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Synthesis of Environmental Evidence: Nitrogen Dioxide Epidemiology Studies

Open access
Hasselblad, Vic, Eddy, David M., Kotchmar, Dennis J.·1992·Journal of the Air & Waste Management Association

Abstract

The use of meta-analysis is becoming more common in the medical literature, but it is not common in the environmental literature. Although meta-analysis cannot combine a group of poorly executed, conflicting studies to get an unequivocal answer, there are certain situations where it can be helpful. The inability of studies to produce similar results may be a function of the power of the studies rather than a reflection of their quality. The literature on the effects of nitrogen dioxide on the odds of respiratory illness in children is such an example. Three quantitative methods for the synthesis of this evidence are presented. Although the methods produce slightly different results, the conclusion from all three methods is that the increase in the odds of respiratory illness in children exposed to a long-term increase of 30 micrograms/m3 (comparable to the increase resulting from exposure to a gas stove) is about 20 percent. This estimated increase is not sensitive to the method of analysis.

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Metadata

Authors
Hasselblad, V., Eddy, D. M., & Kotchmar, D. J.
Venue
Journal of the Air & Waste Management Association
Published
1992-05
Volume
42
Issue
5
Pages
662-671
ISSN
1047-3289 (ISSN-L)
OpenAlex
W2058531919
Cited by
202
References
0
FWCI
5.47
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Synthesis of Environmental Evidence: Nitrogen Dioxide Epidemiology Studies. https://app.cochat.ai/papers/10.1080/10473289.1992.10467018
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Hasselblad, V., Eddy, D. M., & Kotchmar, D. J. (1992). Synthesis of Environmental Evidence: Nitrogen Dioxide Epidemiology Studies. Journal of the Air & Waste Management Association. https://doi.org/10.1080/10473289.1992.10467018

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.