Estimating the health benefit of reducing indoor air pollution in a randomized environmental intervention.
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 of PM levels specifically that improves respiratory health. In this paper 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 amongst 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 amongst 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.
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health.
Roger D
RD
Peng
Division of General Pediatrics, Johns Hopkins School of Medicine.
Arlene M
AM
Butz
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health.
Amber J
AJ
Hackstadt
Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health.
D'Ann L
DL
Williams
Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine.
Gregory B
GB
Diette
Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health.
Patrick N
PN
Breysse
Division of Pediatric Allergy and Immunology, Johns Hopkins School of Medicine.
Elizabeth C
EC
Matsui
Bayesian; asthma; clinical trial; particulate matter; principal stratification
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