Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

<p>OBJECTIVES/GOALS: - Illustrate findings of a translational science case study of multi-pronged research aimed at understanding of social determinants in health disparities and integrating patient-centered technology; - Illuminate translational mechanisms by analyzing and sharing research challenges, facilitators, and benefits. METHODS/STUDY POPULATION: Utilized novel TS evaluation methods and tools: - Translational Science Case Study protocol to examine translational path from innovation to practice, barriers and facilitators for that translational movement. - Translational Science Benefits Model (TSBM) Checklist for translational/research impact analysis. Triangulated diverse data sources: - Primary data: semi-structured interviews with research partners. - Secondary data: researchers’ grant applications, reports, and publications; public stories/news related to their research; scientific publications; organizational/policy documents; and interviews with research stakeholders featured in published sources. RESULTS/ANTICIPATED RESULTS: Translational challenges include: culturally tailored education and outreach; data analysis and intervention planning; engaging community stakeholders in the development and implementation; addressing economic and resource-related challenges. Translational facilitators are: UMN CTSA funding and other support; access to data and resources; use of open-source materials; evidence-based/best practice approaches; diversity and collaboration between researchers, community organizations, healthcare providers; researchers’ drive to translate. The research contributes to community and public health, clinical/medical, and economic benefits, health equity advocacy, catalyzing further research, and public awareness. DISCUSSION/SIGNIFICANCE: The evaluation case study contributes to translational science by providing evidence and lessons learned related to translational benefits, challenges, and facilitators of community-based, patient-centered research bringing people, knowledge, and technology together and contributing to health equity.</p>

Background: Air pollution is positively associated with some childhood cancers while greenness is inversely

<p>Background: Air pollution has been reported to be associated with some childhood cancers, namely leukemias. Less is known about air pollution and childhood brain tumor risk. In adult cancers, increasing vegetation density, or greenness, has been inversely associated with cancer incidence and survival. The interplay between air pollution and greenness, which co-occur, in childhood cancer etiology is unclear. Therefore, we sought to estimate the association between prenatal and early life exposure to air pollution, greenness, and childhood cancer in Texas (1995-2011). Materials and Methods: We included 1,316 individuals with a childhood brain tumor diagnosed &amp;lt;17 years of age and 109,762 age- and sex-matched controls. We linked birth certificate residential address to census tract annual average particulate matter 2.5 µg/m³ (PM2.5) and Normalized Difference Vegetation Index (NDVI) to approximate prenatal and early life exposure to greenness and air pollution. We estimated odds ratios (OR) and 95% confidence intervals (95% CI) as the measure of association between PM2.5 and NDVI interquartile range (IQR) increases and brain tumors. Models were adjusted for birth year, sex, maternal race/ethnicity, and area-level socioeconomic status (Yost index). Results: The following brain tumor types were included: ependymoma (n=136), astrocytoma (n=619), medulloblastoma (n=187), PNET (n=57), ATRT (n=54), and other gliomas (n=263). Average birth year PM2.5 and NDVI exposure levels were similar in cases and controls, 11 µg/m³ and 0.4, respectively. Each IQR increase (2.6 µg/m³) in PM2.5 was associated with ependymoma (OR: 1.27, 95% CI: 1.01-1.60) when adjusting for control-derived quartiles of NDVI. Conversely, after adjusting for PM2.5 quartiles, each IQR increase in NDVI (0.13) was inversely associated with ependymoma in those diagnosed at 0-4 years of age (OR: 0.75, 95% CI: 0.56-0.97) and with medulloblastoma in those aged 0-16 years at diagnosis (OR: 0.75, 95% CI: 0.62-0.91). There was no evidence of statistical interaction between NDVI and PM2.5 (all Likelihood Ratio Test p-values&amp;gt;0.05) for any brain tumors. Conclusions: Increasing residential air pollution during prenatal and early life increased the risk of childhood ependymoma in Texas independent of greenness. Conversely, increasing greenness exposure in prenatal and early life decreased the risk of ependymoma and medulloblastoma independent of PM2.5. These findings highlight the complex relationship between air pollution and greenness in childhood cancer etiology.</p>

Interventions to address social drivers of health (SDH), such as food insecurity, transportation, and housing, can reduce future health care costs but require up-front investment. Although Medicaid...

<h3>Importance</h3><p>Nearly half of the 14.8 million US adults eligible for lung cancer screening (LCS) smoke cigarettes. The optimal smoking cessation program components for the LCS setting are unclear.</p><h3>Objective</h3><p>To assess the effect of adding a referral to prescription medication therapy management (MTM) to the tobacco longitudinal care (TLC) program among patients eligible for LCS who smoke and do not respond to early tobacco treatment and to assess the effect of decreasing the intensity of TLC among participants who do respond to early treatment.</p><h3>Design, Setting, and Participants</h3><p>This randomized clinical trial included patients who currently smoked cigarettes daily and were eligible for LCS. Recruitment took place at primary care centers and LCS programs at 3 large health systems in the US and began in October 2016, and 18-month follow-up was completed April 2021.</p><h3>Interventions</h3><p>(1) TLC comprising intensive telephone coaching and combination nicotine replacement therapy for 1 year with at least monthly contact; (2) TLC with MTM, MTM offered pharmacist-referral for prescription medications; and (3) Quarterly TLC, intensity of TLC was decreased to quarterly contact. Intervention assignments were based on early response to tobacco treatment (abstinence) that was assessed either 4 weeks or 8 weeks after treatment initiation.</p><h3>Main outcomes and Measures</h3><p>Self-reported, 6-month prolonged abstinence at 18-month.</p><h3>Results</h3><p>Of 636 participants, 228 (35.9%) were female, 564 (89.4%) were White individuals, and the median (IQR) age was 64.3 (59.6-68.8) years. Four weeks or 8 weeks after treatment initiation, 510 participants (80.2%) continued to smoke (ie, early treatment nonresponders) and 126 participants (19.8%) had quit (ie, early treatment responders). The 18 month follow-up survey response rate was 83.2% (529 of 636). Across TLC groups at 18 months follow-up, the overall 6-month prolonged abstinence rate was 24.4% (129 of 529). Among the 416 early treatment nonresponders, 6-month prolonged abstinence for TLC with MTM vs TLC was 17.8% vs 16.4% (adjusted odds ratio [aOR] 1.13; 95% CI, 0.67-1.89). In TLC with MTM, 98 of 254 participants (39%) completed at least 1 MTM visit. Among 113 early treatment responders, 6-month prolonged abstinence for Quarterly TLC vs TLC was 24 of 55 (43.6%) vs 34 of 58 (58.6%) (aOR, 0.54; 95% CI, 0.25-1.17).</p><h3>Conclusions and Relevance</h3><p>In this randomized clinical trial, adding referral to MTM with TLC for participants who did not respond to early treatment did not improve smoking abstinence. Stepping down to Quarterly TLC among early treatment responders is not recommended. Integrating longitudinal tobacco cessation care with LCS is feasible and associated with clinically meaningful quit rates.</p><h3>Trial Registration</h3><p>ClinicalTrials.gov Identifier:NCT02597491</p>

Shapefile 1) National LCS Estimates for current smokers, former smokers, current & former smokers 2) National LCS Estimates current & former smokers all categories CSV 1) National_LCS_estimates_current_former_total.csv 2) National_LCS_estimates_all_categories.csv

The mission of the National Breast and Cervical Cancer Early Detection Program's (NBCCEDP) mission is to improve access to mammography and other health services for underserved women. Since its inception in 1991, this national program has improved breast cancer screening rates for women who are uninsured and underinsured. However, the literature has shown that NBCCEDP screenings are decreasing, and only reach a portion of eligible women. Reliable estimates at the sub-county level are needed to identify and reach eligible women. Our work builds upon previous estimates by integrating uninsured and insurance status into spatially adaptive lters. We use spatially adaptive lters to create small area estimates of standardized incidence ratios describing the utilization rate of NBCCEDP services in Minnesota. We integrate the American Community Survey (2010-2014) insurance status data to account for the percentage that an individual is uninsured. We test ve models that integrate insurance status by age, sex, and race/ethnicity. Our composite model, which adjusts for age, sex, and race/ethnicity insurance statuses, reduces 95% of the estimation error. We estimate that there approximately 49,913.7 women eligible to receive services for Minnesota. We also create small geography (i.e., county and sub-county) estimates for Minnesota. The integration of the insurance data improved our utilization estimate. The development of these methods will allow state programs to more eciently use their resources and understand their reach.

Neighborhood deprivation indices are widely used in research, but the performance of these indices has rarely been directly compared in the same analysis. We examined the Area Deprivation Index, Neighborhood Deprivation Index, and Yost index, and compared their associations with breast cancer mortality. Indices were constructed for Georgia census block groups using 2011–2015 American Community Survey data. Pearson correlation coefficients and percent agreement were calculated. Associations between each index and breast cancer mortality were estimated among 36,795 women diagnosed with breast cancer using Cox proportional hazards regression. The indices were strongly correlated (absolute value of correlation coefficients &gt; 0.77), exhibited moderate (41.4%) agreement, and were similarly associated with a 36% increase in breast cancer mortality. The similar associations with breast cancer mortality suggest the indices measure the same underlying construct, despite only moderate agreement. By understanding their correlations, agreement, and associations with health outcomes, researchers can choose the most appropriate index for analysis.

Choropleth mapping continues to be a dominant mapping technique despite suffering from the Modifiable Areal Unit Problem (MAUP), which may distort disease risk patterns when different administrative units are used. Spatially adaptive filters (SAF) are one mapping technique that can address the MAUP, but the limitations and accuracy of spatially adaptive filters are not well tested. Our work examines these limitations by using varying levels of data aggregation using a case study of geocoded breast cancer screening data and a synthetic georeferenced population dataset that allows us to calculate SAFs at the individual-level. Data were grouped into four administrative boundaries (i.e., county, Zip Code Tabulated Areas, census tracts, and census blocks) and compared to individual-level data (control). Correlation assessed the similarity of SAFs, and map algebra calculated error maps compared to control. This work describes how pre-aggregation affects the level of spatial detail, map patterns, and over and under-prediction.

Objective: To estimate associations of residential mobility with body mass index (BMI), physical activity, and diet and whether associations differ across demographics. Design: Longitudinal cohort with 4 waves of survey follow-up over 15 years. Participants and Setting: A total of 2,110 adolescents and young adults originally from the Twin Cities of Minnesota responded to at least 2 waves of follow-up, beginning at ages 15 to 23 years. Main Outcome Measure(s): Self-reported BMI, physical activity, fast food consumption, breakfast frequency, sugary drink consumption, fruit and vegetable consumption, and screen time. Analysis: Each outcome was modeled as a continuous variable using hierarchical linear regression. Residential mobility—change in residential address—was the main effect of interest. Models adjusted for demographics, marriage during follow-up, and previous level of the outcome. Inverse propensity weights accounted for loss to follow up. Results: No weight-related outcomes differed between movers and nonmovers in the whole sample. When examining effect modification by age, as participants aged, moving was increasingly associated with improvements in weight-related outcomes, particularly BMI. Conclusions and Implications: Results suggest that moving may be associated with poorer weight-related outcomes during a brief window from late teens and early-20s and less associated with weight-related outcomes in the mid-20s and 30s.

Community outreach and engagement has been a regular activity of the National Cancer Institute at its designated Cancer Centers. However, in 2016, community outreach and engagement became a required activity for all cancer centers. Yet there is a gap in the literature that provides guidelines for developing materials that resonate with communities. We developed the PEARL rubric to fulfill that gap from our work developing culturally sensitive breast cancer education materials for African American and Immigrant African women. We conducted a targeted literature review to understand the approaches that have been used for developing education materials for communities. We reviewed the literature and distilled key elements into our PEARL guide for creating culturally appropriate education materials. PEARL consists of five elements: Plain language and understandability, Explicit data, statistics, and graphs, Affirmative framing, Representative content, and Local connection. PEARL is a modern comprehensive guide that researchers can use for creating culturally sensitive materials. It is designed to guide researchers develop educational materials who have little to no experience in community engagement.

Background: Housing mobility impacts adolescent alcohol use, and the neighborhood built environment may impact this relationship. Methods: Moving to Opportunity (MTO) was a multi-site, three-arm, household-level experiment. MTO randomly assigned one of three treatment arms (1994–1997) allowing families living in public housing to (1) receive a voucher to be redeemed any neighborhood (2) receive a voucher to be redeemed in a neighborhood with less than 10% poverty (3) remain in public housing (control). MTO decreased girls’ alcohol use, but increased boys’ alcohol use. Treatment groups were pooled because they are similar conceptually and statistically on our primary outcome. Among youth aged 12–19 in 2001–2002 (N = 2829), we estimated controlled direct effects mediation of MTO treatment effects on youth with housing vouchers (N = 1950) vs. controls (N = 879) on past 30-day number of drinks per day on days drank, using gender-stratified Poisson regression. Mediators were density of on- and off-premises alcohol outlets per square mile at the families’ census tract of residence in 1997. Results: Treatment group youth were randomized to live in 1997 census tracts with lower off-premises, but higher on-premises, outlet density. MTO treatment (vs. controls) decreased drinking for girls via alcohol outlet density, but only at higher levels of outlet density. Treatment was 18% more beneficial when girls moved to high density neighborhoods, compared to controls who stayed living in public housing in high density neighborhoods. Conclusion: Additional social processes unmeasured in the current study may play an important role in the alcohol use and other health risks for girls.

The North Carolina Healthy Food Small Retailer Program (NC HFSRP) was established through a policy passed by the state legislature to provide funding for small food retailers located in food deserts with the goal of increasing access to and sales of healthy foods and beverages among local residents. The purpose of this study was to qualitatively examine perceptions of the NC HFSRP among store customers. Qualitative interviews were conducted with 29 customers from five NC HFSRP stores in food deserts across eastern NC. Interview questions were related to shoppers’ food and beverage purchases at NC HFSRP stores, whether they had noticed any in-store efforts to promote healthier foods and beverages, their suggestions for promoting healthier foods and beverages, their familiarity with and support of the NC HFSRP, and how their shopping and consumption habits had changed since implementation of the NC HFSRP. A codebook was developed based on deductive (from the interview guide questions) and inductive (emerged from the data) codes and operational definitions. Verbatim transcripts were double-coded and a thematic analysis was conducted based on code frequency, and depth of participant responses for each code. Although very few participants were aware of the NC HFSRP legislation, they recognized changes within the store. Customers noted that the provision of healthier foods and beverages in the store had encouraged them to make healthier purchase and consumption choices. When a description of the NC HFSRP was provided to them, all participants were supportive of the state-funded program. Participants discussed program benefits including improving food access in low-income and/or rural areas and making healthy choices easier for youth and for those most at risk of diet-related chronic diseases. Findings can inform future healthy corner store initiatives in terms of framing a rationale for funding or policies by focusing on increased food access among vulnerable populations.

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The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) of Minnesota, "Sage", provides breast cancer screening to uninsured women. We introduce a novel mapping technique, spatially adaptive filters (SAFs), to estimate utilization of Sage screening in Minnesota. Sage screenings (N = 74,712) were geocoded. The eligible population was modeled with the RTI synthetic population dataset. Between 2011 and 2015, 36,979 women a year were Sage eligible. Utilization was highly variable across Minnesota (M = 37.2%, range 0%-131%, SD = 18.7%). This replicable approach modeled utilization rates to the neighborhood-level, allowing Sage to prioritize locations and engage communities. INTRODUCTION Cancer is the second leading cause of mortality among women in the United States, and 30% of new cancer diagnoses in 2020 among women will be breast cancers. 1,2 Breast cancer mortality can be reduced via early detection through screening, yet disparities in breast cancer screening persist. Nationally, low-income women (< $15,000/year) ages 50 to 64 are less likely to be screened than women with higher income (>$50,000/year), 71.9% compared to 83.0%. 3 Women without health insurance are screened at a lower rate (54.7%) than women with insurance (80.5%). 3 Racial disparities in screening also exist, as Asian and American Indian women are screened at lower rates than other groups; women of color and American Indians face disproportionate barriers to screening, such as having lower rates of access to health care. 4,5 Recognizing that access to early breast cancer detection is a health priority among low-income and uninsured women, the National Breast and Cervical Cancer Early Detection Program (NBCCEDP) was established in 1991 to provide screening services for such populations.

<p>Less than one-half of small food stores audited in low-income communities met the USDA’s 2016 proposed expansion of the Supplemental Nutrition Assistance Program-authorized retailer stocking requirements.</p>