Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia

Kelly C. Bishop, Sehba Husain-Krautter, Jonathan D. Ketcham, Nicolai V. Kuminoff, Corbett Schimming

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We hypothesize that analyzing individual-level secondary data with instrumental variable (IV) methods can advance knowledge of the long-term effects of air pollution on dementia. We discuss issues in measurement using secondary data and how IV estimation can overcome biases due to measurement error and unmeasured variables. We link air-quality data from the Environmental Protection Agency's monitors with Medicare claims data to illustrate the use of secondary data to document associations. Additionally, we describe results from a previous study that uses an IV for pollution and finds that PM 2.5 's effects on dementia are larger than non-causal associations.

Original languageEnglish (US)
Title of host publicationAlzheimer�s Disease and Air Pollution
Subtitle of host publicationThe Development and Progression of a Fatal Disease from Childhood and the Opportunities for Early Prevention
EditorsLilian Calderon-Garciduenas
PublisherIOS Press BV
Pages531-539
Number of pages9
ISBN (Electronic)9781643681580
DOIs
StatePublished - 2020
Externally publishedYes

Publication series

NameAdvances in Alzheimer's Disease
Volume8
ISSN (Print)2210-5727
ISSN (Electronic)2210-5735

Keywords

  • Air pollution
  • aged
  • dementia
  • instrumental variables
  • research design
  • selection bias

ASJC Scopus subject areas

  • Clinical Neurology

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