title: Future Dementia Severity is Almost Entirely Explained by the Latent Variable δ's Intercept and Slope.
abstract: BACKGROUND
  Structural equation models (SEM) can explicitly distinguish dementia-relevant variance in cognitive task performance. The resulting latent construct "δ" (for dementia) provides a relatively "error free" continuously varying dementia-specific phenotype.
  
  
  OBJECTIVE
  To estimate δ's change over time (Δδ) and determine Δδ's predictive validity using future dementia status as an outcome.
  
  
  METHODS
  Data from n = 2,191 participants of the Texas Alzheimer's Research and Care Consortium (TARCC) were used to construct a latent growth curve model of longitudinal change over four years using five cognitive measures and one measure of Instrumental Activities of Daily Living. Four final latent factors, including baseline δ and Δδ, were simultaneously entered as predictors of wave 4 dementia severity, as estimated by the Clinical Dementia Rating Scale "sum of boxes" (CDR).
  
  
  RESULTS
  All observed measures exhibited significant change [χ2 = 1,152 (df = 229); CFI = 0.968; RMSEA = 0.043]. The final model demonstrated excellent fit to the data [χ2 = 543 (df = 245); CFI = 0.991; RMSEA = 0.023]. All latent indicator loadings were significant, yielding four distinct factors. After adjustment for demographic covariates and baseline CDR scores, d and Δd were significantly independently associated with CDR4, explaining 25% and 49% of its variance, respectively. The latent variable g' significantly explained 3% of CDR4 variance independently of d and Δd. Δg' was not significantly associated with CDR4. Baseline CDR explained 16% of CDR4 variance.
  
  
  CONCLUSIONS
  Future dementia severity is almost entirely explained by the latent construct δ's intercept and slope.
authors.affiliation: Department of Family and Community Medicine, The University of Texas Health Science Center, San Antonio, TX, USA.|Department of Epidemiology and Biostatistics, The University of Texas Health Science Center, San Antonio, TX, USA.|Department of Psychiatry, The University of Texas Health Science Center, San Antonio, TX, USA.
authors.forename: Raymond F
authors.initials: RF
authors.lastname: Palmer
authors.affiliation: Department of Family and Community Medicine, The University of Texas Health Science Center, San Antonio, TX, USA.|Department of Psychiatry, The University of Texas Health Science Center, San Antonio, TX, USA.|Department of Medicine, The University of Texas Health Science Center, San Antonio, TX, USA.|South Texas Veterans' Health System, Audie L. Murphy Division GRECC, San Antonio, TX, USA.
authors.forename: Donald R
authors.initials: DR
authors.lastname: Royall
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000523:psychology*; D003071:Cognition; D060825:Cognitive Dysfunction / Q000175:diagnosis* / Q000523:psychology*; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D009483:Neuropsychological Tests; D011569:Psychiatric Status Rating Scales
keywords: Alzheimer’s disease; dementia; latent variable; longitudinal