Fluctuations in air pollution give risk warning signals of asthma hospitalization
Journal
Atmospheric Environment
Journal Volume
75
Pages
206-216
Date Issued
2013
Author(s)
Hsieh N.-H.
Abstract
Recent studies have implicated that air pollution has been associated with asthma exacerbations. However, the key link between specific air pollutant and the consequent impact on asthma has not been shown. The purpose of this study was to quantify the fluctuations in air pollution time-series dynamics to correlate the relationships between statistical indicators and age-specific asthma hospital admissions. An indicators-based regression model was developed to predict the time-trend of asthma hospital admissions in Taiwan in the period 1998-2010. Five major pollutants such as particulate matters with aerodynamic diameter less than 10μm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) were included. We used Spearman's rank correlation to detect the relationships between time-series based statistical indicators of standard deviation, coefficient of variation, skewness, and kurtosis and monthly asthma hospitalization. We further used the indicators-guided Poisson regression model to test and predict the impact of target air pollutants on asthma incidence. Here we showed that standard deviation of PM10 data was the most correlated indicators for asthma hospitalization for all age groups, particularly for elderly. The skewness of O3 data gives the highest correlation to adult asthmatics. The proposed regression model shows a better predictability in annual asthma hospitalization trends for pediatrics. Our results suggest that a set of statistical indicators inferred from time-series information of major air pollutants can provide advance risk warning signals in complex air pollution-asthma systems and aid in asthma management that depends heavily on monitoring the dynamics of asthma incidence and environmental stimuli. ? 2013 Elsevier Ltd.
Subjects
Air pollution; Asthma hospitalization; Fluctuation; Risk; Statistical indicators; Warning signal
SDGs
Other Subjects
Asthma hospitalization; Coefficient of variation; Environmental stimuli; Fluctuation; Poisson regression models; Spearman's rank correlation; Statistical indicators; Warning signals; Air pollution; Carbon monoxide; Higher order statistics; Hospitals; Information management; Nitrogen oxides; Particles (particulate matter); Poisson distribution; Regression analysis; Risks; Statistics; Sulfur dioxide; Diseases; carbon dioxide; nitrogen dioxide; ozone; sulfur dioxide; asthma; atmospheric pollution; health impact; health risk; hospital sector; monitoring; numerical model; oxide; ozone; particulate matter; time series analysis; adolescent; adult; aged; air pollutant; air pollution; air quality; article; asthma; child; correlation coefficient; hospital admission; hospitalization; human; infant; major clinical study; particulate matter; Poisson distribution; prediction; preschool child; priority journal; school child; time series analysis
Type
journal article