Estimating the association between blood pressure variability and cardiovascular disease: An application using the ARIC Study

Jessica K. Barrett*, Raphael Huille, Richard Parker, Yuichiro Yano, Michael Griswold

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

13 Citations (Scopus)
205 Downloads (Pure)

Abstract

The association between visit-to-visit systolic blood pressure variability and cardiovascular events has recently received a lot of attention in the cardiovascular literature. But, blood pressure variability is usually estimated on a person-by-person basis and is therefore subject to considerable measurement error. We demonstrate that hazard ratios estimated using this approach are subject to bias due to regression dilution, and we propose alternative methods to reduce this bias: a two-stage method and a joint model. For the two-stage method, in stage one, repeated measurements are modelled using a mixed effects model with a random component on the residual standard deviation (SD). The mixed effects model is used to estimate the blood pressure SD for each individual, which, in stage two, is used as a covariate in a time-to-event model. For the joint model, the mixed effects submodel and time-to-event submodel are fitted simultaneously using shared random effects. We illustrate the methods using data from the Atherosclerosis Risk in Communities study.

Original languageEnglish
Pages (from-to)1855-1868
Number of pages14
JournalStatistics in Medicine
Volume38
Issue number10
Early online date21 Dec 2018
DOIs
Publication statusPublished - 10 May 2019

Keywords

  • cardiovascular disease
  • heteroscedasticity
  • joint model
  • mixed effects model
  • repeated measurements
  • survival analysis

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