Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S.

This study assessed food choice priorities (FCP) and associations with consumption of fruits and vegetables (FV), fiber, added sugars from non-beverage sources, and sugar-sweetened beverages (SSB) among college students. Freshmen from eight U.S. universities (N = 1149) completed the Food Choice Priorities Survey, designed for college students to provide a way to determine the factors of greatest importance regarding food choices, and the NCI Dietary Screener Questionnaire. Changes in FCP and dietary intake from fall 2015 to spring 2016 were assessed. Multiple regression models examined associations between FCP and log-transformed dietary intake, controlling for sex, age, race, and BMI. Participant characteristics and FCP associations were also assessed. FCP importance changed across the freshmen year and significantly predicted dietary intake. The most important FCP were price, busy daily life and preferences, and healthy aesthetic. Students who endorsed healthy aesthetic factors (health, effect on physical appearance, freshness/quality/in season) as important for food choice, consumed more FV and fiber and less added sugar and SSB. Busy daily life and preferences (taste, convenience, routine, ability to feel full) predicted lower FV, higher added sugar, and higher SSB consumption. Price predicted lower FV, higher SSB, and more added sugar while the advertising environment was positively associated with SSB intake. FCP and demographic factors explained between 2%–17% of the variance in dietary intake across models. The strongest relationship was between healthy aesthetic factors and SSB (B = −0.37, p \u3c 0.01). Self-rated importance of factors influencing food choice are related to dietary intake among students. Interventions that shift identified FCP may positively impact students’ diet quality especially considering that some FCP increase in importance across the first year of college

Redesign, Field-Testing, and Validation of the Physical Activity Campus Environmental Supports (PACES) Audit.

This paper describes the redesign, field-testing, and convergent validity of a practical tool-Physical Activity Campus Environmental Supports (PACES) audit. Methods. The audit includes two parts: (1) PACES-Programs, which is comprised of questions regarding populations served, fees, programs (recreation/fitness classes and intramurals), proximity, adequacy of facilities, and marketing, and (2) PACES-Facilities, which is comprised of questions regarding built environment (aesthetics, bike racks, stairs, and universal design), recreation equipment, staff, amenities, and access. Each item criterion is specifically scored using a five-point, semantic-differential scale ranging from limited to extensive environmental support. A few questions utilize select all that apply for a summed score. PACES training, interrater reliability, and data collection are all accessible via an online portal. PACES was tested on 76 college campuses. Convergent validity was examined by comparing the PACES-Programs questions to Healthy Campus Initiatives-Programs questions (HCI-Programs) and comparing the PACES-Facilities questions to questions contained in the Physical Activity Resource Assessment (PARA) Instrument. Statistical analyses included Cronbach\u27s alpha, ANOVA, latent profile analysis, and Spearman correlations. Results.The PACES-Programs audit includes 10 items for a potential total of 73 points (α = 0.72) and PACES-Facilities audit includes 15 items for a potential total of 77 points (α = 0.837). Most (77.8%) of the 153 facilities assessed scored in the most healthful range (20-42), which was mainly due to the extensiveness of the aerobic equipment/amenities and the competence/accessibility of staff. Significant differences in PACES-Total and PACES-Programs scores were associated with campus size and PACES-Facilities across regions. For the paired validation assessments, correlations were significant between PACES-Programs and HCI-Programs ((n=41) r=0.498, p \u3c 0.001) and PACES-Facilities and PARA (n=29) for both features (r=0.417, p=0.024) and amenities (r=0.612, p \u3c 0.001), indicating moderate convergent validity. Conclusion. The PACES audit is a valid, reliable tool for assessing the quality of recreation facilities and programs in a variety of college campus environments

Uncertainty in United States coastal wetland greenhouse gas inventorying

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Research Letters 13 (2018): 115005, doi:10.1088/1748-9326/aae157.Coastal wetlands store carbon dioxide (CO2) and emit CO2 and methane (CH4) making them an important part of greenhouse gas (GHG) inventorying. In the contiguous United States (CONUS), a coastal wetland inventory was recently calculated by combining maps of wetland type and change with soil, biomass, and CH4 flux data from a literature review. We assess uncertainty in this developing carbon monitoring system to quantify confidence in the inventory process itself and to prioritize future research. We provide a value-added analysis by defining types and scales of uncertainty for assumptions, burial and emissions datasets, and wetland maps, simulating 10 000 iterations of a simplified version of the inventory, and performing a sensitivity analysis. Coastal wetlands were likely a source of net-CO2-equivalent (CO2e) emissions from 2006–2011. Although stable estuarine wetlands were likely a CO2e sink, this effect was counteracted by catastrophic soil losses in the Gulf Coast, and CH4 emissions from tidal freshwater wetlands. The direction and magnitude of total CONUS CO2e flux were most sensitive to uncertainty in emissions and burial data, and assumptions about how to calculate the inventory. Critical data uncertainties included CH4 emissions for stable freshwater wetlands and carbon burial rates for all coastal wetlands. Critical assumptions included the average depth of soil affected by erosion events, the method used to convert CH4 fluxes to CO2e, and the fraction of carbon lost to the atmosphere following an erosion event. The inventory was relatively insensitive to mapping uncertainties. Future versions could be improved by collecting additional data, especially the depth affected by loss events, and by better mapping salinity and inundation gradients relevant to key GHG fluxes. Social Media Abstract: US coastal wetlands were a recent and uncertain source of greenhouse gasses because of CH4 and erosion.Financial support was provided primarily by NASA Carbon Monitoring Systems (NNH14AY67I) and the USGS Land Carbon Program, with additional support from The Smithsonian Institution, The Coastal Carbon Research Coordination Network (DEB-1655622), and NOAA Grant: NA16NMF4630103

Development and Validation of the Vending Evaluation for Nutrient-Density (VEND)ing Audit

Background: This paper describes the development and validation of the Vending Evaluation for Nutrient-Density (VEND)ing audit to comprehensively evaluate vended products based upon healthfulness, price and promotion, and machine accessibility. Methods: A novel vending nutrient-density score was created to determine the healthfulness of vended snack/beverage products. Field tested in United States colleges, VENDing audit (Σnutrient-density + 10 x % healthy products) and Support sub-scores (price + promotion + accessibility) were calculated for snack/beverage machines. Higher scores indicate more healthful vending options and supports for choosing healthfully. Nutrition Environment Measures Survey-Vending (NEMS-V) was used to validate the nutrient-density score for a sub-sample of machines. Sensitivity and specificity were computed by comparing the number of healthy snacks/beverages determined by NEMS-V and the VENDing nutrient-density scores. Results: Researchers conducted the VENDing audit on 228 snack/beverage vending machines at 9 universities within the United States and used both VENDing and NEMS-V on 33 snack and 52 beverage vending machines. Mean VENDing audit scores were 4.5 ± 2.0 (2.6, 3.4) and 2.6 ± 2.0 (0, 12) for snack/beverage machines, respectively. The number of products considered healthy assessed with both the VENDing nutrient-density scores and the NEMS-V were positively correlated for beverages (r = 0.687, p \u3c 0.001) and snacks (r = 0.366, p \u3c 0.05). The sensitivity was excellent for beverages (0.83) and moderate for snacks (0.69); while the specificity was moderate for both beverages (0.66) and snacks (0.50). Conclusions: The VENDing audit uses unique, valid, an

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

<p>Abstract</p> <p>Background</p> <p>Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgV_H) mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgV_H status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgV_H mutational status which can accurately predict the survival outcome are yet to be discovered.</p> <p>Results</p> <p>In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO) and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgV_H mutation status from the ZAP70 co-expression network.</p> <p>Conclusions</p> <p>We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgV_H mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.</p

Creative destruction in science

Drawing on the concept of a gale of creative destruction in a capitalistic economy, we argue that initiatives to assess the robustness of findings in the organizational literature should aim to simultaneously test competing ideas operating in the same theoretical space. In other words, replication efforts should seek not just to support or question the original findings, but also to replace them with revised, stronger theories with greater explanatory power. Achieving this will typically require adding new measures, conditions, and subject populations to research designs, in order to carry out conceptual tests of multiple theories in addition to directly replicating the original findings. To illustrate the value of the creative destruction approach for theory pruning in organizational scholarship, we describe recent replication initiatives re-examining culture and work morality, working parents\u2019 reasoning about day care options, and gender discrimination in hiring decisions. Significance statement It is becoming increasingly clear that many, if not most, published research findings across scientific fields are not readily replicable when the same method is repeated. Although extremely valuable, failed replications risk leaving a theoretical void\u2014 reducing confidence the original theoretical prediction is true, but not replacing it with positive evidence in favor of an alternative theory. We introduce the creative destruction approach to replication, which combines theory pruning methods from the field of management with emerging best practices from the open science movement, with the aim of making replications as generative as possible. In effect, we advocate for a Replication 2.0 movement in which the goal shifts from checking on the reliability of past findings to actively engaging in competitive theory testing and theory building. Scientific transparency statement The materials, code, and data for this article are posted publicly on the Open Science Framework, with links provided in the article