197
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

COVID-19 vaccine uptake and hesitancy in Chinese patients with asthma

, MD, PhD, , MMORCID Icon, , MBBS, , MD, , MD, , MDORCID Icon, , MD, PhD, , MD, , MBBS, , MBBS, , MBBS, , MBBS, , MD, , MD, , MD, , MD, PhD & , MD, PhD show all
Pages 2111-2120 | Received 01 Apr 2023, Accepted 27 May 2023, Published online: 09 Jun 2023
 

Abstract

Objective

Both patients and physicians may be hesitant toward vaccination in patients with asthma, which may result in lower vaccine uptake. The aim of this work was to investigate the vaccination rate, the adverse reactions, as well as the factors associated with vaccine acceptance and hesitancy toward COVID-19 vaccination among asthmatic patients in Beijing.

Methods

A multi-center, cross-sectional face-to-face survey was conducted in patients with asthma consecutively recruited from December 2021 to April 2022. The survey included asthma status, COVID-19 vaccine uptake and adverse reactions, and knowledge of and attitude toward COVID-19 vaccination.

Results

A total of 261 patients were enrolled. The rate of COVID-19 vaccination during the study period was 73.6%, as compared to 87.64% in the general population in China. Patients who were currently working, had received other vaccines in the past, and had had no adverse reactions to other vaccines, showed a higher rate of COVID-19 vaccination. Patients believing that the vaccination of family members and colleagues had a positive impact on their decision to get vaccinated, were more likely to get the COVID-19 vaccines. The COVID-19 vaccination rate was lower in those with poorly monitored asthma and those using biologic therapies. The adverse effects of COVID-19 vaccines in asthmatic patients were similar to those in the general population.

Conclusion

The COVID-19 vaccination rate in asthmatic patients was lower than the general population in China. Active measures should be taken to control asthma and increase vaccination rates in these patients.

Author contributions

Chun Chang: Conceptualization, design of questionnaire, acquisition, analysis and interpretation of data, Writing – Original Draft, Funding acquisition.

Xiaoqin Zhang: analysis and interpretation of data, Writing – Original Draft.

Yu Feng: acquisition, analysis and interpretation of data.

Rong Jin: Conceptualization, Writing – Reviewing.

Lina Sun: acquisition of data.

Ying Liang: acquisition of data.

Yahong Chen: acquisition of data.

Xiaofang Liu: acquisition of data.

Yanliang Ma: acquisition of data.

Jie Song: acquisition of data.

Pingchao Xiang: acquisition of data.

Erming Zhang: acquisition of data.

Liang Chen: acquisition of data.

Yanwen Jiang: acquisition of data.

Kewu Huang: acquisition of data.

Wen Wang: acquisition of data.

Sun Yongchang: Conceptualization, Writing – Reviewing and Editing.

Data sharing statement

The data that supports the findings of this study will not be shared openly with other third parties due to contractual statements related to intellectual property, confidentiality, and proprietary rights.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethics approval

The study protocol was approved by the Independent Ethics Committee of the Peking University Third Hospital (IRB00006761-M2022186) which was the primary research institution of the present study.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [No. 81970028][No. 82170028][No.82100031].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,078.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.