Evidence map›Paper›PMID 39819429›Full record

ArticleBMC public health2025

Relationship between influenza-related experience and current vaccination outcome.

Yunwei Gai

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Yunwei GaiEconomics Division, Babson College, 231 Forest Street, Wellesley, MA, United States. ygai@babson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study investigated how a person's influenza-related experience, together with demographic, socioeconomic, and health-related factors, was associated with their current vaccination decisions.

methodsThe analysis used ten panels of the Medical Expenditure Panel Survey (MEPS) from 2006 to 2016. Linear and logistic probability models were estimated to predict influenza vaccination using a person's vaccination status in the previous year and history of influenza infection, adjusting for demographics, socioeconomic variables, general health status, and healthcare access. The models used two-way and three-way interactions with race/ethnicity, income, education, health status, and elderly status to examine changing relationships of flu-related experience across these variables.

resultsPrevious vaccination was the most important predictor, with an increase of 63.0-71.8% probability of vaccination in the next year. Infection history could either increase or decrease the impact of past vaccination depending on race/ethnicity, income, education level, health status, and age. There were significant disparities across demographic, socioeconomic, and health-related variables.

conclusionVaccination promotion efforts could focus on those who have not been vaccinated in the past and on specific sub-populations, such as people who are Hispanic, people with lower education levels, the population aged 65 and above, and families with low-income levels. Although past infection is a predictor for some population groups, its magnitude is small and is often not a significant determinant.

Indexed as

Influenza, HumanInfluenza VaccinesVaccinationAdolescentAdultAgedFemaleHumansMaleMiddle AgedSocioeconomic FactorsUnited StatesYoung AdultInfluenza VaccinesHealth care disparityInfluenza infectionInfluenza vaccinationMedical expenditure panel survey

Identifiers

PMID39819429
PMCPMC11736949

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.