Characterization and Triggers of Dyspnea in Patients with Chronic Obstructive Pulmonary Disease or Chronic Heart Failure: Effects of Weather and Environment

Atmospheric pollen concentrations and chronic obstructive pulmonary disease (COPD) patients visits in Beijing: time series analysis using a generalized additive model

To investigate the correlation between the daily visits of chronic obstructive pulmonary disease (COPD) patients in hospital clinic and pollen concentrations in Beijing. We collected daily visits of COPD patients of Beijing Shijitan Hospital from April 1st, 2019 to September 30th, 2019. The relationship between pollen concentrations and COPD patient number was analyzed with meteorological factors, time trend, day of the week effect and holiday effect being controlled by the generalized additive model of time series analysis. R4.1.2 software was applied to generate Spearman correlation coefficient, specific and incremental cumulative effect curves of relative risks as well as the response and three-dimensional diagrams for the exposure lag effect prediction. The fitting models were used to predict the lag relative risk and 95% confidence intervals for specific and incremental cumulative effects of specific pollen concentrations. The number of COPD patients was positively correlated with pollen concentration. When pollen concentration increased by 10 grains/1000 mm2, the peak value of the specific cumulative effect appeared on day0, with the effect gone on day4 and a lag time of 4 days observed, whereas the incremental cumulative effect's peak value was shown on day17, and the effect disappeared on day18, with a lag time of 18 days. The results showed that pollen concentration was not only positively correlated with the number of COPD patients, but also had a bimodal lag effect on COPD visits in the hospital at Beijing.