Associations of PM_2.5, NO₂, and air quality index (AQI) with sickness absenteeism of primary school students in Shanghai

Background The influences of air pollution on sickness absenteeism among school students could be a huge social medical and economic burden.

Objective This study aims to quantify the associations of air pollutants and air quality index (AQI) with sickness absenteeism of primary school students in Shanghai.

Methods Six primary schools were selected in four districts of Shanghai (Jiading, Baoshan, Pudong, and Putuo), and data on daily sickness absenteeism and specific causes of sickness (excluding personal reasons or accidental events) were collected in 2017 and 2018 school years from all the students from the six schools, as well as daily levels of air pollutants and meteorological factors from nearest fixed-site monitoring stations. A generalized additive model was constructed to conduct time-series analysis on the associations of air pollutants and AQI with sickness absenteeism after adjusting for confounding factors including temperature, relative humidity, precipitation, influenza outbreak season, and day-of-the-week effect.

Results A total of 5 746 students were included in this study. The average daily sickness absenteeism in school days was 12.5, accounting for 0.20% of the total students who were supposed to attend school; the average daily sickness absenteeism in winter and spring was higher than that in summer and autumn; the average daily sickness absenteeism in influenza season was higher than that in non-influenza season (all P < 0.05). During the study period, the annual daily average PM_2.5 and NO₂ concentrations were (38.7±26.0) μg·m^-3 and (42.7±18.8) μg·m^-3, respectively. After adjusting for confounding factors, the results of multivariate regression analysis showed that every 10 μg·m^-3 increase of NO₂ concentration was associated with an increase of sickness absentees by 2.3%-3.3%, and the effects lasted for at least one week, while AQI and PM_2.5 had no obvious associations with children's sickness absenteeism. The results of stratification analysis by influenza season showed that PM_2.5, NO₂, and AQI had associations with sickness leave in non-influenza season, with RR (95% CI) of 1.021 (1.004-1.039), 1.048 (1.026-1.071), and 1.015 (1.001-1.030), respectively.

Conclusion In the 2017-2018 school years in Shanghai, NO₂ is associated with sickness absenteeism in primary school students. Further efforts are needed to figure out whether school children's health can be managed purely by AQI.