Discriminant power of socio-demographic characteristics and mood in distinguishing cognitive performance clusters in older individuals: a cross-sectional analysis.

Objectives: Identification of predictors of cognitive trajectories has been a matter of concern on aging research. For this reason, it is of relevance to infer cognitive profiles based on rapid screening variables in order to determine which individuals will be more predisposed to cognitive decline.

Method: In this work, a linear discriminant analysis (LDA) was conducted with socio-demographic variables and mood status as predictors of cognitive profiles, computed in a previous sample, based on different cognitive dimensions. Data were randomly split in two samples. Both samples were representative of the Portuguese population in terms of gender, age and education. The LDA was performed with one sample (n = 506, mean age 65.7 ± 8.98 years) and tested in the second sample (n = 548, mean age 68.5 ± 9.3 years).

Results: With these variables, we were able to achieve an overall hit rate of 65.9%, which corresponds to a significant increment in comparison to classification by chance.

Conclusion: Although not ideal, this model may serve as a relevant tool to identify cognitive profiles based on a rapid screening when few variables are available.