Short-term effects of air pollutants on outpatient volume of respiratory diseases in Guiyang
- VernacularTitle:贵阳市空气污染物对呼吸系统疾病门诊量的短期效应
- Author:
Juan DU
1
;
Yingping TANG
1
;
Ping HE
1
;
Li JIANG
1
Author Information
- Publication Type:Investigation
- Keywords: air pollutant; respiratory disease; distributed lag nonlinear model; fine particulate matter; nitrogen dioxide; carbon monoxide; sulfur dioxide; ozone
- From: Journal of Environmental and Occupational Medicine 2024;41(1):62-69
- CountryChina
- Language:Chinese
- Abstract: Background Affected by concentration, composition, and population tolerance of air pollutants, the relationship between air pollutants and population health has regional differences. There is still a research gap in Guiyang. Objective To explore the short-term effects of air pollutant concentrations in low-pollution areas on the outpatient volume of respiratory diseases. Methods Spearman correlation analysis was used to evaluate the correlation between air pollutants, meteorological factors, and respiratory outpatient volume from January 1, 2013 to December 31, 2020 in Guiyang City. A single pollutant distribution lag nonlinear model and a multi-pollutant interaction model were established based on Poisson distribution. A three-dimensional diagram was drawn to display the relationship between air pollutants and respiratory outpatient volume. Quantitative analysis was conducted on the attribution risk and lag effect of air pollutant concentration on outpatient volume of respiratory diseases in Guiyang City. Results The results of the single pollutant model showed that fine particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) elevated the outpatient volume of respiratory diseases. The maximum relative risk (RR) and 95%CI values of PM2.5, NO2,CO, and SO2 appeared on Day 2, 0, 5, and 6, respectively, which were 1.019 (1.015, 1.023), 1.146 (1.122, 1.171), 1.129 (1.116, 1.143), and 1.046(1.040, 1.052), respectively. For every quartile concentration increment of PM2.5, NO2, CO, or SO2, the outpatient volume of respiratory diseases increased by 0.943% (0.111%, 1.782%), 4.050% (3.573%, 4.529%), 0.595% (0.317%, 0.874%), or 0.667% (0.235%, 1.100%), respectively. The maximum RR (95%CI) of O3 was 1.015 (1.007, 1.023) and appeared on Day 0. The results of multi-pollutant model showed that PM2.5, NO2, CO, SO2, and O3 all elevated the outpatient volume of respiratory diseases. The maximum RR values of PM2.5, NO2, CO, SO2 and O3 appeared on Day 14, 0, 5, 7 and 0, respectively, which were 1.027 (1.021, 1.034), 1.213 (1.179, 1.248), 1.059 (1.043, 1.074), 1.016 (1.005, 1.026), and 1.024 (1.015, 1.033), respectively. Compared with the single pollutant model, the RR values of PM2.5, NO2, and O3 on the outpatient volume of respiratory diseases in the multi-pollutant model showed an upward trend, while the RR values of CO and SO2 in the multi-pollutant model showed a downward trend. Conclusion The impact of low concentrations of PM2.5, NO2, CO, and SO2 on human health cannot be ignored.
