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Air Pollution and Hospital Admissions for Heart Disease in Eight U.S. Counties
Abstract
This study examines the consistency of the association between particulate matter less than 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO), and hospital admissions for cardiovascular disease across eight urban counties with different levels of correlation between pollutants and between the pollutants and weather. I fit Poisson regression models controlling for day-of-week effects and using nonparametric smoothing to control for season and weather. Daily variation in PM10 was associated with hospital admissions for heart disease in the elderly (2.48% increase, for an interquartile range increase in exposure; 95% confidence limits = 1.82%, 3.15%). Daily variation in CO was also associated with admissions (2.79% increase, for an interquartile range (1.75 parts per million) increase in exposure; 95% confidence limits = 1.89%, 3.68%). These associations held in both humid and dry locations and were independent of the correlation between the pollutants and weather or other pollutants. The effect size estimates for PM10 and CO likewise showed no association with their correlation in each location, as one would expect if one pollutant were merely a proxy for the other. The PM10 effects are consistent with recent animal data showing cardiovascular effects and with preliminary human data showing effects on heart rate variability and plasma viscosity. The CO results are consistent with literature on angina exacerbations. (Epidemiology 1999;10:17–22)
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Metadata
- Authors
- Schwartz, J.
- Venue
- Epidemiology
- Published
- 1999-01
- Volume
- 10
- Issue
- 1
- Pages
- 17-22
- ISSN
- 1044-3983 (ISSN-L)
- OpenAlex
- W2062594082
- Cited by
- 3,038
- References
- 5
- FWCI
- 28.96
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.