Effects on Flu Hospitalization, Vaccination and Chronic Conditions for Adults 65 years or older in the United States

Document Type

Poster Presentation

Publication Date

4-17-2026

Keywords

fsc2026

Abstract

Background:  Vaccination has been shown to reduce hospitalizations of infectious diseases, especially in ages 65+ years.1 However, comorbidities (e.g. hypertension, cardiovascular disease, obesity, chronic lung disease, metabolic syndrome and renal disease) may be a confounding factor.

Objective:  This study was performed to evaluate the relationship between vaccination rates and hospitalizations in patients who are 65 years and older. Also, evaluating chronic medical conditions such as hypertension, cardiovascular disease, obesity, chronic lung disease, metabolic syndrome and renal disease as confounding variables.

Methods: A retrospective analysis was conducted using patients who were diagnosed with influenza, hospitalized, who are 65+, that have reported data to The Influenza Hospitalization Surveillance Network [ (FluSurv-NET). This network conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations. The network currently covers over 90 counties or county equivalents in 14 states (CA, CO, CT, GA, MD, MI, MN, NC, NM, NY, OR, TN, UT, and WA)].2 Vaccination records were collected from these 14 states, using FluVaxView from the CDC.3 Pearson correlation analysis was performed to see if there is a correlation between vaccination rates and hospitalization rates who are 65 years and older. n = influenza season year. Multiple linear regression analyses were used to analyze the effect of comorbid conditions on the relationship between the 2 variables.

Results: No statistically significant association between hospitalization rates and vaccination rates, (p = 0.72, R² = 0.01). Also, none of the confounding variables were statistically significant with hospitalization rates; obesity (p = 0.233), cardiovascular disease (p = 0.629), chronic lung disease (p = 0.361), metabolic syndrome (p = 0.362), and renal disease (p = 0.826). Across all conditions, the R²  was small, meaning there is a weak correlation.

Conclusion: In this study, there was no statistical significance between all variables analyzed. These findings may be limited to this dataset. However, due to the limited number of states reporting to the CDC about flu stats, it is possible that an entire analysis of all 50 states should be explored. The sample size was small (n ≈ 11-14), which may be the reason why there was no statistical significance between all the variables analyzed.

Comments

Poster presented at the 2026 Fisher Showcase, St. John Fisher University, April 17, 2026.

This document is currently not available here.

Additional Files

Share

COinS