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Open AccessJournal ArticleDOI

Association between particulate matter and emergency room visits, hospital admissions and mortality in Spokane, Washington

TLDR
It is felt that carbon monoxide may be serving as a marker for combustion-derived pollutants, which is one large component of the diverse air pollutant mixture.
Abstract: 
There is conflicting evidence regarding the association between different size fractions of particulate matter (PM) and cardiac and respiratory morbidity and mortality. We investigated the short-term associations of four size fractions of particulate matter (PM(1), PM(2.5), PM(10), and PM(10-2.5)) and carbon monoxide with hospital admissions and emergency room (ER) visits for respiratory and cardiac conditions and mortality in Spokane, Washington. We used a log-linear generalized linear model to compare daily averages of PM and carbon monoxide with daily counts of the morbidity and mortality outcomes from January 1995 to June 2001. We examined pollution lags ranging from 0 to 3 days and compared our results to a similar log-linear generalized additive model. Effect estimates tended to be smaller and have larger standard errors for the generalized linear model. Overall, we saw no association with respiratory ER visits and any size fraction of PM. However, there was a suggestion of greater respiratory effect from fine PM when compared to coarse fraction. Carbon monoxide was associated with both all respiratory ER visits and visits for asthma at the 3-day lag. We feel that carbon monoxide may be serving as a marker for combustion-derived pollutants, which is one large component of the diverse air pollutant mixture. We also found no association with any size fraction of PM or CO with cardiac hospital admissions or mortality at the 0- to 3-day lag. We found no consistent associations between any size fraction of PM and cardiac or respiratory ER visits or hospital admissions.

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Citations
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Journal ArticleDOI

Epidemiological evidence of effects of coarse airborne particles on health

TL;DR: It is concluded that special consideration should be given to studying and regulating coarse particles separately from fine particles, suggesting that coarse PM may lead to adverse responses in the lungs triggering processes leading to hospital admissions.
Journal ArticleDOI

Tree and forest effects on air quality and human health in the United States

TL;DR: Computer simulations with local environmental data reveal that trees and forests in the conterminous United States removed 17.4 million tonnes of air pollution in 2010, with human health effects valued at 6.8 billion U.S. dollars (range: $1.5-13.0 billion).
Journal ArticleDOI

Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects.

TL;DR: Understanding the impact of urban trees on air quality can lead to improved urban forest management strategies to sustain human health in cities.
Journal ArticleDOI

Association between Air Pollutants and Asthma Emergency Room Visits and Hospital Admissions in Time Series Studies: A Systematic Review and Meta-Analysis.

TL;DR: Short-term exposures to air pollutants account for increased risks of asthma-related ERVs and hospitalizations that constitute a considerable healthcare utilization and socioeconomic burden.
Journal ArticleDOI

Associations between health effects and particulate matter and black carbon in subjects with respiratory disease.

TL;DR: Results from this study indicate that FENO may be a more sensitive marker of PM exposure than traditional health outcomes and that particle-associated BC is useful for examining associations between primary combustion constituents of PM and health outcomes.
References
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Book

Generalized Linear Models

TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Proceedings Article

Information Theory and an Extention of the Maximum Likelihood Principle

H. Akaike
TL;DR: The classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion to provide answers to many practical problems of statistical model fitting.
Book ChapterDOI

Information Theory and an Extension of the Maximum Likelihood Principle

TL;DR: In this paper, it is shown that the classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion.
Journal ArticleDOI

Generalized Additive Models.

R. A. Brown, +2 more
- 01 Jun 1991 - 
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