Traffic-Related Air Pollution and Respiratory Tract Efficiency

被引:12
|
作者
Badyda, A. J. [1 ,2 ]
Dabrowiecki, P. [2 ,3 ]
Czechowski, P. O. [4 ]
Majewski, G. [5 ]
Doboszynska, A. [2 ,6 ]
机构
[1] Warsaw Univ Technol, Fac Environm Engn, PL-00653 Warsaw, Poland
[2] Polish Federat Asthma Allergy & COPD Patients Ass, PL-00002 Warsaw, Poland
[3] Minist Natl Def, Mil Inst Med, Cent Clin Hosp, Warsaw, Poland
[4] Gdynia Maritime Univ, Dept Informat Syst, Gdynia, Poland
[5] Warsaw Univ Life Sci, Fac Civil & Environm Engn, Warsaw, Poland
[6] Univ Warmia & Mazury, Clin Pulmonol, Olsztyn, Poland
来源
ENVIRONMENT EXPOSURE TO POLLUTANTS | 2015年 / 834卷
关键词
Air pollution; Bronchial obstruction; Generalized regression model; Health; Pulmonary function; Traffic congestion; LONG-TERM EXPOSURE; HEALTH; POLLUTANTS; PARTICLES; TRANSPORT; MORTALITY; RISK;
D O I
10.1007/5584_2014_13
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
High concentrations of air pollutants are characteristic of the vicinity of urban busy roads. Numerous studies have shown that these concentrations are significantly higher in comparison with areas located in a certain distance from roads and especially those in rural areas. Inhabitants living in the proximity of roads are, therefore, likely to be more exposed to adverse effects of air pollutants. On the basis of a study realized in 2008-2012 among nearly 5,000 residents of Warsaw and non-urbanized areas, we used generalized linear regression models (GRM) to identify factors that most significantly influence the variability of respiratory function variables. GRMs combine multiple classes of models and estimation methods such as simple, multiple, or factorial regression, ANOVA, ANCOVA, etc. Therefore, they allow receiving results based also on interactions between the independent variables. This paper presents the results of GRM for the forced expiratory volume in 1 s (FEV1) distribution. They indicate that the variation of FEV1 is associated with personal factors such as age, height, weight, BMI, or gender, as well as with factors related to the place of residence: traffic density, duration, and the floor of residence. The results clearly show that living in the proximity of busy roads in the city is linked with a significant decrease in FEV1 values.
引用
收藏
页码:31 / 38
页数:8
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