Ambient air pollution and respiratory disease

1991 ◽  
Vol 154 (8) ◽  
pp. 543-553 ◽  
Author(s):  
Michael Abramson ◽  
Tom Voigt
Author(s):  
Lisha Luo ◽  
Yunquan Zhang ◽  
Junfeng Jiang ◽  
Hanghang Luan ◽  
Chuanhua Yu ◽  
...  

In this study, we estimated the short-term effects of ambient air pollution on respiratory disease hospitalization in Taiyuan, China. Daily data of respiratory disease hospitalization, daily concentration of ambient air pollutants and meteorological factors from 1 October 2014 to 30 September 2017 in Taiyuan were included in our study. We conducted a time-series study design and applied a generalized additive model to evaluate the association between every 10-μg/m3 increment of air pollutants and percent increase of respiratory disease hospitalization. A total of 127,565 respiratory disease hospitalization cases were included in this study during the present period. In single-pollutant models, the effect values in multi-day lags were greater than those in single-day lags. PM2.5 at lag02 days, SO2 at lag03 days, PM10 and NO2 at lag05 days were observed to be strongly and significantly associated with respiratory disease hospitalization. No significant association was found between O3 and respiratory disease hospitalization. SO2 and NO2 were still significantly associated with hospitalization after adjusting for PM2.5 or PM10 into two-pollutant models. Females and younger population for respiratory disease were more vulnerable to air pollution than males and older groups. Therefore, some effective measures should be taken to strengthen the management of the ambient air pollutants, especially SO2 and NO2, and to enhance the protection of the high-risk population from air pollutants, thereby reducing the burden of respiratory disease caused by ambient air pollution.


2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Nalini Sathiakumar ◽  
Meghan Tipre ◽  
Mark Leader ◽  
Ilene Brill ◽  
Jason Kirby ◽  
...  

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Nhung Thi Trang Nguyen ◽  
Christian Schindler ◽  
Dien Minh Tran ◽  
Chau Quy Ngo ◽  
Hoang Tu Le ◽  
...  

Author(s):  
Sajith Priyankara ◽  
Mahesh Senarathna ◽  
Rohan Jayaratne ◽  
Lidia Morawska ◽  
Sachith Abeysundara ◽  
...  

Evidence of associations between exposure to ambient air pollution and health outcomes are sparse in the South Asian region due to limited air pollution exposure and quality health data. This study investigated the potential impacts of ambient particulate matter (PM) on respiratory disease hospitalization in Kandy, Sri Lanka for the year 2019. The Generalized Additive Model (GAM) was applied to estimate the short-term effect of ambient PM on respiratory disease hospitalization. As the second analysis, respiratory disease hospitalizations during two distinct air pollution periods were analyzed. Each 10 μg/m3 increase in same-day exposure to PM2.5 and PM10 was associated with an increased risk of respiratory disease hospitalization by 1.95% (0.25, 3.67) and 1.63% (0.16, 3.12), respectively. The effect of PM2.5 or PM10 on asthma hospitalizations were 4.67% (1.23, 8.23) and 4.04% (1.06, 7.11), respectively (p < 0.05). The 65+ years age group had a higher risk associated with PM2.5 and PM10 exposure and hospital admissions for all respiratory diseases on the same day (2.74% and 2.28%, respectively). Compared to the lower ambient air pollution period, higher increased hospital admissions were observed among those aged above 65 years, males, and COPD and pneumonia hospital admissions during the high ambient air pollution period. Active efforts are crucial to improve ambient air quality in this region to reduce the health effects.


2018 ◽  
Vol 24 (1) ◽  
Author(s):  
V. S. CHAUHAN ◽  
BHANUMATI SINGH ◽  
SHREE GANESH ◽  
JAMSHED ZAIDI

Studies on air pollution in large cities of India showed that ambient air pollution concentrations are at such levels where serious health effects are possible. This paper presents overview on the status of air quality index (AQI) of Jhansi city by using multivariate statistical techniques. This base line data can help governmental and non-governmental organizations for the management of air pollution.


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