Evidence map›Paper›PMID 34172461›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2021

Identifying Area-Level Disparities in Human Papillomavirus Vaccination Coverage Using Geospatial Analysis.

David C Wheeler, Carrie A Miller, Elizabeth K Do, Albert J Ksinan, Justin G Trogdon, Askar Chukmaitov, Bernard F Fuemmeler

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

7 authors.

David C WheelerDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Virginia. dcwheeler@vcu.edu.
Carrie A MillerDepartment of Health Behavior and Policy, Virginia Commonwealth University, Richmond, Virginia.ORCID 0000-0002-8136-7618
Elizabeth K DoDepartment of Health Behavior and Policy, Virginia Commonwealth University, Richmond, Virginia.
Albert J KsinanDepartment of Health Behavior and Policy, Virginia Commonwealth University, Richmond, Virginia.ORCID 0000-0003-3900-5098
Justin G TrogdonDepartment of Health Policy and Management, Gillings School of Global Public Health, Chapel Hill, North Carolina.ORCID 0000-0001-5484-7870
Askar ChukmaitovDepartment of Health Behavior and Policy, Virginia Commonwealth University, Richmond, Virginia.
Bernard F FuemmelerMassey Cancer Center, Virginia Commonwealth University, Richmond, Virginia.

Funding

Virus Vector Shared ResourceP30CA016059 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI Kim Felder Rhoads · 1985 to 2026
$51.0M
Training Program in Cancer Prevention and Control and Cancer Health Equity (CPC-CHE)T32CA093423 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI Bernard F Fuemmeler, Oxana G Palesh · 2018 to 2026
$3.0M
NCI NIH HHS P30 CA016059NCI NIH HHS T32 CA093423
6 · The paper itself

Abstract

backgroundHuman papillomavirus (HPV) is the most common sexually transmitted infection within the United States (US). Despite clinical agreement on the effectiveness and widespread availability of the prophylactic HPV vaccine, vaccination coverage in the US is suboptimal and varies by geographic region and area-level variables. The goals of this article were to model the variation in vaccination rates among boys and girls within ZIP Codes in Virginia, determine whether neighborhood sociodemographic variables explain variation in HPV vaccination, and identify areas with significantly depressed vaccination coverage.

methodsWe used Bayesian hierarchical spatial regression models with statewide immunization registry data to consider the correlation in vaccination among boys and girls, as well as the spatial correlation in vaccination for each sex.

resultsThe results showed low vaccination coverage in our birth cohort (28.9% in girls and 23.8% in boys) relative to the national level (56.8% and 51.8%, respectively). Several area-level variables were significantly and positively associated with vaccination coverage, including population density, percentage of Hispanic population, and average number of vehicles. In addition, there were several areas of significantly lowered vaccination coverage, including predominantly rural ones, and overall large geographic disparities in HPV vaccination.

conclusionsDetermining the geospatial patterning and area-level factors associated with HPV vaccination within a prescribed geographic area helps to inform future planning efforts. IMPACT: The results of this study will help inform future planning efforts for geographically targeted interventions and policies, as well as drive new research to implement clinical and community strategies to increase HPV vaccination.

Indexed as

AdolescentAlphapapillomavirusBayes TheoremChildFemaleHealthcare DisparitiesHumansMalePapillomavirus InfectionsPapillomavirus VaccinesRetrospective StudiesSpatial AnalysisVaccination CoverageVirginiaPapillomavirus Vaccines

Identifiers

PMID34172461
PMCPMC8419078

What OpenQuestion holds

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Registered trials

None linked

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.