Measuring variation in infant mortality and deaths of despair by US congressional district in Pennsylvania: a methodological case study.

Many ecological studies examine health outcomes and disparities using administrative boundaries such as census tracts, counties, or states. These boundaries help us to understand the patterning of health by place, along with impacts of policies implemented at these levels. However, additional geopolitical units (units with both geographic and political meaning), such as congressional districts (CDs), present further opportunities to connect research with public policy. Here we provide a step-by-step guide on how to conduct disparities-focused analysis at the CD level. As an applied case study, we use geocoded vital statistics data from 2010-2015 to examine levels of and disparities in infant mortality and deaths of despair in the 19 US CDs of Pennsylvania for the 111th-112th (2009-2012) Congresses and 18 CDs for the 113th-114th (2013-2016) Congresses. We also provide recommendations for extending CD-level analysis to other outcomes, states, and geopolitical boundaries, such as state legislative districts. Increased surveillance of health outcomes at the CD level can help prompt policy action and advocacy and, hopefully, reduce rates of and disparities in adverse health outcomes.

Comparison of the characteristics of the population eligible for lung cancer screening under 2013 and population newly eligible under 2021 US Preventive Services Task Force recommendations.

PURPOSE: In 2021, the United States Preventive Services Task Force (USPSTF) revised their 2013 recommendations for lung cancer screening eligibility by lowering the pack-year history from 30+ to 20+ pack-years and the recommended age from 55 to 50 years. Simulation studies suggest that Black persons and females will benefit most from these changes, but it is unclear how the revised USPSTF recommendations will impact geographic, health-related, and other sociodemographic characteristics of those eligible. METHODS: This cross-sectional study employed data from the 2017-2020 Behavioral Risk Factor Surveillance System surveys from 23 states to compare age, gender, race, marital, sexual orientation, education, employment, comorbidity, vaccination, region, and rurality characteristics of the eligible population according to the original 2013 USPSTF recommendations with the revised 2021 USPSTF recommendations using chi-squared tests. This study compared those originally eligible to those newly eligible using the BRFSS raking-dervived weighting variable. RESULTS: There were 30,190 study participants. The results of this study found that eligibility increased by 62.4% due to the revised recommendations. We found that the recommendation changes increased the proportion of eligible females (50.1% vs 44.1%), Black persons (9.2% vs 6.6%), Hispanic persons (4.4% vs 2.7%), persons aged 55-64 (55.8% vs 52.6%), urban-dwellers(88.3% vs 85.9%), unmarried (3.4% vs 2.5%) and never married (10.4% vs 6.6%) persons, as well as non-retirees (76.5% vs 56.1%) Respondents without comorbidities and COPD also increased. CONCLUSION: It is estimated that the revision of the lung cancer screening recommendations decreased eligibility disparities in sex, race, ethnicity, marital status, respiratory comorbidities, and vaccination status. Research will be necessary to estimate whether uptake patterns subsequently follow the expanded eligibility patterns.

Geographic Disparities in Availability of General and Specialized Pediatricians in the US and Prevalence of Childhood Neurodevelopmental Disorders.

General pediatricians and those specialized in developmental-behavioral and neurodevelopmental disabilities support children with neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We identified substantial geographic disparities in pediatrician availability (eg, urban > rural areas), as well as regions with low pediatrician access but high ASD/ADHD prevalence estimates (eg, the US Southeast).

Chronic Disease Prevalence in the US: Sociodemographic and Geographic Variations by Zip Code Tabulation Area.

Introduction: We examined the geographic distribution and sociodemographic and economic characteristics of chronic disease prevalence in the US. Understanding disease prevalence and its impact on communities is crucial for effective public health interventions. Methods: Data came from the American Community Survey, the American Hospital Association Survey, and the Centers for Disease Control and Prevention's PLACES. We used quartile thresholds for 10 chronic diseases to assess chronic disease prevalence by Zip Code Tabulation Areas (ZCTAs). ZCTAs were scored from 0 to 20 based on their chronic disease prevalence quartile. Three prevalence categories were established: least prevalent (score ≤6), moderately prevalent (score 7-13), and highest prevalence (score ≥14). Community characteristics were compared across categories and spatial analyses to identify clusters of ZCTAs with high disease prevalence. Results: Our study showed a high prevalence of chronic disease in the southeastern region of the US. Populations in ZCTAs with the highest prevalence showed significantly greater socioeconomic disadvantages (ie, lower household income, lower home value, lower educational attainment, and higher uninsured rates) and barriers to health care access (lower percentage of car ownership and longer travel distances to hospital-based intensive care units, emergency departments, federally qualified health centers, and pharmacies) compared with ZCTAs with the lowest prevalence. Conclusion: Socioeconomic disparities and health care access should be addressed in communities with high chronic disease prevalence. Carefully directed resource allocation and interventions are necessary to reduce the effects of chronic disease on these communities. Policy makers and clinicians should prioritize efforts to reduce chronic disease prevalence and improve the overall health and well-being of affected communities throughout the US.

Effect of rurality and travel distance on contralateral prophylactic mastectomy for unilateral breast cancer.

PURPOSE: Despite lack of survival benefit, demand for contralateral prophylactic mastectomy (CPM) to treat unilateral breast cancer remains high. High uptake of CPM has been demonstrated in Midwestern rural women. Greater travel distance for surgical treatment is associated with CPM. Our objective was to examine the relationship between rurality and travel distance to surgery with CPM. METHODS: Women diagnosed with stages I-III unilateral breast cancer between 2007 and 2017 were identified using the National Cancer Database. Logistic regression was used to model likelihood of CPM based on rurality, proximity to metropolitan centers, and travel distance. A multinomial logistic regression model compared factors associated with CPM with reconstruction versus other surgical options. RESULTS: Both rurality (OR 1.10, 95% CI 1.06-1.15 for non-metro/rural vs. metro) and travel distance (OR 1.37, 95% CI 1.33-1.41 for those who traveled 50 + miles vs. < 30 miles) were independently associated with CPM. For women who traveled 30 + miles, odds of receiving CPM were highest for non-metro/rural women (OR 1.33 for 30-49 miles, OR 1.57 for 50 + miles; reference: metro women traveling < 30 miles). Non-metro/rural women who received reconstruction were more likely to undergo CPM regardless of travel distance (ORs 1.11-1.21). Both metro and metro-adjacent women who received reconstruction were more likely to undergo CPM only if they traveled 30 + miles (ORs 1.24-1.30). CONCLUSION: The impact of travel distance on likelihood of CPM varies by patient rurality and receipt of reconstruction. Further research is needed to understand how patient residence, travel burden, and geographic access to comprehensive cancer care services, including reconstruction, influence patient decisions regarding surgery.

Equitable implementation of lung cancer screening: avoiding its potential to mirror existing inequities among people who use tobacco.

PURPOSE: Lung cancer is the leading cause of cancer death, but the advent of lung cancer screening using low-dose computed tomography offers a tremendous opportunity to improve lung cancer outcomes. Unfortunately, implementation of lung cancer screening has been hampered by substantial barriers and remains suboptimal. Specifically, the commentary emphasizes the intersectionality of smoking history and several important sociodemographic characteristics and identities that should inform lung cancer screening outreach and engagement efforts, including socioeconomic considerations (e.g., health insurance status), racial and ethnic identity, LGBTQ + identity, mental health history, military experience/veteran status, and geographic residence in addressing specific community risk factors and future interventions in efforts to make strides toward equitable lung cancer screening. METHODS: Members of the Equitable Implementation of Lung Cancer Screening Interest Group with the Cancer Prevention and Control Network (CPCRN) provide a critical commentary based on existing literature regarding smoking trends in the US and lung cancer screening uptake to propose opportunities to enhance implementation and support equitable distribution of the benefits of lung cancer screening. CONCLUSION: The present commentary utilizes information about historical trends in tobacco use to highlight opportunities for targeted outreach efforts to engage communities at high risk with information about the lung cancer screening opportunity. Future efforts toward equitable implementation of lung cancer screening should focus on multi-level implementation strategies that engage and work in concert with community partners to co-create approaches that leverage strengths and reduce barriers within specific communities to achieve the potential of lung cancer screening.

Measuring and addressing health equity: an assessment of cancer center designation requirements.

PURPOSE: By requiring specific measures, cancer endorsements (e.g., accreditations, designations, certifications) promote high-quality cancer care. While 'quality' is the defining feature, less is known about how these endorsements consider equity. Given the inequities in access to high-quality cancer care, we assessed the extent to which equity structures, processes, and outcomes were required for cancer center endorsements. METHODS: We performed a content analysis of medical oncology, radiation oncology, surgical oncology, and research hospital endorsements from the American Society of Clinical Oncology (ASCO), American Society of Radiation Oncology (ASTRO), American College of Surgeons Commission on Cancer (CoC), and the National Cancer Institute (NCI), respectively. We analyzed requirements for equity-focused content and compared how each endorsing body included equity as a requirement along three axes: structures, processes, and outcomes. RESULTS: ASCO guidelines centered on processes assessing financial, health literacy, and psychosocial barriers to care. ASTRO guidelines related to language needs and processes to address financial barriers. CoC equity-related guidelines focused on processes addressing financial and psychosocial concerns of survivors, and hospital-identified barriers to care. NCI guidelines considered equity related to cancer disparities research, inclusion of diverse groups in outreach and clinical trials, and diversification of investigators. None of the guidelines explicitly required measures of equitable care delivery or outcomes beyond clinical trial enrollment. CONCLUSION: Overall, equity requirements were limited. Leveraging the influence and infrastructure of cancer quality endorsements could enhance progress toward achieving cancer care equity. We recommend that endorsing organizations 1) require cancer centers to implement processes for measuring and tracking health equity outcomes and 2) engage diverse community stakeholders to develop strategies for addressing discrimination.

Prioritizing rural populations in state comprehensive cancer control plans: a qualitative assessment.

PURPOSE: The Centers for Disease Control and Prevention's National Comprehensive Cancer Control Program (NCCCP) requires that states develop comprehensive cancer control (CCC) plans and recommends that disparities related to rural residence are addressed in these plans. The objective of this study was to explore rural partner engagement and describe effective strategies for incorporating a rural focus in CCC plans. METHODS: States were selected for inclusion using stratified sampling based on state rurality and region. State cancer control leaders were interviewed about facilitators and barriers to engaging rural partners and strategies for prioritizing rural populations. Content analysis was conducted to identify themes across states. RESULTS: Interviews (n = 30) revealed themes in three domains related to rural inclusion in CCC plans. The first domain (barriers) included (1) designing CCC plans to be broad, (2) defining "rural populations," and (3) geographic distance. The second domain (successful strategies) included (1) collaborating with rural healthcare systems, (2) recruiting rural constituents, (3) leveraging rural community-academic partnerships, and (4) working jointly with Native nations. The third domain (strategies for future plan development) included (1) building relationships with rural communities, (2) engaging rural constituents in planning, (3) developing a better understanding of rural needs, and (4) considering resources for addressing rural disparities. CONCLUSION: Significant relationship building with rural communities, resource provision, and successful strategies used by others may improve inclusion of rural needs in state comprehensive cancer control plans and ultimately help plan developers directly address rural cancer health disparities.

Evaluation of Bayesian spatiotemporal infectious disease models for prospective surveillance analysis.

BACKGROUND: COVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection efforts expand, there is a critical need for infectious disease modeling researchers to continue to develop prospective surveillance metrics and statistical models to accommodate the modeling of large disease counts and variability. This paper evaluated different likelihoods for the disease count model and various spatiotemporal mean models for prospective surveillance. METHODS: We evaluated Bayesian spatiotemporal models, which are the foundation for model-based infectious disease surveillance metrics. Bayesian spatiotemporal mean models based on the Poisson and the negative binomial likelihoods were evaluated with the different lengths of past data usage. We compared their goodness of fit and short-term prediction performance with both simulated epidemic data and real data from the COVID-19 pandemic. RESULTS: The simulation results show that the negative binomial likelihood-based models show better goodness of fit results than Poisson likelihood-based models as deemed by smaller deviance information criteria (DIC) values. However, Poisson models yield smaller mean square error (MSE) and mean absolute one-step prediction error (MAOSPE) results when we use a shorter length of the past data such as 7 and 3 time periods. Real COVID-19 data analysis of New Jersey and South Carolina shows similar results for the goodness of fit and short-term prediction results. Negative binomial-based mean models showed better performance when we used the past data of 52 time periods. Poisson-based mean models showed comparable goodness of fit performance and smaller MSE and MAOSPE results when we used the past data of 7 and 3 time periods. CONCLUSION: We evaluate these models and provide future infectious disease outbreak modeling guidelines for Bayesian spatiotemporal analysis. Our choice of the likelihood and spatiotemporal mean models was influenced by both historical data length and variability. With a longer length of past data usage and more over-dispersed data, the negative binomial likelihood shows a better model fit than the Poisson likelihood. However, as we use a shorter length of the past data for our surveillance analysis, the difference between the Poisson and the negative binomial models becomes smaller. In this case, the Poisson likelihood shows robust posterior mean estimate and short-term prediction results.

Outcomes of Shared Decision-Making for Low-Dose Screening for Lung Cancer in an Academic Medical Center.

Shared decision-making (SDM) helps patients weigh risks and benefits of screening approaches. Little is known about SDM visits between patients and healthcare providers in the context of lung cancer screening. This study explored the extent that patients were informed by their provider of the benefits and harms of lung cancer screening and expressed certainty about their screening choice. We conducted a survey with 75 patients from an academic medical center in the Southeastern U.S. Survey items included knowledge of benefits and harms of screening, patients' value elicitation during SDM visits, and decisional certainty. Patient and provider characteristics were collected through electronic medical records or self-report. Descriptive statistics, Kruskal-Wallis tests, and Pearson correlations between screening knowledge, value elicitation, and decisional conflict were calculated. The sample was predominately non-Hispanic White (73.3%) with no more than high school education (53.4%) and referred by their primary care provider for screening (78.7%). Patients reported that providers almost always discussed benefits of screening (81.3%), but infrequently discussed potential harms (44.0%). On average, patients had low knowledge about screening (score = 3.71 out of 8) and benefits/harms. Decisional conflict was low (score = - 3.12) and weakly related to knowledge (R= - 0.25) or value elicitation (R= - 0.27). Black patients experienced higher decisional conflict than White patients (score = - 2.21 vs - 3.44). Despite knowledge scores being generally low, study patients experienced low decisional conflict regarding their decision to undergo lung cancer screening. Additional work is needed to optimize the quality and consistency of information presented to patients considering screening.

Implementation During a Pandemic: Findings, Successes, and Lessons Learned from Community Grantees.

Funding communities through mini-grant programs builds community capacity by fostering leadership among community members, developing expertise in implementing evidence-based practices, and increasing trust in partnerships. The South Carolina Cancer Prevention and Control Research Network (SC-CPCRN) implemented the Community Health Intervention Program (CHIP) mini-grants initiative to address cancer-related health disparities among high-risk populations in rural areas of the state. One community-based organization and one faith-based organization were funded during the most recent call for proposals. The organizations implemented National Cancer Institute evidence-based strategies and programs focused on health and cancer screenings and physical activity and promotion of walking trails. Despite the potential for the COVID-19 pandemic to serve as a major barrier to implementation, grantees successfully recruited and engaged community members in evidence-based activities. These initiatives added material benefits to their local communities, including promotion of walking outdoors where it is less likely to contract the virus when socially distanced and provision of COVID-19 testing and vaccines along with other health and cancer screenings. Future mini-grants programs will benefit from learning from current grantees' flexibility in program implementation during a pandemic as well as their intentional approach to modifying program aspects as needed.

Trends in Cancer Treatment Service Availability Across Critical Access Hospitals and Prospective Payment System Hospitals.

BACKGROUND: Rural residents experience worse cancer prognosis and access to cancer care providers than their urban counterparts. Critical access hospitals (CAHs) represent over half of all rural community hospitals. However, research on cancer services provided within CAHs is limited. OBJECTIVE: The objective of this study was to investigate trends in cancer services availability in urban and rural Prospective Payment System (PPS) hospitals and CAHs. DESIGN: Retrospective, time-series analysis using data from 2008 to 2017 American Hospital Association Annual Surveys. Multivariable logistic regressions were used to examine differential trends in cancer services between urban PPS, rural PPS, and CAHs, overall and among small (<25 beds) hospitals. SUBJECTS: All US acute care and cancer hospitals (4752 in 2008 to 4722 in 2017). MEASURES: Primary outcomes include whether a hospital provided comprehensive oncology services, chemotherapy, and radiation therapy each year. RESULTS: In 2008, CAHs were less likely to provide all cancer services, especially chemotherapy (30.4%) and radiation therapy (2.9%), compared with urban (64.4% and 43.8%, respectively) and rural PPS hospitals (42.0% and 23.3%, respectively). During 2008-2017, compared with similarly sized PPS hospitals, CAHs were more likely to provide oncology services and chemotherapy, but with decreasing trends. Radiation therapy availability between small PPS hospitals and CAHs did not differ. CONCLUSIONS: Compared with all PPS hospitals, CAHs offered fewer cancer treatment services and experienced a decline in service capability over time. These differences in chemotherapy services were mainly driven by hospital size, as small urban and rural PPS hospitals had lower rates of chemotherapy than CAHs. Still, the lower rates of radiotherapy in CAHs highlight disproportionate challenges facing CAHs for some specialty services.

How cancer programs identify and address the financial burdens of rural cancer patients.

PURPOSE: Financial toxicity is associated with negative patient outcomes, and rural populations are disproportionately affected by the high costs of cancer care compared to urban populations. Our objective was to (1) understand cancer programs' perceptions of rural-urban differences in cancer patients' experiences of financial hardship, (2) evaluate the resources available to cancer patients across the rural-urban continuum, and (3) determine how rural and urban health care teams assess and address financial distress in cancer patients. METHODS: Seven research teams within the Cancer Prevention and Research Control Network conducted semi-structured interviews with cancer program staff who have a role in connecting cancer patients with financial assistance services in both rural and urban counties. Interviews were audio-recorded and transcribed. We identified themes using descriptive content and thematic analysis. RESULTS: We interviewed 35 staffs across 29 cancer care programs in seven states, with roughly half of respondents from programs in rural counties. Participants identified differences in rural and urban patients' experiences of financial hardship related to distance required to travel for treatment, underinsurance, and low socioeconomic status. Insufficient staffing was an identified barrier to addressing rural and urban patients' financial concerns. CONCLUSIONS: Improved financial navigation services could mitigate the effects of financial toxicity experienced by cancer patients, particularly rural patients, throughout treatment and survivorship. Future research is needed to improve how cancer programs assess financial hardship in patients and to expand financial navigation services to better serve rural cancer patients.

Exploring Disparities in Youth Physical Activity Environments by Income and Non-Hispanic White Population Across the United States.

This study investigated relationships between youth physical activity (PA) environments and income and non-Hispanic White population across the United States, stratified by US Census region and urban-rural designation. For all counties (n = 3142), publicly accessible data were used for sociodemographic indicators (ie, median household income and percent non-Hispanic White population) and a composite PA environment index (including exercise opportunities, violent crime incidence, walkability, and access to public schools). One-way analysis of variance was used to examine differences in PA environment index values according to income and non-Hispanic White population tertiles. There were significant differences in PA environments according to tertiles of income (F = 493.5, P < .001) and non-Hispanic White population (F = 58.6, P < .001), including variations by region and urban-rural designation. Public health practice and policy initiatives, such as joint use agreements, Safe Routes to School programs, and targeted funding allocations, should be used to address more pronounced income-based disparities in Southern and metropolitan counties and race-based disparities in rural and micropolitan counties.

Residential Segregation and Emergency Department Utilization Among an Underserved Urban Emergency Department Sample in North Carolina.

BACKGROUND Residential segregation is a spatial manifestation of structural racism. Racial disparities in emergency department (ED) utilization mirror social inequity in the larger community. We evaluated associations between residential segregation and ED utilization in a community with known disparities and geographically concentrated social and health risk.METHODS Cross-sectional data were collected from electronic medical records of 101 060 adult ED patients living in Mecklenburg County, North Carolina in 2017. Community context was measured as residential segregation using the dissimilarity index, categorized into quintiles (Q1-Q5) using 2013-2017 American Community Survey estimates, and residency in a public health priority area (PHPA). The outcome was measured as total ED visits during the study period. Associations between community context and ED utilization were modeled using Anderson's behavioral model of health service utilization, and estimated using negative binomial regression, including interaction terms by race.RESULTS Compared to areas with the lowest proportions of Black residents (Q1), living in Q4 was associated with higher rates of ED utilization among Black/Other (AME = 0.11) and White (AME = 0.23) patients, while associations with living in Q5 were approximately equivalent (AME = 0.12). PHPA residency was associated with higher rates of ED utilization among Black/Other (AME = 0.10) and White patients (AME = 0.22).LIMITATIONS Associations should not be interpreted as causal, or be generalized to the larger community without ED utilization. Health system leakage is possible but limited.CONCLUSIONS Residential segregation is associated with higher rates of ED utilization, as are PHPA residency and other individual-level determinants.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach.

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

Rural-urban and racial/ethnic trends and disparities in early-onset and average-onset colorectal cancer.

BACKGROUND: Incidence rates (IRs) of early-onset colorectal cancer (EOCRC) are increasing, whereas average-onset colorectal cancer (AOCRC) rates are decreasing. However, rural-urban and racial/ethnic differences in trends by age have not been explored. The objective of this study was to examine joint rural-urban and racial/ethnic trends and disparities in EOCRC and AOCRC IRs. METHODS: Surveillance, Epidemiology, and End Results data on the incidence of EOCRC (age, 20-49 years) and AOCRC (age, ≥50 years) were analyzed. Annual percent changes (APCs) in trends between 2000 and 2016 were calculated jointly by rurality and race/ethnicity. IRs and rate ratios were calculated for 2012-2016 by rurality, race/ethnicity, sex, and subsite. RESULTS: EOCRC IRs increased 35% from 10.44 to 14.09 per 100,000 in rural populations (APC, 2.09; P < .05) and nearly 20% from 9.37 to 11.20 per 100,000 in urban populations (APC, 1.26; P < .05). AOCRC rates decreased among both rural and urban populations, but the magnitude of improvement was greater in urban populations. EOCRC increased among non-Hispanic White (NHW) populations, although rural non-Hispanic Black (NHB) trends were stable. Between 2012 and 2016, EOCRC IRs were higher among all rural populations in comparison with urban populations, including NHW, NHB, and American Indian/Alaska Native populations. By sex, rural NHB women had the highest EOCRC IRs across subgroup comparisons, and this was driven primarily by colon cancer IRs 62% higher than those of their urban peers. CONCLUSIONS: EOCRC IRs increased in rural and urban populations, but the increase was greater in rural populations. NHB and American Indian/Alaska Native populations had particularly notable rural-urban disparities. Future research should examine the etiology of these trends.

Multilevel predictors of guideline concordant needle biopsy use for non-metastatic breast cancer.

PURPOSE: Persistent breast cancer disparities, particularly geographic disparities, may be explained by diagnostic practice patterns such as utilization of needle biopsy, a National Quality Forum-endorsed quality metric for breast cancer diagnosis. Our objective was to assess the relationship between patient- and facility-level factors and needle biopsy receipt among women with non-metastatic breast cancer in the United States. METHODS: We examined characteristics of women diagnosed with breast cancer between 2004 and 2015 in the National Cancer Database. We assessed the relationship between patient- (e.g., race/ethnicity, stage, age, rurality) and facility-level (e.g., facility type, breast cancer case volume) factors with needle biopsy utilization via a mixed effects logistic regression model controlling for clustering by facility. RESULTS: In our cohort of 992,209 patients, 82.96% received needle biopsy. In adjusted models, the odds of needle biopsy receipt were higher for Hispanic (OR 1.04, Confidence Interval 1.01-1.08) and Medicaid patients (OR 1.04, CI 1.02-1.08), and for patients receiving care at Integrated Network Cancer Programs (OR 1.21, CI 1.02-1.43). Odds of needle biopsy receipt were lower for non-metropolitan patients (OR 0.93, CI 0.90-0.96), patients with cancer stage 0 or I (at least OR 0.89, CI 0.86-0.91), patients with comorbidities (OR 0.93, CI 0.91-0.94), and for patients receiving care at Community Cancer Programs (OR 0.84, CI 0.74-0.96). CONCLUSION: This study suggests a need to account for sociodemographic factors including rurality as predictors of utilization of evidence-based diagnostic testing, such as needle biopsy. Addressing inequities in breast cancer diagnosis quality may help improve breast cancer outcomes in underserved patients.

Cervical cancer treatment initiation and survival: The role of residential proximity to cancer care.

OBJECTIVE: To examine the role of driving time to cancer care facilities on days to cancer treatment initiation and cause-specific survival for cervical cancer patients. METHODS: A retrospective cohort analysis of patients diagnosed with invasive cervical cancer during 2001-2016, using South Carolina Central Cancer Registry data linked to vital records. Kaplan-Meier survival curves and Cox proportional hazards models were used to examine the association of driving times to both a patient's nearest and actual cancer treatment initiation facility with cause-specific survival and time to treatment initiation. RESULTS: Of 2518 eligible patients, median cause-specific survival was 49 months (interquartile, 17-116) and time to cancer treatment initiation was 21 days (interquartile, 0-40). Compared to patients living within 15 min of the nearest cancer provider, those living more than 30 min away were less likely to receive initial treatment at teaching hospitals, Joint Commission accredited facilities, and/or Commission on Cancer accredited facilities. After controlling for patient, clinical, and provider characteristics, no significant associations existed between driving times to the nearest cancer provider and survival/time to treatment. When examining driving times to treatment initiation (rather than simply nearest) provider, patients who traveled farther than 30 min to their actual providers had delayed initiation of cancer treatment (hazard ratio, 0.81; 95% confidence interval, 0.73-0.90), including surgery (0.82; 95% CI, 0.72-0.92) and radiotherapy (0.82, 95% CI, 0.72-0.94). Traveling farther than 30 min to the first treating provider was not associated with worse cause-specific survival. CONCLUSIONS: For cervical cancer patients, driving time to chosen treatment providers, but not to the nearest cancer care provider, was associated with prolonged time to treatment initiation. Neither was associated with survival.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income.

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions.