Objective To realize the prevalence of absenteeism caused by respiratory symptoms among Shanghai primary and middle school students, and investigate the relationships between the absenteeism and air pollutants.
Methods Absenteeism, air pollutants, and temperature data from 2013 to 2016 in Shanghai were collected. The prevalence of absenteeism caused by respiratory symptoms was estimated. Principal component analysis was used for combining air pollutants and temperature into a comprehensive indicator. Multiple linear regression model was used to assess the relationships between absenteeism and selected air pollutants.
Results Totally 667 978 person-days of absenteeism due to respiratory symptoms were recorded from 2013 to 2016, and the absenteeism rate was 0.71‰. The absenteeism rates in winter and spring were higher than the other seasons. As the eigenvalues of the first principal component and the second principal component were both greater than 1, their accumulated contribution rate reached 84%, and these two principal components were selected for the following multiple linear regression analysis. With every 1 μg/m3 increase of PM2.5, PM10, SO2, and NO2, and every 1 mg/m3 increase of CO, the absenteeism rate due to respiratory symptoms rose 0.54‰, 0.51‰, 0.70‰, 0.94‰, and 0.01‰ respectively. With every 1 μg/m3 increment of O3 daily maximum 8 h concentration and every 1℃ increase of temperature, the absenteeism rate due to respiratory symptoms fell 5.51‰ and 0.94‰, respectively.
Conclusion The absenteeism rate due to respiratory symptoms is correlated with levels of air pollutants and temperature in selected primary and middle school students in Shanghai.
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