Ranking States on Coverage of Cancer-Preventing Vaccines Among Adolescents: The Influence of Imprecision

Cluster Analysis Methods to Support Population Health Improvement Among US Counties

CONTEXT

Population health rankings can be a catalyst for the improvement of health by drawing attention to areas in need of relative improvement and summarizing complex information in a manner understood by almost everyone. However, ranks also have unintended consequences, such as being interpreted as "hard truths," where variations may not be significant. There is a need to improve communication about uncertainty in ranks, with accurate interpretation. The most common solutions discussed in the literature have included modeling approaches to minimize statistical noise or borrow strength from covariates. However, the use of complex models can limit communication and implementation, especially for broad audiences.

OBJECTIVES

Explore data-informed grouping (cluster analysis) as an easier-to-understand, empirical technique to account for rank imprecision that can be effectively communicated both numerically and visually.

DESIGN

Cluster analysis, specifically k-means clustering with Wasserstein (earth mover's) distance, was explored as an approach to identify natural and meaningful groupings and gaps in the data distribution for the County Health Rankings' (CHR) health outcomes ranks.

SETTING

County-level health outcomes from the 2022 CHR.

PARTICIPANTS

3082 counties that were ranked in the 2022 CHR.

MAIN OUTCOME MEASURE

Data-informed health groups.

RESULTS

Cluster analysis identified 30 health groupings among counties nationwide, with cluster size ranging from 9 to 184 counties. On average, states had 16 identified clusters, ranging from 3 in Delaware and Hawaii to 27 in Virginia. Number of clusters per state was associated with number of counties per state and population of the state. The method helped address many of the issues that arise from providing rank estimates alone.

CONCLUSIONS

Public health practitioners can use this information to understand uncertainty in ranks, visualize distances between county ranks, have context around which counties are not meaningfully different from one another, and compare county performance to peer counties.

An Update on Human Papillomavirus Vaccination in the United States

Cervical cancer remains a significant disease in the United States. Although the human papillomavirus (HPV) vaccine has been approved for those aged 9-26 years and for some individuals up to age 45 years, there are many circumstances in which health care professionals may not know whether the vaccine should be recommended, such as for patients with previous infection, health care workers, and those older than age 26 years. This article highlights the evidence that the HPV vaccine is a safe and highly effective way to prevent cervical cancer, with the strongest predictor of vaccine uptake being practitioner recommendation.

Area-Level Variation and Human Papillomavirus Vaccination among Adolescents and Young Adults in the United States: A Systematic Review

Understanding how human papillomavirus (HPV) vaccination coverage varies by geography can help to identify areas of need for prevention and control efforts. A systematic review of the literature was conducted using a combination of keywords (HPV vaccination, geography, neighborhoods, and sociodemographic factors) on Medline and Embase databases. Studies had to provide information on HPV vaccination by area-level variables, be conducted in the United States, and be published in English (analyzing data from January 2006 to February 2020). Conference abstracts and opinion pieces were excluded. Of 733 records identified, 25 were included for systematic review. Across studies, the average initiation rate was 40.5% (range, 6.3%-78.0%). The average rate of completion was 23.4% (range, 1.7%-55.2%). Geographic regions and area-level factors were associated with HPV vaccination, including zip code tabulation area-level poverty, urbanicity/rurality, racial/ethnic composition, and health service region characteristics. Only three studies utilized geospatial approaches. None accounted for geospatial-temporal associations. Individual-level and area-level factors and their interactions are important for characterizing HPV vaccination. Results demonstrate the need to move beyond existing multilevel methods and toward the adoption of geospatial approaches that allow for the mapping and detection of geographic areas with low HPV vaccination coverage.

Human papillomavirus vaccination among diverse college students in the state of Georgia: who receives recommendation, who initiates and what are the reasons?

Young adulthood is a critical time for catch-up HPV vaccination. We assessed predictors of vaccine recommendation and initiation among college students. We analysed cross-sectional surveys from 2397 students using multivariable logistic regressions. Guided by the Socio-ecological and Health Belief Models, measures included socio-demographic characteristics, intrapersonal measures (e.g. vaccine beliefs), interpersonal measures (e.g. doctor's recommendation) and institutional-level measures (e.g. college settings). The sample included students from private, public, technical and historically black colleges/universities. Of the sample, 64.5% were White; additionally, 48.3% of women (n = 750/1552) and 18.8% of men (n = 159/845) received a doctor's recommendation. Among women, predictors included older age, US-born, higher parental education and attending private schools. Among men, predictors included younger age, being homosexual and attending private schools. HPV vaccine series initiation was low-43.3% of women (n = 672) and 16.7% of men (n = 141). Doctor's recommendation predicted initiation for both sexes. Younger women, women attending technical colleges and men of 'multiple/other' race had lower odds of initiation. Common initiation barriers for both sexes included a lack of doctor recommendation and sexual inactivity. These barriers and the associations between nativity, race and socio-economic status with vaccine recommendation and initiation should be further investigated. Interventions should improve patient-provider communication around HPV vaccine.

Adolescent Behavioral Cancer Prevention in the United States: Creating a Composite Variable and Ranking States' Performance

Preventive behaviors established during adolescence can reduce cancer throughout the life span. Understanding the combinations of multiple behaviors, and how these behaviors vary across states, is important for identifying where additional interventions are needed. Using data on 2011-2015 vaccination, energy balance, and substance use from national surveys, we created state-level composite scores for adolescent cancer prevention. Hierarchical Bayesian linear mixed models were used to predict estimates for states with no data on select behaviors. We used a Monte Carlo procedure with 100,000 simulations to generate states' ranks and 95% confidence intervals. Across states, hepatitis B vaccination was 84.3% to 97.1%, and human papillomavirus vaccination was 41.8% to 78.0% for girls and 19.0% to 59.3% for boys. For energy balance, 20.2% to 34.6% of adolescents met guidelines for physical activity, 4.1% to 15.8% for fruit and vegetable consumption, and 66.4% to 82.0% for healthy weight. For substance use, 82.5% to 93.5% reported abstaining from binge alcohol use, 84.3% to 95.4% from cigarette smoking, and 62.9% to 92.8% from marijuana use. (1) Rhode Island, (2) Colorado, (4) Hawaii and New Hampshire (tied), and (5) Vermont performed the best for adolescent cancer prevention, and (47) Missouri, (48) Arkansas, Mississippi, and South Carolina (tied), and (51) Kentucky performed the worst. However, 95% CIs around ranks often overlapped, indicating lack of statistical differences. Adolescent cancer prevention behaviors clustered into a composite index. States varied on their performance on this index, especially for states at the high and low extremes, but most states did not differ statistically. These findings can inform decision makers about where and how to intervene to improve cancer prevention among adolescents.