Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China. Issue 10 (7th October 2020)

• Record Type: Journal Article
• Authors: Ma, Rui; Liang, Lizhong; Kong, Yunfeng; Chen, Mingyang; Zhai, Shiyan; Song, Hongquan; Hou, Yane; Zhang, Guangli
• Is Part Of: BMJ open. Volume 10:Issue 10(2020)
• Publication Date: 2020-10-07
• Subjects: asthma -- public health -- statistics & research methods; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2020-038117
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objective: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. Setting: Guangxi, China. Participants: This study was done among 7804 asthma patients. Primary and secondary outcome measures: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. Results: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m 3 increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO2 ) and particulate matter (PM2.5 ) in multiple regions. According to the result of GAM, the adjusted R 2 was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. Conclusion: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO2, SO2 or PM2.5 in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.