Introduction In 2014, the National Cancer Institute conducted the Family Life, Activity, Sun, Health, and Eating Study (FLASHE). This parent and adolescent survey examines psychosocial, generational (parent–adolescent), and environmental (home and neighborhood) correlates of cancer-preventive behaviors, with a particular emphasis on diet and physical activity. This paper describes the FLASHE data collection methods and enrollment and response rates. Methods FLASHE data collection methods included web-based surveys delivered to dyads of parents and their adolescent children, and deployment of accelerometers to a subset of adolescents, to achieve study goals in a nationwide study sample. The National Cancer Institute contracted with Westat, Inc. to recruit, enroll, and collect the data using a consumer opinion panel. Results A total of 5,027 dyads were screened for eligibility, and 1,945 (38.7%) enrolled. Of fully enrolled dyads, 85.6% of those in the Survey-Only group completed all four surveys, and 58.7% of dyads in the Motion Study group completed all surveys and were compliant with the accelerometer protocol for adolescents. The overall study response rate was 29.4%; 1,479 dyads completed all study procedures. The majority of parents were female, whereas the adolescent sample was gender balanced. Data were analyzed in 2015–2016. Conclusions FLASHE recruited a large sample of parent–adolescent dyads. Although challenges for research in parent–adolescent dyads include enrolling a diverse sample and having multistep enrollment and consent processes, study completion rate was high among fully enrolled dyads. Future panel studies may consider approaches used in FLASHE to encourage study enrollment and completion.

Aims Alcohol intake has been shown to increase the risk of breast cancer. However, the dose-response analysis of different alcoholic beverages (spirits, wine and beer) is not clear. Our meta-analysis aims to provide a dose-response estimation between different alcohols and breast cancer risk. Methods Search of PubMed and Web of Science and manual searches were conducted up to 1 December 2018, and summary relative risks (RRs) and attributable risk percentage (ARP) for alcohol intake on the development of breast cancer were calculated. Dose-response meta-analysis modeled relationships between drinking type and breast cancer risk. Sources of heterogeneity were explored, and sensitivity analyses were conducted to test the robustness of findings. Results In total, 22 cohort studies and 45,350 breast cancer cases were included. Current drinkers for ER+ had an increased risk compared with never drinkers. In dose-response analysis, there was a statistically significant linear trend with breast cancer risk increasing gradually by total alcohol and wine dose: when adding 10 g per day, the risk increased by 10.5% (RR = 1.10, 95%CI = 1.08–1.13) in total alcohol and 8.9% (RR = 1.08, 95%CI = 1.04–1.14) in wine. For postmenopausal women, the risk increases by 11.1% (RR = 1.11, 95%CI = 1.09–1.13) with every 10 g of total alcohol increase. Furthermore, the breast cancer alcohol-attributed percentage is higher in Europe than in North America and Asia. Conclusions The effect of drinking on the incidence of breast cancer is mainly manifested in ER+ breast cancer. Quantitative analysis showed total drinking had a significant risk for breast cancer, especially for postmenopausal women. However, for different alcohols, just wine intake has the similar results.

Background The Health Resources and Services Administration (HRSA), an agency within the U.S. Department of Health and Human Services (HHS), works to ensure accessible, quality, health care for the nation's underserved populations, especially those who are medically, economically, or geographically vulnerable. HRSA-designated primary care Health Professional Shortage Areas (pcHPSAs) provide a vital measure by which to identify underserved populations and prioritize locations and populations lacking access to adequate primary and preventive health care-the foundation for advancing health equity and maintaining health and wellness for individuals and populations. However, access to care is a complex, multifactorial issue that involves more than just the number of health care providers available, and pcHPSAs alone cannot fully characterize the distribution of medically, economically, and geographically vulnerable populations. Methods and findings In this county-level analysis, we used descriptive statistics and multiple correspondence analysis to assess how HRSA's pcHPSA designations align geographically with other established markers of medical, economic, and geographic vulnerability. Reflecting recognized social determinants of health (SDOH), markers included demographic characteristics, race and ethnicity, rates of low birth weight births, median household income, poverty, educational attainment, and rurality. Nationally, 96 percent of U.S. counties were either classified as whole county or partial county pcHPSAs or had one or more established markers of medical, economic, or geographic vulnerability in 2017, suggesting that at-risk populations were nearly ubiquitous throughout the nation. Primary care HPSA counties in HHS Regions 4 and 6 (largely lying within the southeastern and south central United States) had the most pervasive and complex patterns in population risk.

Serum autoantibodies that react with tumor-associated antigens (TAAs) can be used as potential biomarkers for diagnosis of cancer. This study aims to evaluate the immunodiagnostic value of 11 anti-TAAs autoantibodies for detection of breast cancer (BC) and establish a diagnostic model for distinguishing BC from normal human controls (NHC) and benign breast diseases (BBD). Sera from 10 BC patients and 10 NHC were used to detect 11 anti-TAAs autoantibodies by western blotting. The 11 anti-TAAs autoantibodies were further assessed in 983 sera by relative quantitative enzyme-linked immunosorbent assay (ELISA). Binary logistic regression and Fisher linear discriminant analysis were conducted to establish a prediction model by using 184 BC and 184 NHC (training cohort, n = 568) and validated by leave-one-out cross-validation. Logistic regression model was selected to establish the prediction model. Results were validated using an independent validation cohort (n = 415). The five anti-TAAs (p53, cyclinB1, p16, p62, 14-3-3ξ) autoantibodies were selected to construct the model with the area under the curve (AUC) of 0.943 (95% CI, 0.919-0.967) in training cohort and 0.916 (95% CI, 0.886-0.947) in the validation cohort. In the identification of BC and BBD, AUCs were 0.881 (95% CI, 0.848-0.914) and 0.849 (95% CI, 0.803-0.894) in training and validation cohort, respectively. In summary, our study indicates that the immunodiagnostic model can distinguish BC from NHC and BC from BBD and this model may have a potential application in immunodiagnosis of breast cancer.

The authors used data from a large, national sample to examine the interaction of various literacy measures among young children with disabilities. Using structural equation modeling, they examined the relationships among measures of phonemic awareness, decoding, vocabulary, and reading comprehension. Child and family factors, including sex, severity of disability, race/ethnicity, household income, and mother's education were used as covariates. The model supported the notion of 2 unique paths to reading comprehension, one through decoding and a second through vocabulary.