Estimating the health benefit of reducing indoor air pollution in a randomized environmental intervention

Roger D. Peng, Arlene M. Butz, Amber J. Hackstadt, D'Ann L. Williams, Gregory B. Diette, Patrick N. Breysse, Elizabeth C. Matsui

Research output: Contribution to journalArticle

Abstract

Summary: Recent intervention studies targeted at reducing indoor air pollution have demonstrated both the ability to improve respiratory health outcomes and to reduce particulate matter (PM) levels in the home. However, these studies generally do not address whether it is the reduction in PM levels specifically that improves respiratory health. We apply the method of principal stratification to data from a randomized air cleaner intervention designed to reduce indoor PM in homes of children with asthma. We estimate the health benefit of the intervention among study subjects who would experience a substantial reduction in PM in response to the intervention. For those subjects we find an increase in symptom-free days that is almost three times as large as the overall intention-to-treat effect. We also explore the presence of treatment effects among those subjects whose PM levels would not respond to the air cleaner. This analysis demonstrates the usefulness of principal stratification for environmental intervention trials and its potential for much broader application in this area.

Original languageEnglish (US)
Pages (from-to)425-443
Number of pages19
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume178
Issue number2
DOIs
StatePublished - Feb 1 2015

Keywords

  • Asthma
  • Bayesian
  • Clinical trial
  • Particulate matter
  • Principal stratification

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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