Assessing the Association between Cardiovascular Diseases and Short-Term Exposure to Particulate Matter and Nitrogen Dioxide with Land Use Regression Models
Date Issued
2014
Date
2014
Author(s)
Shen, Fu-Hui
Abstract
Background:
The study was designed to combine air quality monitoring data with land use data to build land use regression (LUR) models in Taipei Metropolis to predict individualized traffic-related air pollutants exposure levels and linked with cardiovascular endpoints to discuss the association between short-term traffic-related air pollution and acute cardiovascular effects.
Method:
We selected 117 subjects working at a bank to have health examination in February, June, and September in 2013. The health examinations included general medical examination and cardiovascular screening. Additionally, we monitored air quality at the subjects’ workplaces over the period of health examination. We also collected information on the subjects’ home addresses and time-activity patterns to predict individualized PM2.5 and NO2 exposures at the subjects’ home addresses by land use regression models. Three exposure assessment methods were developed to represent personal exposure: (1) LUR models, (2) LUR models combine with indoor air monitoring, and (3) Nearest station. For cardiovascular markers, we used the inflammation maker (High-sensitivity CRP, hsCRP) and the markers for the arterial stiffness (baPWV and ABI) as our health endpoints.
Results:
With regard to the different exposure assessment methods, we found that using LUR models combining with indoor air monitoring data had a better explanation on the relationship with acute cardiovascular effects. With regard to the association between traffic-related air pollutants and cardiovascular endpoints, we found that both PM2.5 and NO2 was significantly associated with baPWV, and NO2 was significantly associated with hsCRP. However, ABI was not found to be associated with traffic-related air pollutants.
Conclusion:
We were able to develop land use regression models by combining air-quality monitoring data with geographic variables to predict personal exposure in Taipei Metropolis. These LUR models were applied to link with the subjects’ health data. It was found that acute cardiovascular effects were significantly associated with short-term traffic-related air pollution.
Subjects
土地利用模式
細懸浮微粒
二氧化氮
急性心血管效應
Type
thesis
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