| Autor: |
Ty J. Skyles, Harlan P. Stevens, Spencer C. Davis, Acelan M. Obray, Dashiell S. Miner, Matthew J. East, Tyler Davis, Haley Hoelzer, Stephen R. Piccolo, Jamie L. Jensen, Brian D. Poole |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Vaccines, Vol 12, Iss 10, p 1164 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2076-393X |
| DOI: |
10.3390/vaccines12101164 |
| Popis: |
Background: Seasonal influenza vaccination rates are very low among teenagers. Objectives: We used publicly available data from the NIS-Teen annual national immunization survey to explore factors that influence the likelihood of a teen receiving their seasonal flu shot. Methods: Traditional stepwise multivariable regression was used in tandem with machine learning to determine the predictive factors in teen vaccine uptake. Results and Conclusions: Age was the largest predictor, with older teens being much less likely to be vaccinated than younger teens (97.48% compared to 41.71%, p < 0.0001). Provider participation in government programs such as Vaccines for Children and the state vaccine registry positively impacts vaccine uptake (p < 0.0001). Identifying as non-Hispanic Black was a small, negative predictor of teen vaccine uptake (78.18% unvaccinated compared to 73.78% of White teens, p < 0.0001). The state quartile for COVID-19 vaccine uptake also strongly predicted flu vaccine uptake, with the upper quartile of state COVID-19 vaccine uptake being significantly more likely to also get vaccinated for influenza (76.96%, 74.94%, 74.55%, and 72.97%, p < 0.0001). Other significant factors are the number of providers, education of the mother, poverty status, and having a mixed provider facility type. Additionally, the multivariable regression analysis revealed little difference in the predictive factors of vaccine uptake between pre- and post-pandemic datasets. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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