scholarly journals Effects of indoor coal fine particulate matter on the expression levels of inflammatory factors in ovalbumin-induced mice

2019 ◽  
Vol 8 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Jie Yu ◽  
Yin Tang ◽  
Jie Xu

Objective: Cooking and heating with coal is the main source of household air pollution in acid rain-plagued areas of China and is a leading contributor to disease burden.

2018 ◽  
Vol 28 (4) ◽  
pp. 400-410 ◽  
Author(s):  
Jessica L. Elf ◽  
Aarti Kinikar ◽  
Sandhya Khadse ◽  
Vidya Mave ◽  
Nishi Suryavanshi ◽  
...  

Toxics ◽  
2016 ◽  
Vol 4 (3) ◽  
pp. 12 ◽  
Author(s):  
Kanyiva Muindi ◽  
Elizabeth Kimani-Murage ◽  
Thaddaeus Egondi ◽  
Joacim Rocklov ◽  
Nawi Ng

Author(s):  
Megan Benka-Coker ◽  
Maggie Clark ◽  
Sarah Rajkumar ◽  
Bonnie Young ◽  
Annette Bachand ◽  
...  

Household air pollution is estimated to be responsible for nearly three million premature deaths annually. Measuring fractional exhaled nitric oxide (FeNO) may improve the limited understanding of the association of household air pollution and airway inflammation. We evaluated the cross-sectional association of FeNO with exposure to household air pollution (24-h average kitchen and personal fine particulate matter and black carbon; stove type) among 139 women in rural Honduras using traditional stoves or cleaner-burning Justa stoves. We additionally evaluated interaction by age. Results were generally consistent with a null association; we did not observe a consistent pattern for interaction by age. Evidence from ambient and household air pollution regarding FeNO is inconsistent, and may be attributable to differing study populations, exposures, and FeNO measurement procedures (e.g., the flow rate used to measure FeNO).


2018 ◽  
Vol 120 ◽  
pp. 354-363 ◽  
Author(s):  
Matthew Shupler ◽  
William Godwin ◽  
Joseph Frostad ◽  
Paul Gustafson ◽  
Raphael E. Arku ◽  
...  

Author(s):  
Cavin K. Ward‐Caviness, ◽  
Mahdieh Danesh Yazdi, ◽  
Joshua Moyer, ◽  
Anne M. Weaver, ◽  
Wayne E. Cascio, ◽  
...  

Background Long‐term air pollution exposure is a significant risk factor for inpatient hospital admissions in the general population. However, we lack information on whether long‐term air pollution exposure is a risk factor for hospital readmissions, particularly in individuals with elevated readmission rates. Methods and Results We determined the number of readmissions and total hospital visits (outpatient visits+emergency room visits+inpatient admissions) for 20 920 individuals with heart failure. We used quasi‐Poisson regression models to associate annual average fine particulate matter at the date of heart failure diagnosis with the number of hospital visits and 30‐day readmissions. We used inverse probability weights to balance the distribution of confounders and adjust for the competing risk of death. Models were adjusted for age, race, sex, smoking status, urbanicity, year of diagnosis, short‐term fine particulate matter exposure, comorbid disease, and socioeconomic status. A 1‐µg/m 3 increase in fine particulate matter was associated with a 9.31% increase (95% CI, 7.85%–10.8%) in total hospital visits, a 4.35% increase (95% CI, 1.12%–7.68%) in inpatient admissions, and a 14.2% increase (95% CI, 8.41%–20.2%) in 30‐day readmissions. Associations were robust to different modeling approaches. Conclusions These results highlight the potential for air pollution to play a role in hospital use, particularly hospital visits and readmissions. Given the elevated frequency of hospitalizations and readmissions among patients with heart failure, these results also represent an important insight into modifiable environmental risk factors that may improve outcomes and reduce hospital use among patients with heart failure.


2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.


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