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: Contribution to journalArticlepeer-review

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 PM2.5's effects on dementia are larger than non-causal associations.

Original languageEnglish (US)
Pages (from-to)15-23
Number of pages9
JournalJournal of Alzheimer's Disease
Volume79
Issue number1
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

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

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia'. Together they form a unique fingerprint.

Cite this