| Literature DB >> 35530953 |
Wei Han1, Yi Su1, Binglin Liu2, Wenjing Zhu3, Xinjuan Yu3, Xiaohui Sun4, Xuefei Qi1, Xiaopei Lin5, Syed A A Rizvi6, Woo-Jung Song7, Ji-Hyang Lee7, Yasuo Shimizu8, Ziguang Li5, Qinghai Li1.
Abstract
Background: The hospitalization for asthma exacerbation has varied with seasons, however, the underlying weather reasons have not been fully explored yet. This study is aimed to explore the effect of weather factors on increased number of hospitalization due to worsening of asthma symptoms. This will provide more information to the relevant authorities to allocate appropriate medical resources as per the weather conditions in Qingdao, China.Entities:
Keywords: Asthma exacerbation; climate change; pollution; weather condition
Year: 2022 PMID: 35530953 PMCID: PMC9073776 DOI: 10.21037/atm-22-1755
Source DB: PubMed Journal: Ann Transl Med ISSN: 2305-5839
Figure 1Geographical distribution of 13 hospitals (branches) and air pollutant stations in this study. Blue triangles stand for air pollution monitoring station, red triangles stand for hospitals (branches).
Patients hospitalized for asthma exacerbation in 13 hospitals of Qingdao from 2017 to 2019 (n)
| Year | Afflicted Hospital of Qingdao University | Qilu Hospital of Shandong University | Qingdao Municipal Hospital | Qingdao Center Hospital | Qingdao No. 8 People’s Hospital | Qingdao No. 3 People’s Hospital | Jimo People’s Hospital | Laixi People’s Hospital | Jiaozhou People’s Hospital | Jiaozhou Center Hospital | Pingdu People’s Hospital | Huangdao People’s Hospital | Huangdao Center Hospital | All |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017 | 214 | 151 | 775 | 193 | 368 | 281 | 185 | 118 | 147 | 253 | 242 | 385 | 213 | 3,525 |
| 2018 | 221 | 155 | 811 | 178 | 300 | 320 | 163 | 98 | 209 | 187 | 265 | 371 | 175 | 3,453 |
| 2019 | 245 | 141 | 902 | 236 | 265 | 264 | 225 | 109 | 163 | 187 | 320 | 382 | 132 | 3,571 |
| All | 680 | 447 | 2,488 | 607 | 933 | 865 | 573 | 325 | 519 | 627 | 827 | 1,138 | 520 | 10,549 |
Figure 2Interannual variability of hospitalization for asthma exacerbation.
Figure 3The time series of observed monthly concentrations of the (A) AQI, (B) PM2.5 and (C) PM10 from January 2017 to December 2019 in Qingdao. AQI, air quality index; PM, particulate matter.
Figure 4The climatology of the 850 hPa horizontal wind for the (A) winter and (B) spring during the period of 1960–2020. Vectors denote the horizontal winds (arrow) with wind speed (shading). Units for the horizontal winds are m/s.
Figure 5The climatology of the vertical velocity at 500 hPa for the (A) winter and (B) spring during the period of 1960–2020. Positive (negative) values denote downward (upward) motion. Units for the vertical velocity are Pa/s.
Figure 6The anomalous 850 hPa horizontal winds for the (A) 2018 winter and (B) 2019 spring. Vectors denote the anomalous winds (arrow) and wind speed (shading). White dots show where the wind speed anomalies are significant over 95% confidence level. Units for the horizontal winds are m/s.
Figure 7The anomalous vertical velocity at 500 hPa for the (A) 2018 winter and (B) 2019 spring. Positive (negative) values denote downward (upward) motion anomalies. Black dots show where the vertical velocity anomalies are significant over 95% confidence level. Units for the vertical velocity are Pa/s.
Figure 8The relationship between asthma inpatients and air quality. VV, vertical visibility.