Background
Air quality health index (AQHI) has been widely used to quantify the health effects of multiple pollutants observed in population-based epidemiological studies, and can better reflect the widespread linear non-threshold between air pollution and health effects.
Objective
To explore an AQHI for pediatric respiratory diseases (AQHIr) in Shanghai and evaluate its feasibility.
Methods
The daily numbers of hospital outpatient visits for pediatric respiratory diseases from 2015 to 2019 were obtained from five general hospitals in Xuhui, Baoshan, Hongkou, Jinshan, and Chongming Districts of Shanghai. Monitoring data on air pollutants (PM2.5, PM10, SO2, NO2, and O3), air quality index (AQI), and meteorological variables (temperature, relative humidity, air pressure, and wind speed) were collected from five air quality monitoring sites nearest to selected hospitals. Time-series analysis using generalized additive model (GAM) was conducted to estimate the associations between respiratory-related pediatric outpatient visits and the concentrations of air pollutants. The sum of excess risk (ER) of hospital outpatient visits was used to construct AQHIr. To assess the predictive power of AQHIr, the associations of AQHIr and AQI with the number of pediatric respiratory outpatient visits in three hospitals in Xuhui, Hongkou, and Chongming districts were compared.
Results
Air pollutants had various effects on respiratory diseases outpatient visits. PM2.5, NO2, and O3 had most significant impacts on lag0 day and the associated ERs of hospital outpatient visits for each 10 μg·m−3 increase in pollutant concentration were 1.27% (95%CI: 0.88%-1.66%), 0.75% (95%CI: 0.40%-1.11%), and 0.36% (95%CI: 0.10%-0.62%), respectively. PM10 and SO2 had most significant impacts on lag3 day and the associated ERs of hospital outpatient visits for each 10 μg·m−3 increase in pollutant concentration were 0.81% (95%CI: 0.51%-1.12%) and 5.64% (95%CI: 3.37%-7.96%), respectively. There were significant effects of combinations of two pollutants among PM2.5, PM10, NO2, SO2, and O3 except for PM10+NO2, SO2+PM2.5, and SO2+NO2 (P<0.05). According to the results of single-pollutant and two-pollutant models, PM2.5, NO2, SO2, and O3 were selected to construct AQHIr. The comparison showed that for every interquartile range increase in AQHIr, the ER for pediatric outpatient visits was higher than that for the value corresponding to AQI.
Conclusion
Air pollutants in Shanghai have an impact on the number of pediatric respiratory outpatient visits. The AQHIr based on and outpatient visits for pediatric respiratory diseases can be a sensitive index to predict the effects of air pollution on children's respiratory health.
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