Evaluating temporally decomposed associations between PM2.5 and hospitalisation risks of AECOPD: A case study in Beijing from 2010 to 2019

Abstract

Few studies investigated relative contributions of PM2.5 concentration at multiple time-scales (short-term, seasonal and long-term periods) on the hospitalisation risk for acute exacerbation of COPD (AECOPD). In this study, we specified and discriminated the short-term, seasonal and long-term trend effects of PM2.5 concentration on the hospitalisation for AECOPD in Beijing between 2010 and 2019. Daily PM2.5 observations from US Beijing Embassy from Jan 1, 2010, to Dec 31, 2019 (3652 days) were decomposed to short-term, seasonal and long-term trend components by using the robust Kolmogorov-Zurbenko filter. During the study period, daily counts of AECOPD hospitalisation were obtained from a database compiled by Beijing Public Health Information Center. Two separate generalized additive models were built to assess effects of raw PM2.5 concentrations and the three decomposed components of time-scales on hospitalisation of AECOPD in Beijing. We found raw PM2.5 concentrations were associated with AECOPD in Beijing with a 10 μg/m3 increase corresponding to 0.46% (95% CI: 0.40%–0.52%) increase in hospitalisation. In the model of decomposed PM2.5 time-series, both the short-term and long-term components exhibited statistically significant positive association with AECOPD, which, respectively, was associated to 0.42% (95% CI: 0.36%–0.48%) and 6.91% (95% CI: 6.08%–7.74%) increase in AECOPD hospitalisation per 10 μg/m3 increase. The seasonal trend had an insignificant U-shaped relationship with AECOPD. Our study simultaneously confirmed that a statistically significant positive association between the raw PM2.5 concentrations, the decomposed short-term and long-term trend of PM2.5 concentrations and increased risk for AECOPD hospitalisation. Strong long-term effects in this study indicated that stringent emission control measures would bring strong public health benefits concerning AECOPD.