Comparing models of the effect of air pollutants on hospital admissions and symptoms for chronic obstructive pulmonary disease
Language English Country Czech Republic Media print
Document type Comparative Study, Journal Article
PubMed
23441395
DOI
10.21101/cejph.a3757
Knihovny.cz E-resources
- MeSH
- Bayes Theorem MeSH
- Pulmonary Disease, Chronic Obstructive epidemiology etiology MeSH
- Hospitalization statistics & numerical data MeSH
- Humans MeSH
- Linear Models MeSH
- Monte Carlo Method MeSH
- Neural Networks, Computer MeSH
- Poisson Distribution MeSH
- Predictive Value of Tests MeSH
- Air Pollution adverse effects MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Comparative Study MeSH
There is an increasing interest in the use of hospital admission for Chronic obstructive pulmonary disease (COPD) in studies of short-term exposure effects attributed to air pollutants. However, little is known about the effect of air pollutants on COPD symptoms. This study was undertaken to determine whether there was an association between air pollutant levels and both hospital admissions and symptoms for COPD. For model comparison, we present Generalized Linear Model, Generalized Additive Model and a general approach for Bayesian inference via Markov chain Monte Carlo in generalized additive model. Furthermore, for comparing the predictive accuracy, Artificial Neural Networks (ANN) approach is given.
References provided by Crossref.org