Multi-time-point data preparation robustly reveals MCI and dementia risk factors

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Abstract

INTRODUCTION: Conflicting results on dementia risk factors have been reported across studies. We hypothesize that variation in data preparation methods may partially contribute to this issue.
METHODS: We propose a comprehensive data preparation approach comparing individuals with stable diagnosis over time, to those who progress to mild cognitive impairment (MCI)/dementia. This was compared to the often-used ‘baseline’ analysis. Multivariate logistic regression was employed to evaluate both methods.
RESULTS: The results obtained from sensitivity analyses were consistent with those from our multi-time-point data preparation approach, exhibiting its robustness. Compared to analysis using only baseline data, the number of significant risk factors identified in progression analyses was substantially lower. Additionally, we found that moderate depression increased Healthy-to-MCI/Dementia risk, while hypertension reduced MCI-to-Dementia risk.
DISCUSSION: Overall, multi-time-point based data preparation approaches may pave the way for a better understanding of dementia risk factors, and address some of the reproducibility issues in the field.
Original languageEnglish
JournalAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM)
DOIs
Publication statusAccepted/In press - 16 Sep 2020

Keywords

  • Dementia progression
  • mild cognitive impairment (MCI)
  • cardiometabolic risk factors
  • multi-time-point data preparation
  • multivariate logistic regression
  • NACC data
  • longitudinal data
  • baseline

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