Abstract:
In order to investigate the impact of air pollution episode characterized by persistent high PM
2.5 exposure on people's hospitalization in Beijing, we collected data of air pollutants, meteorological factors and hospital admissions in Beijing from 2013 to 2018. Under six persistent PM
2.5-polluted scenarios defined by PM
2.5 concentration (75.0 μg/m
3, 150.0 μg/m
3, P
95 (205.8 μg/m
3)) and duration (≥2 d, ≥3 d), generalized additive models (GAM) based on quasi-Poisson regression were used to carry out time series analyses to obtain the impact of air pollution episode characterized by persistent high exposure to PM
2.5 on hospitalizations of the entire population and subgroups. The results showed that: (1) For the entire population, relative to non-specified pollution scenarios, when the PM
2.5 exposure concentration was >150 μg/m
3 and lasted for two days or more, the hospitalization risk for non-accidental diseases and cardio-cerebrovascular diseases increased by 5.0% (95%CI, 1.2% to 9.0%) and 5.6% (95%CI, 1.8% to 9.5%), respectively. (2) A stratified analysis of subgroup populations found that under heavy PM
2.5-pollution scenarios that lasted for two days or more, non-accidental and cardio-cerebrovascular hospitalizations significantly increased in the subgroups of men, women, people 0-64 years old, people 65-74 years old, and people 75 years or older. In the extreme PM
2.5-pollution concentration (>205.8 μg/m
3) that lasted for three days or more, non-accidental and cardio-cerebrovascular hospitalizations significantly increased in only the subgroups of women, people 0-64 years old and people 65-74 years old. (3) For respiratory admissions, we only detected statistical significance when PM
2.5 exposure concentration was greater than 150.0 μg/m
3 and lasted for two days or more in the 0-64 years old population, and the risk increased by 3.4% (95%CI, 0.2% to 6.6%). This study shows that air pollution episode characterized by persistent high exposure to PM
2.5 had a significant impact on hospital admissions.