Male
Aging Aging .Mood Neuropsychological Tests Logistic regression Affect (psychology) 050105 experimental psychology Article Developmental psychology 03 medical and health sciences 0302 clinical medicine Cognition Neurocognitive/neuropsychological assessment Memory Psychology [Social sciences] Psicologia [Ciências sociais] Mood Humans Psychology 0501 psychology and cognitive sciences Psychological testing Effects of sleep deprivation on cognitive performance Cognitive decline 10. No inequality Aged Aged 80 and over Science & Technology 05 social sciences General Medicine Middle Aged Affect Cross-Sectional Studies Psicologia Female Geriatrics and Gerontology Cognition Disorders Neurocognitive 030217 neurology & neurosurgery Clinical psychology |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP AGE; Vol 35 |
| Popis: | First Online: 06 October 2012 Identification of predictors of cognitive trajectories through the establishment of composite or single-parameter dimensional categories of cognition and mood may facilitate development of strategies to improve quality of life in the elderly. Participants (n = 487, aged 50+ years) were representative of the Portuguese population in terms of age, gender, and educational status. Cognitive and mood profiles were established using a battery of neurocognitive and psychological tests. Data were subjected to principal component analysis to identify core dimensions of cognition and mood, encompassing multiple test variables. Dimensions were correlated with age and with respect to gender, education, and occupational status. Cluster analysis was applied to isolate distinct patterns of cognitive performance and binary logistic regression models to explore interrelationships between aging, cognition, mood, and socio-demographic characteristics. Four main dimensions were identified: memory, executive function, global cognitive status, and mood. Based on these, strong and weak cognitive performers were distinguishable. Cluster analysis revealed further distinction within these two main categories into very good, good, poor, and very poor performers. Mood was the principal factor contributing to the separation between very good and good, as well as poor and very poor, performers. Clustering was also influenced by gender and education, albeit to a lesser extent; notably, however, female gender × lower educational background predicted significantly poorer cognitive performance with increasing age. Mood has a significant impact on the rate of cognitive decline in the elderly. Gender and educational level are early determinants of cognitive performance in later life. This work was funded by the European Commission (FP7) “SwitchBox” (Contract HEALTH-F2-2010-259772). NCS is supported by a SwitchBox post-doctoral fellowship. We are thankful to all study participants. The authors would like to acknowledge all colleagues who assisted with participant recruitment and evaluation. |
| Databáze: | OpenAIRE |
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