title: Adjusting for mortality when identifying risk factors for transitions to mild cognitive impairment and dementia.
abstract: Risk factors for mild cognitive impairment (MCI) and dementia are often investigated without accounting for the competing risk of mortality, which can bias results and lead to spurious conclusions, particularly regarding protective factors. Here, we apply a semi-Markov modeling approach to 531 participants in the University of Kentucky Biologically Resilient Adults in Neurological Studies (BRAiNS) longitudinal cohort, over one-third of whom died without transitioning to a cognitively impaired clinical state. A semi-Markov approach enables a statistical study of clinical state transitions while accounting for the competing risk of death and facilitates insights into both the odds that a risk factor will affect clinical transitions as well as the age at which the transition to MCI or dementia will occur. Risk factors assessed in the current study were identified by matching those reported in the literature with the data elements collected on participants. The presence of Type II diabetes at baseline shortens the time it takes cognitively intact individuals to transition to MCI by seven years on average while use of estrogen replacement therapy at enrollment (baseline) decreases the time required to convert from MCI to dementia by 1.5 years. Finally, smoking and being overweight do not promote transitions to impaired states but instead hasten death without a dementia. In contrast, conventional statistical analyses based on Cox proportional hazards models fail to recognize diabetes as a risk, show that being overweight increases the risk of clinical MCI, and that high blood pressure at baseline increases the risk of a dementia.
authors.affiliation: Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536, USA.
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Kryscio
authors.forename: Erin L
authors.initials: EL
authors.lastname: Abner
authors.forename: Yushun
authors.initials: Y
authors.lastname: Lin
authors.forename: Gregory E
authors.initials: GE
authors.lastname: Cooper
authors.forename: David W
authors.initials: DW
authors.lastname: Fardo
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Jicha
authors.forename: Peter T
authors.initials: PT
authors.lastname: Nelson
authors.forename: Charles D
authors.initials: CD
authors.lastname: Smith
authors.forename: Linda J
authors.initials: LJ
authors.lastname: Van Eldik
authors.forename: Lijie
authors.initials: L
authors.lastname: Wan
authors.forename: Frederick A
authors.initials: FA
authors.lastname: Schmitt
mesh_terms: D000368:Aged; D000465:Algorithms; D001057:Apolipoproteins E / Q000235:genetics; D060825:Cognitive Dysfunction / Q000401:mortality*; D015331:Cohort Studies; D003704:Dementia / Q000401:mortality*; D039721:Diagnostic and Statistical Manual of Mental Disorders; D018450:Disease Progression; D005260:Female; D006801:Humans; D007629:Kentucky / Q000453:epidemiology; D016013:Likelihood Functions; D008137:Longitudinal Studies; D008297:Male; D008390:Markov Chains; D009483:Neuropsychological Tests; D016017:Odds Ratio; D012044:Regression Analysis; D012307:Risk Factors
chemical_list: D001057:Apolipoproteins E