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Predicting future vaccination habits: The link between influenza vaccination patterns and future vaccination decisions among old aged adults in China

Authors :
Yang Shen
Jingyu Wang
Quiping zhao
Min Lv
Jiang Wu
Stephen Nicholas
Elizabeth Maitland
Ping He
Dawei Zhu
Source :
Journal of Infection and Public Health, Vol 17, Iss 6, Pp 1079-1085 (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Background: Annual influenza vaccination is crucially recommended for the elderly to maintain humoral immunity. Insufficient coverage requires us to understand the determinants of their influenza behaviors and how these patterns impact vaccination choices. Methods: Data from 540 Beijing residents aged over 65 were collected through interviews, capturing vaccination history and sociodemographic details. Individual influenza vaccination records from 2016 to 2020 were obtained from China’s Immunization Information Systems. A latent class model identified three vaccination patterns. Multinomial logistic regression assessed relative risk ratios (RRRs) for vaccination based on sociodemographic factors. Vaccination patterns were used to predict future vaccination likelihood. Results: The analysis revealed three groups: sporadically vaccinated (63.33%), occasionally vaccinated (18.71%), and frequently vaccinated (17.96%). Factors associated with frequent vaccination included age over 70 (RRR = 2.81), lower income (RRR = 0.39), higher vaccine hesitancy (RRR = 3.10), multiple chronic conditions (RRR = 2.72), and rural residence (RRR = 2.48). The frequently vaccinated group was more likely to sustain regular vaccination habits in subsequent years compared to the occasionally vaccinated group. Conclusions: Only 17.96% of Beijing’s older population exhibited a consistent influenza vaccination pattern. Older age, rural residency, and chronic diseases correlated with repeated influenza vaccination. Segmenting the population based on past vaccination behavior can aid in designing targeted interventions to improve vaccination rates.

Details

Language :
English
ISSN :
18760341
Volume :
17
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Journal of Infection and Public Health
Publication Type :
Academic Journal
Accession number :
edsdoj.fb000d30e5e4eaba815366a0510a46d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jiph.2024.04.017