Population Structure Analyses Provide Insight into the Source Populations Underlying Rural Isolated Communities in Illinois.

We have previously hypothesized that relatively small and isolated rural communities may experience founder effects, defined as the genetic ramifications of small population sizes at the time of a community's establishment. To explore this, we used an Illumina Infinium Omni2.5Exome-8 chip to collect data from 157 individuals from four Illinois communities, three rural and one urban. Genetic diversity estimates of 999,259 autosomal markers suggested that the reduction in heterozygosity due to shared ancestry was approximately 0, indicating a randomly mating population. An eigenanalysis, which is similar to a principal component analysis but run on a genetic coancestry matrix, conducted in the SNPRelate R package revealed that most of these individuals formed one cluster, with a few putative outliers obscuring population variation. An additional eigenanalysis on the same markers in a combined data set including the 2,504 individuals in the 1000 Genomes database found that most of the 157 Illinois individuals clustered into one group in close proximity to individuals of European descent. A final eigenanalysis of the Illinois individuals with the 503 individuals of European descent (within the 1000 Genomes Project) revealed two clusters of individuals and likely two source populations; one British and one consisting of multiple European subpopulations. We therefore demonstrate the feasibility of examining genetic relatedness across Illinois populations and assessing the number of source populations using publicly available databases. When assessed, population structure information can contribute to the understanding of genetic history in rural populations.

Intrastate Variations in Rural Cancer Risk and Incidence: An Illinois Case Study.

CONTEXT: Although rural-urban cancer disparities have been explored with some depth, disparities within seemingly homogeneous rural areas have received limited attention. However, exploration of intrarural cancer incidence may have important public health implications for risk assessment, cancer control, and resource allocation. OBJECTIVE: The objective of this study was to explore intrastate rural cancer risk and incidence differences within Illinois. DESIGN: Illinois's 83 rural counties were categorized into northern, central, and southern regions (IL-N, IL-C, and IL-S, respectively). Chi-square test for independence and analysis of variance calculations were performed to assess regional differences in demographic characteristics, socioeconomic deprivation, smoking history, obesity, cancer-screening adherence, and density of general practitioners. Age-adjusted incidence rates were calculated for 5 cancer categories: all cancers combined, lung, colorectal, breast (female), and prostate cancers. Unadjusted and adjusted incidence rate ratios (IRRs) were calculated to evaluate regional differences in rates for each cancer category. RESULTS: Socioeconomic deprivation varied by region: 4.5%, 6.9%, and 40.6% of IL-N, IL-C, and IL-S counties, respectively (P < .001). Smoking history also significantly differed by region. Mean former/current smoking prevalence in IL-N, IL-C, and IL-S counties was 46.4%, 48.2%, and 51.4%, respectively (P = .006). In unadjusted analysis, IL-C (IRR = 1.12; 95% confidence interval [CI], 1.02-1.23) and IL-S (IRR = 1.24; 95% CI, 1.13-1.35) had increased lung cancer incidence compared with IL-N. Elevated risk remained in IL-S after adjusting for relevant factors such as smoking and socioeconomic deprivation (IRR = 1.14; 95% CI, 1.04-1.26). CONCLUSIONS: Socioeconomic deprivation, health behaviors, and lung cancer incidence varied across rural regions. Our findings underscore the importance of identifying cancer risk heterogeneity, even within a state, to effectively target risk factor reduction and cancer control interventions.

Inflammation and psychosocial factors mediate exercise effects on sleep quality in breast cancer survivors: pilot randomized controlled trial.

OBJECTIVE: To improve mechanistic understanding, this pilot randomized controlled trial examined mediators of an exercise intervention effects on sleep in breast cancer survivors (BCS). METHODS: Forty-six postmenopausal BCS (≤Stage II, off primary treatment) were randomized to a 3-month exercise intervention or control group. Intervention included 160 min/week of moderate intensity aerobic walking, twice weekly resistance training (resistance bands), and six discussion groups (to improve adherence). Blinded assessments at baseline and post-intervention included sleep disturbance (PSQI and PROMIS®), objective sleep quality (accelerometer), serum cytokines, accelerometer physical activity, cardiorespiratory fitness, body composition, fatigue, and psychosocial factors. Mediation was tested using Freedman-Schatzkin difference-in-coefficients tests. RESULTS: When compared with control, the intervention group demonstrated a significant increase in PSQI sleep duration (i.e., fewer hours of sleep/night) (d = 0.73, p = .03). Medium to large but non-significant standardized effect sizes were noted for PSQI daytime somnolence (d = -0.63, p = .05) and accelerometer latency (d = -0.49, p = .14). No statistically significant mediators were detected for PSQI sleep duration score or accelerometer latency. Daytime somnolence was mediated by tumor necrosis factor-alpha (mediated 23% of intervention effect, p < .05), interleukin (IL)-6:IL-10 (16%, p < .01), IL-8:IL-10 (26%, p < .01), and fatigue (38%, p < .05). Mediating or enhancing relationships for several of the sleep outcomes were noted for accelerometer physical activity, PROMIS® fatigue, exercise social support, and/or physical activity enjoyment. CONCLUSIONS: Inflammation and psychosocial factors may mediate or enhance sleep response to our exercise intervention. Further study is warranted to confirm our results and translate our findings into more effective interventions aimed at improving sleep quality in BCS.

Refining Measurement of Social Cognitive Theory Factors Associated with Exercise Adherence in Head and Neck Cancer Patients.

Social cognitive theory (SCT) measures related to exercise adherence in head and neck cancer (HNCa) patients were developed. Enrolling 101 HNCa patients, psychometric properties and associations with exercise behavior were examined for barriers self-efficacy, perceived barriers interference, outcome expectations, enjoyment, and goal setting. Cronbach's alpha ranged from.84 to.95; only enjoyment demonstrated limited test-retest reliability. Subscales for barriers self-efficacy (motivational, physical health) and barriers interference (motivational, physical health, time, environment) were identified. Multiple SCT constructs were cross-sectional correlates and prospective predictors of exercise behavior. These measures can improve the application of the SCT to exercise adherence in HNCa patients.

Designing Policy Solutions to Build a Healthier Rural America.

Disparities exist in the health, livelihood, and opportunities for the 46-60 million people living in America's rural communities. Rural communities across the United States need a new energy and focus concentrated around health and health care that allows for the designing capturing, and spreading of existing and new innovations. This paper aims to provide a framework for policy solutions to build a healthier rural America describing both the current state of rural health policy and the policies and practices in states that could be used as a national model for positive change.

Rurality and Health in the United States: Do Our Measures and Methods Capture Our Intent?

Rural status in the United States can be objectively measured using multiple designations within different geographic extents, often considering both population density and proximity to urban areas. However, these measurements are often incomplete for assessing the relationship between rural status and health and are often inadequately considered in analysis. To address these limitations, we posit four recommendations: two recommendations to improve current measures by including additional factors and making measures continuous and two recommendations to improve regression analysis by considering rural status as a contextual factor in multilevel modeling and as a variable in conjunction with socioeconomic factors derived through principal component analysis.

Pediatric population health analysis of southern and central Illinois region: A cross sectional retrospective study using association rule mining and multiple logistic regression.

BACKGROUND: Southern Illinois University School of Medicine (SIUSOM) collects large amounts of data every day. SIUSOM and other similar healthcare systems are always looking for better ways to use the data to understand and address population level problems. The purpose of this study is to analyze the administrative dataset for pediatric patients served by Southern Illinois University School of Medicine (SIUSOM) to uncover patterns that correlate specific demographic information to diagnoses of pediatric diseases. The study uses a cross-sectional database of medical billing information for all pediatric patients served by SIUSOM between June 2013 and December 2016. The dataset consists of about 980.9K clinical visits for 65.4K unique patients and includes patient demographic identifiers such as their sex, date of birth, race, anonymous zipcode and primary and secondary insurance plan as well as the related pediatric diagnosis codes. The goal is to find unknown correlations in this database. METHOD: We proposed a two step methodology to derive unknown correlations in SIUSOM administrative database. First, Class association rule mining was used as a well-established data mining method to generate hypothesis and derive associations of the form D → M, where D is diagnosis code of a pediatric disease and M is a patient demographic identifier (age,sex, anonymous zipcode, insurance plan, or race). The resulting associations were pruned and filtered using measures such as lift, odds ratio, relative risk, and confidence. The final associations were selected by a pediatric doctor based on their clinical significance. Second,each association rule in the final set was further validated and adjusted odds ratios were obtained using multiple logistic regression. RESULTS: Several associations were found correlating specific patients' residential zip codes with the diagnosis codes for viral hepatitis carrier, exposure to communicable diseases, screening for mental and developmental disorder in childhood, history allergy to medications, disturbance of emotions specific to childhood, and acute sinusitis. In addition, the results show that African American patients are more likely to be screened for mental and developmental disorders compared to White patients for SIUSOM pediatric population (Odds Ratio (OR):3.56, 95% Confidence Interval (CI):[3.29,3.85]). CONCLUSION: Class association rule mining is an effective method for detecting signals in a large patient administrative database and generating hypotheses which correlate patients' demographics with diagnosis of pediatric diseases. A post processing of the hypotheses generated by this method is necessary to prune spurious associations and select a set of clinically relevant hypotheses.

Rural-Urban Disparities in Stage of Diagnosis Among Cancers With Preventive Opportunities.

INTRODUCTION: Despite having lower overall incidence rates, rural populations tend to have higher cancer mortality rates. Rural populations often have higher rates of cancers with primary and secondary prevention modalities. However, there is limited research on rural-urban differences in incidence by stage. Therefore, the objective was to assess rural-urban differences in cancer rates by stage. METHODS: The North American Association of Central Cancer Registries public use data set (2009-2013) was used to calculate age-adjusted incidence rates and rate ratios (rural versus urban) for all stageable cancers, tobacco-associated cancers, human papillomavirus-associated cancers, and individual cancers with screening modalities. Analyses were performed in summer 2017 for all populations and stratified by race/ethnicity and region for localized and distant stages. RESULTS: For all cancers, rural populations had lower rates of localized stage cancers (rate ratio=0.95, 95% CI=0.95, 0.95) and higher rates of distant stage cancer (rate ratio=1.05, 95% CI=1.05, 1.06). Higher rates of distant stage human papillomavirus-associated, tobacco-associated, colorectal, oropharyngeal, lung, cervical cancers, and melanoma were identified in rural populations. Racial/ethnic stratifications identified higher rates of distant stage cancers in rural non-Hispanic whites, but not non-Hispanic blacks and Hispanics. Distant stage lung cancer rates were higher in all rural groups, whereas rural whites had higher distant rates of tobacco-associated, colorectal, and cervical cancers, and rural blacks had higher distant rates for human papillomavirus-associated and oral cancers. Regional stratifications showed the greatest disparity in stage at diagnosis in the South. CONCLUSIONS: These findings might help explain the higher rural cancer mortality rates and provide additional evidence to support targeted interventions.

Rural-Urban Differences in Cancer Incidence and Trends in the United States.

Background: Cancer incidence and mortality rates in the United States are declining, but this decrease may not be observed in rural areas where residents are more likely to live in poverty, smoke, and forego cancer screening. However, there is limited research exploring national rural-urban differences in cancer incidence and trends.Methods: We analyzed data from the North American Association of Central Cancer Registries' public use dataset, which includes population-based cancer incidence data from 46 states. We calculated age-adjusted incidence rates, rate ratios, and annual percentage change (APC) for: all cancers combined, selected individual cancers, and cancers associated with tobacco use and human papillomavirus (HPV). Rural-urban comparisons were made by demographic, geographic, and socioeconomic characteristics for 2009 to 2013. Trends were analyzed for 1995 to 2013.Results: Combined cancers incidence rates were generally higher in urban populations, except for the South, although the urban decline in incidence rate was greater than in rural populations (10.2% vs. 4.8%, respectively). Rural cancer disparities included higher rates of tobacco-associated, HPV-associated, lung and bronchus, cervical, and colorectal cancers across most population groups. Furthermore, HPV-associated cancer incidence rates increased in rural areas (APC = 0.724, P < 0.05), while temporal trends remained stable in urban areas.Conclusions: Cancer rates associated with modifiable risks-tobacco, HPV, and some preventive screening modalities (e.g., colorectal and cervical cancers)-were higher in rural compared with urban populations.Impact: Population-based, clinical, and/or policy strategies and interventions that address these modifiable risk factors could help reduce cancer disparities experienced in rural populations. Cancer Epidemiol Biomarkers Prev; 27(11); 1265-74. ©2017 AACR.

Utility and Generalizability of Multistate, Population-Based Cancer Registry Data for Rural Cancer Surveillance Research in the United States.

More than 46 million Americans live in rural areas, but rural populations remain relatively understudied in cancer disparities research. However, several analyses of multistate cancer registry data that describe the rural cancer incidence burden have been recently published. In light of this, our article aims to characterize the utility and generalizability of multistate, population-based cancer registry datasets for rural cancer surveillance research. First, we describe the accessibility, geographic coverage, available variables, and strengths and weaknesses of five data sources. Second, we evaluate two of these data sources-the North American Association of Central Cancer Registries (NAACCR) public use dataset (93% population coverage) and the Surveillance Epidemiology and End Results (SEER) 18 dataset (28% population coverage)-on their characterization of rural-urban cancer incidence rates and sociodemographic representation. The five data sources varied in geographic coverage and extent of available variables. SEER 18's cancer rates sociodemographic representation differed from the more geographically representative NAACCR data. We suggest that SEER increase its geographic coverage to improve their generalizability and to take advantage of their utility to assess disparities along the cancer control continuum. We also suggest that non-SEER data sources be utilized more frequently to capitalize on their extensive geographic coverage. Cancer Epidemiol Biomarkers Prev; 27(11); 1252-60. ©2018 AACR.

Engaging rural communities in genetic research: challenges and opportunities.

Statistical analyses of health and disease in rural communities is frequently limited by low sample counts. Still, some studies indicate increased risk for some diseases even after adjustment for known risk factors. It has been hypothesized that the context of community formation in rural areas facilitates the propagation of genetic founder effects-potentially impacting disease susceptibility. However, outright examination of genetic diversity in such communities has not been performed. Our objective was to engage otherwise research-inexperienced rural communities of largely European descent in genomic research in the context of cancer susceptibility. From September 2015 to February 2016, we implemented a systematic process of progressive community engagement. This iterative method sought project buy-in from first the town mayor, then village council. If approved by both, a focus group of community members examined how residents might view the research, informed consent and specimen collection, and issues of privacy. We were successful in engaging three of the four communities approached for the research project. There was universal enthusiasm for the project by all mayors and village councils. The focus groups' main point of discussion involved wording in the informed consent, with little concern regarding the research question or privacy. Perhaps contrary to popular thought, we found each community we approached to be both welcoming and enthusiastic about collaborating in research on genomic diversity. The systematic method of engagement did much to preserve community respect and autonomy and facilitated buy-in.

E-cigarettes: Who's using them and why?

Background: Electronic cigarettes (e-cigarettes) are often marketed as safe and effective aids for quitting cigarette smoking, but concerns remain that use of e-cigarettes might actually reduce the number of quit attempts. To address these issues, we characterized the utilization and demographic correlates of dual use of e-cigarettes and traditional cigarettes (referred to here as simply "cigarettes") among smokers in a rural population of Illinois. Methods: The majority of survey participants were recruited from the 2014 Illinois State Fair and from another event­the Springfield Mile (a motorcycle racing event)­in Springfield, Ill. Survey questions explored participant demographics and cigarette and e-cigarette use history. Results: Of 201 total cigarette smokers, 79 smoked only tobacco cigarettes (smokers), while 122 also used e-cigarettes (dual users). Dual users did not differ significantly from smokers in gender, age, income, or education. Compared to smokers, dual users were more likely to smoke within 30 minutes of awakening (odds ratio [OR]=3.3; 95% confidence interval [CI], 1.8-6.3), but did not smoke more cigarettes per day or perceive a greater likelihood of quit success. Non-white dual users smoked fewer cigarettes per day than smokers . In addition, 79.5% of all dual users reported that they were using e-cigarettes to quit smoking or reduce the number of cigarettes smoked, and white respondents were 6 times more likely than non-whites to use e-cigarettes for 'trying to quit smoking' (OR=6.0; 95% CI, 1.1-32.9). Males and respondents with lower income were less likely to say they were using e-cigarettes to reduce the number of cigarettes smoked than females or participants with higher income (OR=0.2; 95% CI, 0.1-0.8 and OR=0.1; 95% CI, 0.0-0.5, respectively). Conclusions: E-cigarettes may significantly alter the landscape of nicotine physical dependence, and local influences likely are associated with use patterns. Future research should continue to examine whether dual use of traditional and electronic cigarettes impacts smoking cessation, and clinicians should be aware that local norms may create differences from national level data.

Does where you live play an important role in cancer incidence in the U.S.?

Some studies have shown disproportionate cancer incidence burden in rural areas which may be attributable partly due to the use of 'rural' as a generic term implying homogeneity of risk/protective factors across wide geographic spans. Counties in SEER 18 registries (years 2001-2011) were classified by their Rural-Urban Continuum Code (RUCC) and aggregated into urban, adjacent rural, and non-adjacent rural and were also aggregated into 3 regions: North, South, and West. Two-way ANCOVA was performed with region and RUCC as factors with adjustment for rates of common risk factors obtained from the County Health Rankings (2013). RUCC has a significant effect on incidence rate in urban areas on breast (P =0.001) and prostate (P =0.009). Colorectal significantly varies by region (P<0.0001), and the effect of rurality significantly varies across regions with North highest (P=0.0005). Lung rates significantly vary across both region and RUCC (P<0.0001 and P=0.0001, respectively). The analysis shows that risk-adjusted cancer incidence varies significantly across regions. However, we also found that rural cancer incidence significantly varied across otherwise-similar rural areas implying that 'rural' is not a homogeneous classification.

Biobehavioral factors mediate exercise effects on fatigue in breast cancer survivors.

PURPOSE: This study aimed to examine mediators of fatigue response to an exercise intervention for breast cancer survivors in a pilot randomized controlled trial. METHODS: Postmenopausal breast cancer survivors (n = 46; ≤stage 2), off primary treatment, and reporting fatigue and/or sleep dysfunction were randomized to a 3-month exercise intervention (160 min·wk of moderate-intensity aerobic walking, twice weekly resistance training with resistance bands) or control group. Six discussion group sessions provided behavioral support to improve adherence. Fatigue, serum cytokines, accelerometer physical activity, cardiorespiratory fitness, sleep dysfunction, and psychosocial factors were assessed at baseline and 3 months. RESULTS: The exercise intervention effect sizes for fatigue were as follows: fatigue intensity d = 0.30 (P = 0.34), interference d = -0.38 (P = 0.22), and general fatigue d = -0.49 (P = 0.13). Using the Freedman-Schatzkin difference-in-coefficients tests, increase in fatigue intensity was significantly mediated by interleukin 6 (IL-6) (82%), IL-10 (94%), IL-6/IL-10 (49%), and tumor necrosis factor-α (TNF-α):IL-10 (78%) with reduced sleep dysfunction increasing the relationship between intervention and fatigue intensity rather than mediating intervention effects (-88%). Decrease in fatigue interference was mediated by sleep dysfunction (35%), whereas IL-10 and pro-anti-inflammatory cytokine ratios increased the relationship between intervention and interference (-25% to -40%). The reduction in general fatigue was significantly mediated by minutes of physical activity (76%), sleep dysfunction (45%), and physical activity enjoyment (40%), with IL-10 (-40%) and IL-6/IL-10 (-11%) increasing the intervention-fatigue relationship. In the intervention group, higher baseline fatigue, anxiety, depression, and perceived exercise barrier interference predicted a greater decline in fatigue interference and/or general fatigue during the intervention. CONCLUSIONS: Biobehavioral factors mediated and enhanced intervention effects on fatigue, whereas psychosocial factors predicted fatigue response. Further study is warranted to confirm our results and to improve understanding of relationships that mediate and strengthen the intervention-fatigue association.

Effects of a physical activity behavior change intervention on inflammation and related health outcomes in breast cancer survivors: pilot randomized trial.

BACKGROUND: The goal of this pilot study was to determine the magnitude and direction of intervention effect sizes for inflammatory-related serum markers and relevant health outcomes among breast cancer survivors (BCSs) receiving a physical activity behavior change intervention compared with usual care. METHODS: This randomized controlled trial enrolled 28 stage I, II, or IIIA BCSs who were post-primary treatment and not regular exercisers. Participants were assigned to either a 3-month physical activity behavior change intervention group (ING) or usual care group (UCG). Intervention included supervised aerobic (150 weekly minutes, moderate-intensity) and resistance (2 sessions per week) exercise that gradually shifted to home-based exercise. Outcomes were assessed at baseline and 3 months. RESULTS: Cardiorespiratory fitness significantly improved in the ING versus the UCG (between-group difference = 3.8 mL/kg/min; d = 1.1; P = .015). Self-reported sleep latency was significantly reduced in the ING versus the UCG (between group difference = -0.5; d = -1.2; P = .02) as was serum leptin (between-group difference = -9.0 ng/mL; d = -1.0; P = .031). Small to medium nonsignificant negative effect sizes were noted for interleukin (IL)-10 and tumor necrosis factor (TNF)-α and ratios of IL-6 to IL-10, IL-8 to IL-10, and TNF-α to IL-10, whereas nonsignificant positive effect sizes were noted for IL-6 and high-molecular-weight adiponectin. CONCLUSIONS: Physical activity behavior change interventions in BCSs can achieve large effect size changes for several health outcomes. Although effect sizes for inflammatory markers were often small and not significant, changes were in the hypothesized direction for all except IL-6 and IL-10.

Pilot, randomized trial of resistance exercise during radiation therapy for head and neck cancer.

BACKGROUND: The purpose of this study was to determine the feasibility of a randomized trial of resistance exercise in patients with head and neck cancer receiving radiation. METHODS: Fifteen patients with head and neck cancer receiving radiation were randomized to resistance exercise (using resistance bands) or control group. Resistance exercise occurred at the radiation therapy site (weeks 1-6) and home (weeks 7-12). RESULTS: No serious adverse events occurred related to resistance exercise. Medium to large effect size differences favoring resistance exercise versus control group were noted for perceived fatigue at 6 weeks (smaller increase in fatigue for resistance exercise group; 7.4 vs 15.4, effect size [d] = -0.64), quality of life at 6 weeks (-7.0 vs -14.4, d = 0.52), and chair rise time (seconds) at 6 and 12 weeks (-1.6 vs 0.4, d = -.63 and -1.9 vs 0.1, d = -0.60, respectively). CONCLUSIONS: Resistance exercise is safe and feasible in patients with head and neck cancer receiving radiation; a definitive trial is warranted.

Exercise preferences among patients with head and neck cancer: prevalence and associations with quality of life, symptom severity, depression, and rural residence.

BACKGROUND: Our aim was to determine exercise preferences among patients with head and neck cancer and their associations with quality of life, symptom severity, depression, and rural residence. METHODS: This study involved a cross-sectional chart review and self-administered survey, with 90 outpatients with head and neck cancer (response rate = 83%). RESULTS: The majority were <65 years old (65%), male (78%), and white (96%) with stage > or = III (81%). Lack of preference was the most frequent option for counseling source (66%), counseling delivery (47%), and exercise variability (52%). Popular specific preferences included outdoors (49%), morning (47%), and alone (50%). Significant adjusted associations occurred for patients' interest with lower functional well-being, alone with higher functional well-being, and morning with higher total quality of life and emotional, social, and functional well-being. No significant associations occurred with symptoms, depression, or rural residence. CONCLUSION: Patients with head and neck cancer may be open to a variety of exercise options. Quality of life may influence interest and preference for exercising alone or in the morning.