Mood is a key determinant of cognitive performance in community-dwelling older adults: a cross-sectional analysis

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Nadine Correia Santos (Author) Other; Patrício Costa (Author) FPCEUP; Pedro Cunha (Author) Other; Jorge Cotter (Author) Other; Adriana Sampaio (Author) Other; Joseph Zihl (Author) Other; Osborne F. X. Almeida (Author) Other; João J. Cerqueira (Author) Other; Joana Almeida Palha (Author) Other; Nuno Sousa (Author) Other

Journal

Title: Age

Pages: 1983-1993

ISSN: 0161-9152

Publisher: Kluwer Academic Publishers

Indexing

ISI Web of Knowledge

Scopus - 2 Citations

Scientific classification

FOS: Social sciences > Psychology

Other information

Authenticus ID: P-008-Q7V

DOI: 10.1007/s11357-012-9482-y

Abstract (EN): 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. © 2012 American Aging Association.

Language: English

Type (Professor's evaluation): Scientific

Notes: <a href="http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS&DestLinkType=FullRecord&KeyUT=000324545200035">Acesso à Web of Science</a>

No. of pages: 11