Abstract
Air quality has been long known to be strongly related to human health. Many studies have assessed the impact of air pollution on human health. This case study illustrates how to conduct a statistical study related to air pollution and health issues using the statistical methods introduced in the previous chapter. This case study is to examine if PM2.5 contributes to the incidence of lung and bronchial cancers in the United States. Statistical analyses, such as descriptive statistics, scatter plots, time series analyses, generalized linear regression models, and lagged regression, are used to explore the relationship between the lung and bronchial cancer annual rates and PM2.5 values at both national and state levels.
Original language | American English |
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Title of host publication | Spatiotemporal Analysis of Air Pollution and Its Application in Public Health |
DOIs | |
State | Published - Nov 22 2019 |
Disciplines
- Public Health
- Biostatistics
- Environmental Public Health
- Epidemiology
Keywords
- Air pollution
- Lung and bronchial cancers
- PM2.5
- Regression analysis
- Spatiotemporal interpolation
- Time series analysis