Introduction: Although there is evidence for distinct behavioural sub-phenotypes in Alzheimer's disease (AD), their inter-relationships and the effect of clinical variables on their expression have been little investigated.
Methods: We have analysed a sample of 1850 probable AD patients from the UK and Greece with 10 item Neuropsychiatric Inventory (NPI) data. We applied a Multiple Indicators Multiple Causes (MIMIC) approach to investigate the effect of MMSE, disease duration, gender, age and age of onset on the structure of a four-factor model consisting of "psychosis", "moods", "agitation" and "behavioural dyscontrol".
Results: Specific clinical variables predicted the expression of individual factors. When the inter-relationship of factors is modelled, some previously significant associations are lost. For example, lower MMSE scores predict psychosis, agitation and behavioural dyscontrol factors, but psychosis and mood predict the agitation factor. Taking these associations into account MMSE scores did not predict agitation.
Conclusions: The complexity of the inter-relations between symptoms, factors and clinical variables is efficiently captured by this MIMIC model. (C) 2009 Elsevier Inc. All rights reserved.
|Number of pages||9|
|Journal||Neurobiology of Aging|
|Publication status||Published - Mar 2011|
- Alzheimer's disease (AD)
- Behavioural sub-phenotypes
- Structural Equation Modelling (SEM)
- Confirmatory Factor Analysis (CFA)
- Multiple Indicators Multiple Causes (MIMIC) model
- Latent variables
- Differential Item Functioning (DIF)
- Neuropsychiatric Inventory (NPI)
- Disease duration
- Age of onset