Online Appendix for Effects of Short-Term Air Pollution Exposure on U.S. COVID-19 Mortality

2022 ◽  
Author(s):  
Ruohao Zhang ◽  
Jeffrey Whittle ◽  
Vladimir A. Atanasov ◽  
John Meurer ◽  
Paula Natalia Barreto Parra ◽  
...  
Keyword(s):  
Air Pollution ◽  
Short Term ◽  
Online Appendix ◽  
Air Pollution Exposure ◽  
Pollution Exposure

Association between lung function of school age children and short-term exposure to air pollution and pollen: the PARIS cohort

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-215515
Author(s):  
Hélène Amazouz ◽  
Nicolas Bougas ◽  
Michel Thibaudon ◽  
Guillaume Lezmi ◽  
Nicole Beydon ◽  
...  
Keyword(s):  
Air Pollution ◽  
Lung Function ◽  
School Age Children ◽  
School Age ◽  
Short Term ◽  
Short Term Exposure ◽  
Air Pollution Exposure ◽  
Total Pollen ◽  
Pollution Exposure ◽  
Cluster 2

BackgroundDaily levels of ambient air pollution and pollen may affect lung function but have rarely been studied together. We investigated short-term exposure to pollen and air pollution in relation to lung function in school-age children from a French population-based birth cohort.MethodsThis study included 1063 children from the PARIS (Pollution and Asthma Risk: an Infant Study) cohort whose lung function and FeNO measurements were performed at age 8 years old. Exposure data were collected up to 4 days before testing. We estimated daily total pollen concentration, daily allergenic risk indices for nine pollen taxa, as well as daily concentrations of three air pollutants (particulate matter less than 10 µm (PM10), nitrogen dioxide (NO2), ozone (O3)). Children with similar pollen and air pollution exposure were grouped using multidimensional longitudinal cluster analysis. Associations between clusters of pollen and air pollution exposure and respiratory indices (FEV1, FVC, FeNO) were studied using multivariable linear and logistic regression models adjusted for potential confounders.ResultsFour clusters of exposure were identified: no pollen and low air pollution (Cluster 1), grass pollen (Cluster 2), PM10 (Cluster 3) and birch/plane-tree pollen with high total pollen count (Cluster 4). Compared with children in Cluster 1, children in Cluster 2 had significantly lower FEV1 and FVC levels, and children from Cluster 3 had higher FeNO levels. For FEV1 and FVC, the associations appeared stronger in children with current asthma. Additional analysis suggested a joint effect of grass pollen and air pollution on lung function.ConclusionDaily ambient chemical and biological air quality could adversely influence lung function in children.

scholarly journals Short-term air pollution exposure decreases lung function: a repeated measures study in healthy adults

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Luc Int Panis ◽  
Eline B Provost ◽  
Bianca Cox ◽  
Tijs Louwies ◽  
Michelle Laeremans ◽  
...  
Keyword(s):  
Air Pollution ◽  
Lung Function ◽  
Repeated Measures ◽  
Healthy Adults ◽  
Short Term ◽  
Air Pollution Exposure ◽  
Pollution Exposure

scholarly journals Design and evaluation of mobile monitoring campaigns for air pollution exposure assessment in epidemiologic cohorts

2021 ◽  
Author(s):  
Magali N. Blanco ◽  
Annie Doubleday ◽  
Elena Austin ◽  
Julian D. Marshall ◽  
Edmund Seto ◽  
...  
Keyword(s):  
Air Pollution ◽  
Study Design ◽  
Monitoring Data ◽  
Mobile Monitoring ◽  
Short Term ◽  
Balanced Design ◽  
Air Pollution Exposure ◽  
Balanced Designs ◽  
Pollution Exposure

AbstractMobile monitoring makes it possible to estimate the long-term trends of less commonly measured pollutants through the collection of repeated short-term samples. While many different mobile monitoring approaches have been taken, few studies have looked at the importance of study design when the goal is application to epidemiologic cohort studies. Air pollution concentrations include random variability and systematic variability, and we hypothesize that mobile campaigns benefit from temporally balanced designs that randomly sample from all seasons of the year, days of the week, and hours of the day. We carried out a simulation study of fixed-site monitors to better understand the role of short-term mobile monitoring design on the prediction of long-term air pollution exposure surfaces. Specifically, we simulated three archetypal sampling designs using oxides of nitrogen (NOx) monitoring data from 69 California air quality system (AQS) sites: (1) a year-around, Balanced Design, (2) a Rush Hours Design, and (3) a Business Hours Design. We used Monte Carlo resampling to investigate the range of possible outcomes (i.e., the resulting annual average concentration prediction) from each design against the “truth”, the actual monitoring data. We found that the Balanced Design consistently yielded the most accurate annual averages; Rush Hours and Business Hours Designs generally resulted in comparatively more biased estimates and model predictions. Importantly, the superior performance of the Balanced Design was evident when predictions were evaluated against true concentrations but less detectable when predictions were evaluated against the measurements from the same sampling campaign since these were themselves biased. This result is important since mobile monitoring campaigns that use their own measurements to test the robustness of the results may underestimate the level of bias in their results. Appropriate study design is crucial for mobile monitoring campaigns aiming to assess accurate long-term exposure in epidemiologic cohorts. Campaigns should aim to implement balanced designs that sample during all seasons of the year, days of the week, and all or most hours of the day to produce generally unbiased, long-term averages. Furthermore, differential exposure misclassification could result from unbalanced designs, which may result in misleading health effect estimates in epidemiologic investigations.

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