scholarly journals A New Multipollutant, No-Threshold Air Quality Health Index Based on Short-Term Associations Observed in Daily Time-Series Analyses

2008 ◽  
Vol 58 (3) ◽  
pp. 435-450 ◽  
Author(s):  
David M. Stieb ◽  
Richard T. Burnett ◽  
Marc Smith-Doiron ◽  
Orly Brion ◽  
Hwashin Hyun Shin ◽  
...  
2019 ◽  
Vol 3 ◽  
pp. 185
Author(s):  
Johansson C ◽  
Olstrup H ◽  
Forsberg B ◽  
Ekebom A ◽  
Meister K ◽  
...  

2019 ◽  
Author(s):  
Tonya G. Mason ◽  
C. Mary Schooling ◽  
King Pan Chan ◽  
Linwei Tian

AbstractBackgroundOn December 30th, 2013, the Hong Kong government implemented the Air Quality Health Index (AQHI) to reduce short-term impacts of air pollution on the population. However, whether air quality alert programs, such as the AQHI, reduce morbidity is still questionable. Using a quasi-experimental design, we conducted the first evaluation of the AQHI in Hong Kong focusing on respiratory morbidity.MethodInterrupted time series with Poisson segmented regression from 2010 to 2016 were used to detect any sudden or gradual changes in emergency respiratory hospital admissions, adjusted for air pollutants (NO2, SO2, PM10, O3), temperature and humidity, when the AQHI policy was implemented. Findings were validated using three false policy periods. We also assessed changes by specific respiratory diseases (respiratory tract infections (RTI), asthma, chronic obstructive pulmonary disease and pneumonia) and by age.ResultsFrom January 1st, 2010-December 31st, 2016, 10576.98 deseasonalized, age- and sex-standardized hospital admissions for respiratory diseases occurred in Hong Kong. On implementation of the AQHI, RTI admissions immediately dropped by 14% (relative risk (RR) 0.86 95% confidence interval (CI) 0.76-0.98). In age specific analysis, immediate reductions in hospital admissions, were only apparent in children for RTI (RR 0.84, 95% CI 0.74-0.96) and pneumonia (RR 0.88, 95% CI 0.60-0.96).ConclusionHong Kong’s AQHI helped reduced hospital admissions in children, particularly for RTI and pneumonia. To maximize the health benefits of the policy, at risk groups need to be able to follow the behavioral changes recommended by the AQHI index.


2013 ◽  
Vol 121 (1) ◽  
pp. 46-52 ◽  
Author(s):  
Teresa To ◽  
Shixin Shen ◽  
Eshetu G. Atenafu ◽  
Jun Guan ◽  
Susan McLimont ◽  
...  

2018 ◽  
Vol 48 (2) ◽  
pp. 67-76 ◽  
Author(s):  
Eman Abdellatef ◽  
Gehan Zaki ◽  
Ahmed Issa

Author(s):  
Henrik Olstrup ◽  
Christer Johansson ◽  
Bertil Forsberg ◽  
Andreas Tornevi ◽  
Agneta Ekebom ◽  
...  

In this study, an Air Quality Health Index (AQHI) for Stockholm is introduced as a tool to capture the combined effects associated with multi-pollutant exposure. Public information regarding the expected health risks associated with current or forecasted concentrations of pollutants and pollen can be very useful for sensitive persons when planning their outdoor activities. For interventions, it can also be important to know the contribution from pollen and the specific air pollutants, judged to cause the risk. The AQHI is based on an epidemiological analysis of asthma emergency department visits (AEDV) and urban background concentrations of NOx, O3, PM10 and birch pollen in Stockholm during 2001–2005. This analysis showed per 10 µg·m–3 increase in the mean of same day and yesterday an increase in AEDV of 0.5% (95% CI: −1.2–2.2), 0.3% (95% CI: −1.4–2.0) and 2.5% (95% CI: 0.3–4.8) for NOx, O3 and PM10, respectively. For birch pollen, the AEDV increased with 0.26% (95% CI: 0.18–0.34) for 10 pollen grains·m–3. In comparison with the coefficients in a meta-analysis, the mean values of the coefficients obtained in Stockholm are smaller. The mean value of the risk increase associated with PM10 is somewhat smaller than the mean value of the meta-coefficient, while for O3, it is less than one fifth of the meta-coefficient. We have not found any meta-coefficient using NOx as an indicator of AEDV, but compared to the mean value associated with NO2, our value of NOx is less than half as large. The AQHI is expressed as the predicted percentage increase in AEDV without any threshold level. When comparing the relative contribution of each pollutant to the total AQHI, based on monthly averages concentrations during the period 2015–2017, there is a tangible pattern. The AQHI increase associated with NOx exhibits a relatively even distribution throughout the year, but with a clear decrease during the summer months due to less traffic. O3 contributes to an increase in AQHI during the spring. For PM10, there is a significant increase during early spring associated with increased suspension of road dust. For birch pollen, there is a remarkable peak during the late spring and early summer during the flowering period. Based on monthly averages, the total AQHI during 2015–2017 varies between 4 and 9%, but with a peak value of almost 16% during the birch pollen season in the spring 2016. Based on daily mean values, the most important risk contribution during the study period is from PM10 with 3.1%, followed by O3 with 2.0%.


2020 ◽  
Vol 70 (10) ◽  
pp. 1009-1021
Author(s):  
Jeffrey Trieu ◽  
Jiayun Yao ◽  
Kathleen E. McLean ◽  
Dave M. Stieb ◽  
Sarah B. Henderson

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