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Autor(en) / Beteiligte
Titel
Patterns and Disparities in Human Papillomavirus (HPV) Vaccine Uptake for Young Female Adolescents among U.S. States: NIS-Teen (2008-2016)
Ist Teil von
  • Cancer epidemiology, biomarkers & prevention, 2020-07, Vol.29 (7), p.1458-1467
Ort / Verlag
United States
Erscheinungsjahr
2020
Link zum Volltext
Quelle
Electronic Journals Library
Beschreibungen/Notizen
  • Several studies have reported differential vaccine uptake outcomes that are associated with sociodemographic and socioeconomic characteristics, as well as provider type. However, none has examined a trend over a multiple-year span. In this study, we utilize a longitudinal data-based approach to examine state-level human papillomavirus (HPV) vaccine trends and their influences over time. We analyzed National Immunization Survey - Teen data (2008-2016) to estimate HPV vaccine initiation rate in young female adolescent ages 13-17 years old among U.S. States. We identified growth patterns using the latent class growth method and explored state-level characteristics, including socioeconomic and sociodemographic attributes, and health legislation and policy-related programs among patterns. We identified three growth patterns, which showed gradually increasing vaccination trends but different baseline HPV uptake rates (high, moderate, low). States within Pattern 1 (highest HPV vaccination rates) included the lowest percentage of families with incomes below federal poverty level, the highest percentage of bachelor's degree or higher, and the lowest number of uninsured, while states within Pattern 3 (lowest HPV vaccination rates) included families with socioeconomic attributes along the opposite end of the spectrum. Latent class growth models are an effective tool to be able to capture health disparities in heterogeneity among states in relation to HPV vaccine uptake trajectories. These findings might lead to designing and implementing effective interventions and changes in policies and health care coverage to promote HPV vaccination uptake for states represented under the lowest trajectory pattern.
Sprache
Englisch
Identifikatoren
ISSN: 1055-9965
eISSN: 1538-7755
DOI: 10.1158/1055-9965.EPI-19-1103
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7415186
Format

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