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Annual Wellness Visits and Influenza Vaccinations among Older Adults in the US.


ABSTRACT: OBJECTIVES:Investigate whether combinations of sociodemographic factors, chronic conditions, and other health indicators pose barriers for older adults to access Annual Wellness Visits (AWVs) and influenza vaccinations. METHODS:Data on 4999 individuals aged ?65?years from the 2012 wave of the Health and Retirement Study linked with Medicare claims were analyzed. Conditional Inference Tree (CIT) and Random Forest (CIRF) analyses identified the most important predictors of AWVs and influenza vaccinations. Multivariable logistic regression (MLR) was used to quantify the associations. RESULTS:Two-year uptake was 22.8% for AWVs and 65.9% for influenza vaccinations. For AWVs, geographical region and wealth emerged as the most important predictors. For influenza vaccinations, number of somatic conditions, race/ethnicity, education, and wealth were the most important predictors. CONCLUSIONS:The importance of geographic region for AWV utilization suggests that this service was unequally adopted. Non-Hispanic black participants and/or those with functional limitations were less likely to receive influenza vaccination.

SUBMITTER: Jorgensen TSH 

PROVIDER: S-EPMC7536477 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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Annual Wellness Visits and Influenza Vaccinations among Older Adults in the US.

Jørgensen Terese Sara Høj TSH   Allore Heather H   Elman Miriam R MR   Nagel Corey C   Zhang Mengran M   Markwardt Sheila S   Quiñones Ana R AR  

Journal of primary care & community health 20200101


<h4>Objectives</h4>Investigate whether combinations of sociodemographic factors, chronic conditions, and other health indicators pose barriers for older adults to access Annual Wellness Visits (AWVs) and influenza vaccinations.<h4>Methods</h4>Data on 4999 individuals aged ≥65 years from the 2012 wave of the Health and Retirement Study linked with Medicare claims were analyzed. Conditional Inference Tree (CIT) and Random Forest (CIRF) analyses identified the most important predictors of AWVs and  ...[more]

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2022-02-16 | GSE196793 | GEO