ArticleJournal of racial and ethnic health disparities2025
Regional Disparities in the Uptake of Differentiated Influenza Vaccines in the United States.
Article in Journal of racial and ethnic health disparities, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
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Abstract
Significant racial/ethnic inequities in the uptake of differentiated influenza vaccines (DIVs) have been previously reported, though less is known about regional disparities. We conducted a retrospective longitudinal study (2014/15-2017/18 influenza seasons) among privately insured adults aged 65 + years in the US. The exposure was the beneficiary's area of residence (US Census Bureau division) and the outcome was the type of influenza vaccine: differentiated (high-dose [HDV], adjuvanted, recombinant, and cell-based) versus conventional standard-dose egg-based. Multilevel logistic regression modeling, guided by a causal diagram, was used to assess the influence of socio-demographics, medical, healthcare utilization, community, and vaccinator characteristics in confounding or mediating regional disparities. Among those vaccinated in physician offices, beneficiaries in the East North Central region were twice as likely to receive a DIV vs those in the South Atlantic, whereas those in the East and West South Central were least likely. Disparities became more pronounced in models adjusted for individual and community characteristics, suggesting that crude uptake estimates understate the true magnitude of disparities. A vaccinator's previous HDV use was most influential in explaining regional differences. Similar but less pronounced patterns emerged for vaccinations in pharmacies/facilities. Regional disparities remained even in fully adjusted models, pointing to currently poorly understood factors that may include quality of healthcare, client health literacy and engagement, and other political and cultural factors.
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