Sauver, Jennifer L. St.

Background: In 2012, updated cervical cancer screening recommendations were released with consensus on Papanicolaou (Pap) testing every 3 years for women age 21–65 years or Pap–human papillomavirus (HPV) cotesting at 5-year intervals for women age 30–65 years. Primary study aims: Assess current use of Pap-HPV cotesting and describe local population trends over time in Pap and Pap-HPV cotesting. Secondary aim: Assess sociodemographic factors correlating with screening. Methods: We assessed Rochester Epidemiology Project data for Pap and Pap-HPV cotesting among women age 16 years and older living in Olmsted County, Minnesota, yearly from 2005 (study population n = 47,203) through 2016 (study population n = 49,510). We calculated 3-year (Pap) and 5-year (Pap-HPV) moving prevalence rates of screening as proportion of eligible population. Multivariable logistic regression was used to assess factors potentially associated with screening. Results: In 2016, 64.6% of 27,418 eligible 30- to 65-year-old women were up to date with cervical cancer screening; 60.8% had received Pap-HPV cotest screening. Significant declines in Pap completion rates over time were observed in all age groups, including an unexpected decline in 21- to 29-year-old women. Coincident with decreasing Pap screening rates, Pap-HPV cotesting significantly increased among women age 30–65 years, from 10.0% in 2007 to 60.8% in 2016. Conclusions: This suggests increasing adoption of 2012 screening recommendations in the 30- to 65-year-old population. However, decline in Pap screening among 21- to 29-year-old women is concerning. Disparities by race, ethnicity, smoking status, and comorbidity level were observed. Results suggest need for multilevel patient and clinician interventions to increase cervical cancer screening adherence.

Background: Health and Wellness Coaching has been shown to enhance treatment outcomes in the primary care setting. However, little is known about the experience and perceptions of patients who worked with a wellness coach as an integrated member of their primary health-care team. Objective: This project assessed patients’ experience and obtained their perceptions on barriers and facilitators to participation in a primary care–based wellness coaching program. Method: A survey was mailed to 99 primary care patients with prediabetes who participated in a 12-week wellness coaching program. Results: Sixty-two (63%) completed the survey; responders felt that participation in the wellness coaching program helped move them toward healthier lifestyle behavior and created a personal vision of wellness. Major themes associated with participation were supportive coaching relationship, increased self-accountability, increased goal-setting, and healthy behavior strategies. No significant barrier to participation was reported. Conclusion: Participants reported highly positive experience with the program; how to best integrate health and wellness coaching into the primary care setting needs to be explored.

The prevalence of childhood obesity has increased over the past 3 decades. This study was designed to understand how childhood body mass index (BMI) influences later risk of obesity. We calculated BMIs for children residing in Olmsted County, Minnesota, between January 1, 2005 and December 31, 2012 using medical records data. We defined homogenous BMI trajectory clusters using a nonparametric hill-climbing algorithm. Overall, 16,538 (47%) children had >3 weight assessments at least 1 year apart and were included in the analyses. Within the 8-year follow-up period, children who were younger than 2 years and overweight had a 3- fold increase of obesity (adjusted hazard ratio [HR] = 3.24; 95% confidence interval [CI] = 2.69-3.89) and those aged 5 years and overweight had a 10-fold increased risk of obesity (adjusted HR = 9.97, 95% CI = 8.55-11.62). Three distinct BMI trajectories could be distinguished prior to 5 years of age. The risk of developing obesity in those who are overweight increased dramatically with increasing age. Interventions to prevent obesity need to occur prior to school age to prevent children from entering unhealthy BMI trajectories.

Advances in pharmacogenomics (PGx) have the potential to transform healthcare by allowing precision medicine to become a reality. However, PGx knowledge is new, complex, and evolving, and relying on the cognition of clinicians alone is insufficient for clinical implementation. Integrating clinical decision support (CDS) tools in the electronic health record (EHR) is critical for translating PGx into clinical practice. Herein, we review current strategies to implement PGx using EHR‐CDS functionalities.

137 Background: LUTS are one of the most common reasons patients visit urologists. These symptoms have not been typically associated with the development of prostate cancer (CaP). However, we hypothesized that visiting a physician for LUTS may modify the diagnostic intensity for CaP compared to population controls. Methods: We examined data from a longitudinal, population-based cohort of 2,447 men between 40 and 79 years old who were followed prospectively from 1990 to 2010. Participants completed the American Urological Association Symptom Index (AUASI) every two years. Self-reported moderate/severe LUTS were defined as an AUASI score >7 (n=1627). Data including the treatment for LUTS (n=874), prostate biopsy (PBx), family history of CaP and diagnosis of CaP were obtained through self-report and review of medical records. Associations between self-reported LUTS, treatment for LUTS, and risk of PBx or CaP were estimated using multivariate Cox proportional hazard models. Results: An interaction was noted between age and LUTS and PBx and CaP diagnosis. In younger men, the diagnosis and treatment of LUTS was associated with increased risk of PBx (HR 2.39: 95% CI 1.83, 3.13) and CaP (HR 3.47: 95% CI 2.38, 5.07). Conversely in older men, treatment for LUTS was associated with a decreased risk of PBx and CaP (Table). Self reported LUTS was not significantly associated with CaP diagnosis in younger men and was protective in older men (Table). Conclusions: There is a differential effect of LUTS on prostate cancer testing and diagnosis when stratified by age. The reason for this difference is unclear, but appears to be due largely to diagnostic intensity rather than a true biologic association between LUTS and CaP. [Table: see text]

Abstract Background: Human papillomavirus (HPV) vaccination rates in the United States remain low and lag behind other recommended adolescent vaccines. Studies evaluating the association of geographic and area-level characteristics with HPV vaccination rates provide a valuable resource for public health planning. Method: We used the Rochester Epidemiology Project data linkage system to ascertain HPV vaccination rates between 2010 and 2015 in a 7-county region of southern Minnesota. Geocoded individual patient data were spatially linked to socioeconomic data from the American Community Survey at the census block group level. Bayesian hierarchical logistic regression was used to model incident vaccination rates, adjusting for individual- and area-level sociodemographic characteristics, and geolocation. Geolocation was modeled as an approximated Gaussian field using a Stochastic Partial Differential Equations approach. All models were estimated using Integrated Nested Laplace Approximations. Results: In adjusted models, increasing age and female sex were associated with increased HPV vaccination. Lower socioeconomic status was associated with decreased rates of initiation [adjusted odds ratio (AOR); 95% confidence interval = 0.90 (0.86–0.95)], completion of the second dose [AOR = 0.88 (0.83–0.93)], and completion of the third dose [AOR = 0.85 (0.80–0.92)]. Geographic spatial analysis demonstrated increased odds of vaccination for the eastern region and in the greater Rochester metropolitan area, showing significant spatial variation not explained by individual level characteristics and ACS block group-level data. Conclusions: HPV vaccination rates varied geographically and by individual and geographically indexed sociodemographic characteristics. Impact: Identifying geographic regions with low HPV vaccination rates can help target clinical and community efforts to improve vaccination rates. Cancer Epidemiol Biomarkers Prev; 26(4); 533–40. ©2017 AACR. See all the articles in this CEBP Focus section, “Geospatial Approaches to Cancer Control and Population Sciences.”