Ensuring Equitable Care in Diabetes Management Among Patients of Health Resources & Services Administration-Funded Health Centers in the United States.

Aim: To explore whether there are racial/ethnic differences in diabetes management and outcomes among adult health center (HC) patients with type 2 diabetes. Methods: We analyzed data from the 2014 Health Center Patient Survey, a national sample of HC patients. We examined indicators of diabetes monitoring (A1C testing, annual foot/eye doctor visits, and cholesterol checks) and care management (specialist referrals, individual treatment plan, and receipt of calls/appointments/home visits). We also examined diabetes-specific outcomes (blood glucose levels, diabetes-related emergency department [ED] visits/hospitalizations, and diabetes self-management confidence) and general outcomes (number of doctor visits, ED visits, and hospitalizations). We used multilevel logistic regression models to examine racial/ethnic disparities by the above indicators. Results: We found racial/ethnic parity in A1C testing, eye doctor visits, and diabetes-specific outcomes. However, Hispanics/Latinos (odds ratio [OR] 0.26), non-Hispanic African Americans (OR 0.25), and Asians (OR 0.11) were less likely to receive a cholesterol check than Whites. Non-Hispanic African Americans (OR 0.43) were less likely to have frequent doctor visits, while Hispanic/Latino patients (OR 0.45) were less likely to receive an individual treatment plan. Conclusion: HCs largely provide equitable diabetes care but have room for improvement in some indicators. Tailored efforts such as culturally competent care and health education for some racial/ethnic groups may be needed to improve diabetes management and outcomes.

Factors associated with frequent emergency department visits among health centre patients receiving primary care.

RATIONALE, AIMS AND OBJECTIVES: We sought to examine specific care-seeking behaviours and experiences, access indicators, and patient care management approaches associated with frequency of emergency department (ED) visits among patients of Health Resources and Services Administration-funded health centres that provide comprehensive primary care to low-income and uninsured patients. METHOD: We used cross-sectional data of a most recent nationally representative sample of health centre adult patients aged 18-64 (n = 4577) conducted between October 2014 and April 2015. These data were merged with the 2014 Uniform Data System to incorporate health centre characteristics. We measured care-seeking behaviours by whether the patient called the health centre afterhours, for an urgent appointment, or talked to a provider about a concern. Access to care indicators included health centre continuity of care and receipt of transportation or translation services. We included receipt of care coordination and specialist referral as care management indicators. We used a multilevel multinomial logistic regression model to identify the association of independent variables with number of ED visits (4 or more visits, 2-3 visits, 1 visit, vs. 0 visits), controlling for predisposing, enabling, and need characteristics. RESULTS: Calling the health centre after-hours (OR = 2.41) or for urgent care (OR = 2.53), and being referred to specialists (OR = 2.36) were associated with higher odds of four or more ED visits versus none. Three or more years of continuity with the health centre (OR = 0.32) was also associated with lower odds of four or more ED visits versus none. CONCLUSIONS: Findings underscore opportunities to reduce higher frequency of ED visits in health centres, which are primary care providers to many low-income populations. Our findings highlight the potential importance of improving patient retention, better access to providers afterhours or for urgent visits, and access to specialist as areas of care in need of improvement.

Staffing transformation following Patient-Centered Medical Home recognition among Health Resources & Services Administration-funded health centers.

INTRODUCTION: Patient-Centered Medical Home (PCMH) recognition is designed to promote whole-person team-based and integrated care. PURPOSE: Our goal was to assess changes in staffing infrastructure that promoted team-based and integrated care delivery before and after PCMH recognition in Health Resources & Services Administration (HRSA)-funded health centers (HCs). METHODOLOGY/APPROACH: We identified changes in staffing 2 years before and 3 years after PCMH recognition using 2010-2019 Uniform Data System data among three cohorts of HCs that received PCMH recognition in 2013 ( n = 346), 2014 ( n = 207), and 2015 ( n = 115). Our outcomes were team-based ratio (full-time equivalent medical and nonmedical providers and staff to one primary care physician) and a multidisciplinary staff ratio (allied medical and nonmedical staff to 1,000 patients). We used mixed-effects Poisson regression models. RESULTS: The earlier cohorts served fewer complex patients and were larger before PCMH recognition. Three years following recognition, the 2013 and 2014 cohorts had significantly larger team-based ratios, and all three cohorts had significantly larger multidisciplinary staff ratios. Cohorts varied, however, in the type of staff that drove this change. Both ratios increased in the longer term. CONCLUSION: Our study suggests that growth in team-based and multidisciplinary staff ratios in each cohort may have been due to a combination of HCs' perceptions of need for specific services, HRSA funding, and technical assistance opportunities. POLICY IMPLICATIONS: Further research is needed to understand barriers such as costs of employing a multidisciplinary staff, particularly those that cannot directly bill for services as well as whether such changes lead to practice transformation and improved quality of care.

A Systematic Literature Review of Health Center Efforts to Address Social Determinants of Health.

Health centers (HCs) play a crucial and integral role in addressing social determinants of health (SDOH) among vulnerable and underserved populations, yet data on SDOH assessment and subsequent actions is limited. We conducted a systematic review to understand the existing evidence of integration of SDOH into HC primary-care practices. Database searches yielded 3,516 studies, of which 41 articles met the inclusion criteria. A majority of studies showed that HCs primarily captured patient-level rather than community-level SDOH data. Studies also showed that HCs utilized SDOH in electronic health records but capabilities varied widely. A few studies indicated that HCs measured health-related outcomes of integrating SDOH data. The review highlighted that many knowledge gaps exist in the collection, use, and assessment of impact of these data on outcomes, and future research is needed to address this knowledge gap.

Machine Learning Approach to Facilitate Knowledge Synthesis at the Intersection of Liver Cancer, Epidemiology, and Health Disparities Research.

PURPOSE: Liver cancer is a global challenge, and disparities exist across multiple domains and throughout the disease continuum. However, liver cancer's global epidemiology and etiology are shifting, and the literature is rapidly evolving, presenting a challenge to the synthesis of knowledge needed to identify areas of research needs and to develop research agendas focusing on disparities. Machine learning (ML) techniques can be used to semiautomate the literature review process and improve efficiency. In this study, we detail our approach and provide practical benchmarks for the development of a ML approach to classify literature and extract data at the intersection of three fields: liver cancer, health disparities, and epidemiology. METHODS: We performed a six-phase process including: training (I), validating (II), confirming (III), and performing error analysis (IV) for a ML classifier. We then developed an extraction model (V) and applied it (VI) to the liver cancer literature identified through PubMed. We present precision, recall, F1, and accuracy metrics for the classifier and extraction models as appropriate for each phase of the process. We also provide the results for the application of our extraction model. RESULTS: With limited training data, we achieved a high degree of accuracy for both our classifier and for the extraction model for liver cancer disparities research literature performed using epidemiologic methods. The disparities concept was the most challenging to accurately classify, and concepts that appeared infrequently in our data set were the most difficult to extract. CONCLUSION: We provide a roadmap for using ML to classify and extract comprehensive information on multidisciplinary literature. Our technique can be adapted and modified for other cancers or diseases where disparities persist.

The Relative Contribution of Social Determinants of Health Among Health Resources and Services Administration-Funded Health Centers.

Frameworks for identifying and assessing social determinants of health (SDOH) are effective for developing long-term societal policies to promote health and well-being, but may be less applicable in clinical settings. The authors compared the relative contribution of a specific set of SDOH indicators with several measures of health status among patients served by health centers (HCs). The 2014 Health Center Patient Survey was used to identify a sample of HC patient adults 18 years and older that reported the HC as their usual source of care (n = 5024). The authors examined the relationship between SDOH indicators organized in categories (health behaviors, access and utilization, social factors, economic factors, quality of care, physical environment) with health status measures (fair or poor health, diabetes, hypertension, cardiovascular disease, depression, or anxiety) using logistic regressions and predicted probabilities. Findings indicated that access to care and utilization indicators had the greatest relative contribution to all health status measures, but the relative contribution of other SDOH indicators varied. For example, access indicators had the highest predicted probability in the model with fair or poor health as the dependent variable (72.4%) and the model with hypertension as the dependent variable (47.4%). However, the second highest predicted probability was for social indicators (54.1%) in the former model and physical environment (44.7%) indicators in the latter model. These findings have implications for HCs that serve as the primary point of access to medical care in underserved communities and to mitigate SDOH particularly for patients with diabetes, depression, or anxiety.

Intersection of complexity and high utilization among health center patients aged 18 to 64 years.

OBJECTIVES: Existing literature indicates that multimorbidity, mental health (MH) conditions, substance use disorders (SUDs), and social determinants of health are hallmarks of high-need, high-cost patients. Health Resources and Services Administration-funded health centers (HCs) provide care to nearly 30 million patients, but data on their patients' complexity and utilization patterns are limited. We identified subgroups of HC patients based on latent concepts of complexity and utilization. STUDY DESIGN: We used cross-sectional national data from the 2014 Health Center Patient Survey and latent class analyses to identify distinct and homogenous groups of complex high-utilizing patients aged 18 to 64 years. METHODS: We included indicators of chronic conditions (CCs), MH, SUD risk, and health behavior to measure complexity. We used number of outpatient and emergency department visits in the past year to measure utilization. RESULTS: HC patients were separated in 9 distinct groups based on 3 complexity latent classes (MH, multiple CCs, and low risk) and 3 utilization classes (low, high, and superutilizers). Conditions associated with each subgroup differed. The highest prevalence of bipolar disorder (45%) and high SUD risk (6%) was observed among MH superutilizers, whereas the highest prevalence of cardiovascular disease (48%) and obesity (96%) was seen among CC superutilizers. Most MH superutilizer patients concurrently had MH conditions and obesity and were smokers, but most CC superutilizer patients concurrently had hypertension, obesity, and cardiovascular disease. CONCLUSIONS: Our examination of complexity and utilization indicated distinct HC patient populations. Managing the care of each group may require different targeted intervention approaches such as multidisciplinary care teams that include MH providers or specialists.

Trends in access to care among rural patients served at HRSA-funded health centers.

PURPOSE: Nearly one-fifth of Americans live in rural areas and experience multiple socioeconomic and health disparities. Health Resources and Services Administration (HRSA)-funded health centers (HCs) provide comprehensive primary care in rural communities. However, no prior research has examined trends in access to care in rural HC patients. We examined the change in access to care among patients served at rural HRSA-funded HCs in the United States between 2009 and 2014. METHODS: We compared patients by year to examine measures of access using multilevel generalized structural equation logistic regression models with random effects. We used the 2009 and 2014 cross-sectional Health Center Patient Surveys and identified 2,625 adult rural HC patients. Dependent variables were subjective (unmet need/delay in medical care, mental health, dental care, and prescription medications) and objective measures (preventive care and other health care utilization) in access to care. Our independent variable of interest was time, comparing access in 2009 and 2014. RESULTS: Rural HC patients reported higher predicted probability of influenza vaccine receipt (37% vs 51%), and lower unmet (25% vs 14%) and delayed medical care (36% vs 18%) between 2009 and 2014. Any emergency department visits in the last year increased (32% vs 46%) and mammogram (70% vs 55%) and Pap test (83% vs 72%) screening rates decreased. CONCLUSIONS: Observed increases in access to care among rural HC patients are positive developments but the challenges to access care still persist. Remote services, such as telehealth, could be cost-effective means of improving access to care among rural patients with limited provider supply.

Facilitating cancer systems epidemiology research.

Systems epidemiology offers a more comprehensive and holistic approach to studies of cancer in populations by considering high dimensionality measures from multiple domains, assessing the inter-relationships among risk factors, and considering changes over time. These approaches offer a framework to account for the complexity of cancer and contribute to a broader understanding of the disease. Therefore, NCI sponsored a workshop in February 2019 to facilitate discussion about the opportunities and challenges of the application of systems epidemiology approaches for cancer research. Eight key themes emerged from the discussion: transdisciplinary collaboration and a problem-based approach; methods and modeling considerations; interpretation, validation, and evaluation of models; data needs and opportunities; sharing of data and models; enhanced training practices; dissemination of systems models; and building a systems epidemiology community. This manuscript summarizes these themes, highlights opportunities for cancer systems epidemiology research, outlines ways to foster this research area, and introduces a collection of papers, "Cancer System Epidemiology Insights and Future Opportunities" that highlight findings based on systems epidemiology approaches.

Mental Health Staffing at HRSA-Funded Health Centers May Improve Access to Care.

OBJECTIVE: The study objective was to examine the association between mental health staffing at health centers funded by the Health Resources and Services Administration (HRSA) and patients' receipt of mental health treatment. METHODS: Data were from the 2014 HRSA-funded Health Center Patient Survey and the 2013 Uniform Data System. Colocation of any mental health staff, including psychiatrists, psychologists, and other licensed staff, was examined. The outcomes of interest were whether a patient received any mental treatment and received any such treatment on site (at the health center). Analyses were conducted with multilevel generalized structural equation logistic regression models for 4,575 patients ages 18-64. RESULTS: Patients attending health centers with at least one mental health full-time equivalent (FTE) per 2,000 patients had a higher predicted probability of receiving mental health treatment (32%) compared with those attending centers with fewer than one such FTE (24%) or no such staffing (22%). Among patients who received this treatment, those at health centers with no staffing had a significantly lower predicted probability of receiving such treatment on site (28%), compared with patients at health centers with fewer than one such FTE (49%) and with at least one such FTE (65%). The predicted probability of receiving such treatment on site was significantly higher if there was a colocated psychiatrist versus no psychiatrist (58% versus 40%). CONCLUSIONS: Colocating mental health staff at health centers increases the probability of patients' access to such treatment on site as well as from off-site providers.

Patient-Provider Communication and Adherence to Cholesterol Management Advice: Findings from a Cross-Sectional Survey.

High cholesterol is a preventable risk factor for heart disease. This study examines which aspects of patient-provider communication are associated with patient report of increased adherence to cholesterol management advice in a diverse, low-income patient population accessing the health care safety net, using the 2014 Health Center Patient Survey. Patient-provider communication measures included patient report of: how often a provider listened carefully, gave easy-to-understand information, knew important information about the patient's medical history, showed respect, and spent enough time with the patient. Outcome measures were patient report of following provider advice to eat fewer high fat or high cholesterol foods, manage weight, increase physical activity, or take prescribed medicine. In adjusted analyses, when patients perceived their provider always knew their medical history, patients were more likely to report taking prescribed medication (adjusted odds ratio [aOR]: 3.2; 95% confidence interval [CI]: 1.6, 6.6). Knowledge of medical history (aOR: 2.8, 95% CI: 1.4, 5.8), spending enough time (aOR: 2.3, 95% CI: 1.2, 4.4), and providing easily understandable information (aOR: 2.2, 95% CI: 1.0, 4.7) were significantly associated with report of following physical activity advice. Knowledge of medical history (aOR: 2.3, 95% CI: 1.0, 5.2) and providing easily understandable information (aOR: 3.3, 95% CI: 1.4, 7.9) were significantly associated with report of following weight management advice. This study indicates different components of patient-provider communication influence patient adherence to lifestyle modification advice and medication prescription. These results suggest a tailored approach to optimize the impact of patient-provider communication on cholesterol management advice adherence.

The role of dentist supply, need for care and long-term continuity in Health Resources and Services Administration-funded health centres in the United States.

OBJECTIVES: Health Resources and Services Administration-funded health centres (HCs) are an important source of dental services for low-income and vulnerable patients in the United States. About 82% of HCs in 2018 had dental workforce, but it is unclear whether this workforce meets the oral health needs of HC patients. Thus, we first examined (a) whether dental workforce was associated with any dental visits vs none and (b) whether HC patients with any visits were more likely to have a visit at the HC vs elsewhere. We then examined (c) if need for oral health care and long-term continuity at the HC were associated with dental visits and visits at the HC. METHODS: This study used the 2014 Health Center Patient Survey, a nationally representative study of US HC patients, and the 2013 Uniform Data System, an administrative dataset of HC characteristics. We also used the 2013 Area Health Resource File to measure the contribution of local supply of dentists. We included working-age adult patients (n = 5006) and used multilevel structural equation models with Poisson specification. RESULTS: Larger dental workforce at the HC was significantly associated with 1% higher likelihood (relative risk [RR]: 1.01, 1.00-1.02) of any visits and 10% higher likelihood of a visit at the HC among those with a visit (RR: 1.10, 1.06-1.14). Patient self-reported oral health need was positively associated with 157% higher likelihood of dental visits (RR: 2.57, 2.29-2.88), and 42% higher likelihood of dental visit at the HC vs elsewhere (RR: 1.42, 1.19-1.69). Long-term continuity with the HC was not significantly associated with likelihood of dental visits, but was associated with 26% higher likelihood of visits at the HC among those who had any visits (RR: 1.26, 1.02-1.56). DISCUSSION: The findings highlight the potential impact of increasing dental workforce at HCs to promote access; the high level of need for oral health care at HCs; and the increased effort required to promote access among newer patients who may be less familiar with the availability of oral health care at HCs. Together, these findings reinforce the importance of addressing barriers of use of oral health services among low-income and uninsured patients.

Telehealth Practice Among Health Centers During the COVID-19 Pandemic - United States, July 11-17, 2020.

Early in the coronavirus disease 2019 (COVID-19) pandemic, in-person ambulatory health care visits declined by 60% across the United States, while telehealth* visits increased, accounting for up to 30% of total care provided in some locations (1,2). In March 2020, the Centers for Medicare & Medicaid Services (CMS) released updated regulations and guidance changing telehealth provisions during the COVID-19 Public Health Emergency, including the elimination of geographic barriers and enhanced reimbursement for telehealth services† (3-6). The Health Resources and Services Administration (HRSA) administers a voluntary weekly Health Center COVID-19 Survey§ to track health centers' COVID-19 testing capacity and the impact of COVID-19 on operations, patients, and staff. CDC and HRSA analyzed data from the weekly COVID-19 survey completed by 1,009 HRSA-funded health centers (health centers¶) for the week of July 11-17, 2020, to describe telehealth service use in the United States by U.S. Census region,** urbanicity,†† staffing capacity, change in visit volume, and personal protective equipment (PPE) supply. Among the 1,009 health center respondents, 963 (95.4%) reported providing telehealth services. Health centers in urban areas were more likely to provide >30% of health care visits virtually (i.e., via telehealth) than were health centers in rural areas. Telehealth is a promising approach to promoting access to care and can facilitate public health mitigation strategies and help prevent transmission of SARS-CoV-2 and other respiratory illnesses, while supporting continuity of care. Although CMS's change of its telehealth provisions enabled health centers to expand telehealth by aligning guidance and leveraging federal resources, sustaining expanded use of telehealth services might require additional policies and resources.

Geographic disparities in cancer screening and fatalism among a nationally representative sample of US adults.

BACKGROUND: Cancer screening in the USA is suboptimal, particularly for individuals living in vulnerable communities. This study aimed to understand how rurality and racial segregation are independently and interactively associated with cancer screening and cancer fatalism. METHODS: We used data from a nationally representative sample of adults (n=17 736) from National Cancer Institute's Health Information National Trends Survey, 2011-2017, including cancer screening (colorectal, breast, cervical, prostate) among eligible participants and cancer fatalism. These data were linked to county-level metropolitan status/rurality (US Department of Agriculture) and racial segregation (US Census). We conducted multivariable analyses of associations of geographic variables with screening and fatalism. RESULTS: Breast cancer screening was lower in rural (92%, SE=1.5%) than urban counties (96%, SE=0.5%) (adjusted OR (aOR)=0.52, 95% CI 0.31 to 0.87). Colorectal cancer screening was higher in highly segregated (70%, SE=1.0%) than less segregated counties (65%, SE=1.7%) (aOR=1.28, 95% CI 1.04 to 1.58). Remaining outcomes did not vary by rurality or segregation, and these variables did not interact in their associations with screening or fatalism. CONCLUSION: Similar to previous studies, breast cancer screening was less common in rural areas. Contrary to expectations, colorectal cancer screening was higher in highly segregated counties. More research is needed on the influence of geography on cancer screening and beliefs, and how access to facilities or information may mediate these relationships.

Obesity-Associated Alterations in Inflammation, Epigenetics, and Mammary Tumor Growth Persist in Formerly Obese Mice.

Using a murine model of basal-like breast cancer, we tested the hypothesis that chronic obesity, an established breast cancer risk and progression factor in women, induces mammary gland epigenetic reprogramming and increases mammary tumor growth. Moreover, we assessed whether the obesity-induced epigenetic and protumor effects are reversed by weight normalization. Ovariectomized female C57BL/6 mice were fed a control diet or diet-induced obesity (DIO) regimen for 17 weeks, resulting in a normal weight or obese phenotype, respectively. Mice on the DIO regimen were then randomized to continue the DIO diet or were switched to the control diet, resulting in formerly obese (FOb) mice with weights comparable with control mice. At week 24, all mice were orthotopically injected with MMTV-Wnt-1 mouse mammary tumor cells. Mean tumor volume, serum IL6 levels, expression of proinflammatory genes in the mammary fat pad, and mammary DNA methylation profiles were similar in DIO and FOb mice and higher than in controls. Many of the genes found to have obesity-associated hypermethylation in mice were also found to be hypermethylated in the normal breast tissue of obese versus nonobese human subjects, and nearly all of these concordant genes remained hypermethylated after significant weight loss in the FOb mice. Our findings suggest that weight normalization may not be sufficient to reverse the effects of chronic obesity on epigenetic reprogramming and inflammatory signals in the microenvironment that are associated with breast cancer progression. Cancer Prev Res; 9(5); 339-48. ©2016 AACR.

Body mass index associated with genome-wide methylation in breast tissue.

Gene expression studies indicate that body mass index (BMI) is associated with molecular pathways involved in inflammation, insulin-like growth factor activation, and other carcinogenic processes in breast tissue. The goal of this study was to determine whether BMI is associated with gene methylation in breast tissue and to identify pathways that are commonly methylated in association with high BMI. Epigenome-wide methylation profiles were determined using the Illumina HumanMethylation450 BeadChip array in the non-diseased breast tissue of 81 women undergoing breast surgery between 2009 and 2013 at the University of North Carolina Hospitals. Multivariable, robust linear regression was performed to identify methylation sites associated with BMI at a false discovery rate q value <0.05. Gene expression microarray data was used to identify which of the BMI-associated methylation sites also showed correlation with gene expression. Gene set enrichment analysis was conducted to assess which pathways were enriched among the BMI-associated methylation sites. Of the 431,568 methylation sites analyzed, 2573 were associated with BMI (q value <0.05), 57 % of which showed an inverse correlation with BMI. Pathways enriched among the 2573 probe sites included those involved in inflammation, insulin receptor signaling, and leptin signaling. We were able to map 1251 of the BMI-associated methylation sites to gene expression data, and, of these, 226 (18 %) showed substantial correlations with gene expression. Our results suggest that BMI is associated with genome-wide methylation in non-diseased breast tissue and may influence epigenetic pathways involved in inflammatory and other carcinogenic processes.

Racial variation in breast tumor promoter methylation in the Carolina Breast Cancer Study.

BACKGROUND: African American (AA) women are diagnosed with more advanced breast cancers and have worse survival than white women, but a comprehensive understanding of the basis for this disparity remains unclear. Analysis of DNA methylation, an epigenetic mechanism that can regulate gene expression, could help to explain racial differences in breast tumor clinical biology and outcomes. METHODS: DNA methylation was evaluated at 1,287 CpGs in the promoters of cancer-related genes in 517 breast tumors of AA (n = 216) or non-AA (n = 301) cases in the Carolina Breast Cancer Study (CBCS). RESULTS: Multivariable linear regression analysis of all tumors, controlling for age, menopausal status, stage, intrinsic subtype, and multiple comparisons [false discovery rate (FDR)], identified seven CpG probes that showed significant (adjusted P < 0.05) differential methylation between AAs and non-AAs. Stratified analyses detected an additional four CpG probes differing by race within hormone receptor-negative (HR(-)) tumors. Genes differentially methylated by race included DSC2, KCNK4, GSTM1, AXL, DNAJC15, HBII-52, TUSC3, and TES; the methylation state of several of these genes may be associated with worse survival in AAs. TCGA breast tumor data confirmed the differential methylation by race and negative correlations with expression for most of these genes. Several loci also showed racial differences in methylation in peripheral blood leukocytes (PBL) from CBCS cases, indicating that these variations were not necessarily tumor-specific. CONCLUSIONS: Racial differences in the methylation of cancer-related genes are detectable in both tumors and PBLs from breast cancer cases. IMPACT: Epigenetic variation could contribute to differences in breast tumor development and outcomes between AAs and non-AAs.

Body mass index is associated with gene methylation in estrogen receptor-positive breast tumors.

BACKGROUND: Although obesity is associated with breast cancer incidence and prognosis, the underlying mechanisms are poorly understood. Identification of obesity-associated epigenetic changes in breast tissue may advance mechanistic understanding of breast cancer initiation and progression. The goal of this study, therefore, was to investigate associations between obesity and gene methylation in breast tumors. METHODS: Using the Illumina GoldenGate Cancer I Panel, we estimated the association between body mass index (BMI) and gene methylation in 345 breast tumor samples from phase I of the Carolina Breast Cancer Study, a population-based case-control study. Multivariable linear regression was used to identify sites that were differentially methylated by BMI. Stratification by tumor estrogen receptor (ER) status was also conducted. RESULTS: In the majority of the 935 probes analyzed (87%), the average beta value increased with obesity (BMI ≥ 30). Obesity was significantly associated with differential methylation (FDR q < 0.05) in just two gene loci in breast tumor tissue overall and in 21 loci among ER-positive tumors. Obesity was associated with methylation of genes that function in immune response, cell growth, and DNA repair. CONCLUSIONS: Obesity is associated with altered methylation overall, and with hypermethylation among ER-positive tumors in particular, suggesting that obesity may influence the methylation of genes with known relevance to cancer. Some of these differences in methylation by obese status may influence levels of gene expression within breast cells. IMPACT: If our results are validated, obesity-associated methylation sites could serve as targets for prevention and treatment research. Cancer Epidemiol Biomarkers Prev; 24(3); 580-6. ©2015 AACR.

Racial differences in physical activity among breast cancer survivors: implications for breast cancer care.

BACKGROUND: Physical activity after breast cancer diagnosis is associated with improved survival. The current study examined levels of and changes in physical activity after breast cancer diagnosis, overall and by race. METHODS: Phase 3 of the Carolina Breast Cancer Study assessed both pre- and postdiagnosis physical activity levels in a cohort of 1735 women aged 20 years to 74 years who were diagnosed with invasive breast cancer between 2008 and 2011 in 44 counties of North Carolina. Logistic regression and analysis of variance were used to examine whether demographic, behavioral, and clinical characteristics were associated with activity levels. RESULTS: Only 35% of study participants met current physical activity guidelines after diagnosis with breast cancer. A decrease in activity after diagnosis was reported by 59% of patients, with the average study participant reducing their activity by 15 metabolic equivalent task (MET) hours (95% confidence interval [95% CI], 12 MET hours-19 MET hours). After adjustment for potential confounders, when compared with white women, African American women were less likely to meet national physical activity guidelines after diagnosis (odds ratio, 1.38; 95% CI, 1.01-1.88) and reported less weekly postdiagnosis physical activity (12 MET hours vs 14 MET hours; P = .13). In adjusted stratified analyses, receipt of treatment was found to be significantly associated with postdiagnosis activity in African American women (P < 0.01). CONCLUSIONS: Despite compelling evidence demonstrating the benefits of physical activity after a diagnosis of breast cancer, it is clear that more work needs to be done to promote physical activity in patients with breast cancer, especially among African American women.

A comparison of ambulatory perioperative times in hospitals and freestanding centers.

BACKGROUND: The volume of surgical procedures performed in ambulatory surgical centers has increased rapidly. METHODS: Ambulatory surgical visits of Medicare beneficiaries were compared for hospital-based and freestanding ambulatory surgical centers (ASCs). The main outcomes were time in surgery, time in operating room, time in postoperative care, and total perioperative time. RESULTS: The mean total perioperative time for all procedures examined was 39% shorter in freestanding ASCs then in hospital-based ASCs (83 vs 135 min; P < .01); surgery time was 37% shorter (19 vs 30 min; P < .01), operating room time was 37% shorter (34 vs 54 min; P < .01), and postoperative time was 35% shorter (48 vs 74 min; P < .01). CONCLUSIONS: Perioperative times were significantly shorter in freestanding ASCs than in hospital-based ASCs. It is unclear how much of the difference was the result of efficiency versus patient selection.