BMC public health · 2025
Relationship between influenza-related experience and current vaccination outcome.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Gai Yunwei
Аннотация
BACKGROUND: This study investigated how a person's influenza-related experience, together with demographic, socioeconomic, and health-related factors, was associated with their current vaccination decisions.
METHODS: The 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.
RESULTS: Previous 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.
CONCLUSION: Vaccination 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.
METHODS: The 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.
RESULTS: Previous 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.
CONCLUSION: Vaccination 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.