Impervious surface area (ISA)

BackgroundImproving cardiovascular health (CVH) of all Americans by 2020 is a strategic goal of the American Heart Association. Understanding the sources of variation and identifying contextual factors associated with poor CVH may suggest important avenues for prevention.Methods and ResultsCross-sectional data from the Behavioral Risk Factor Surveillance System for the year 2011 were linked to state-level coronary heart disease and stroke mortality data from the National Vital Statistics System and to state-level measures of median household income, income inequality, taxes on soda drinks and cigarettes, and food and physical activity environments from various administrative sources. Poor CVH was defined according to the American Heart Association definition using 7 self-reported CVH metrics (current smoking, physical inactivity, obesity, poor diet, hypertension, diabetes, and high cholesterol). Linked micromap plots and multilevel logistic models were used to examine state variation in poor CVH and to investigate the contributions of individual- and state-level factors to this variation. We found significant state-level variation in the prevalence of poor CVH (median odds ratio 1.32, P<0.001). Higher rates of poor CVH and cardiovascular disease mortality were clustered in the southern states. Minority and low socioeconomic groups were strongly associated with poor CVH and explained 51% of the state-level variation in poor CVH; state-level factors explained an additional 28%. State-level median household income (odds ratio 0.89; 95% CI 0.84–0.94), taxes on soda drinks (odds ratio 0.94; 95% CI 0.89–0.99), farmers markets (odds ratio 0.91; 95% CI 0.85–0.98), and convenience stores (odds ratio 1.09; 95% CI 1.01–1.17) were predictive of poor CVH even after accounting for individual-level factors.ConclusionsThere is significant state-level variation in poor CVH that is partly explained by individual- and state-level factors. Additional longitudinal research is warranted to examine the influence of state-level policies and food and physical activity environments on poor CVH.

Current research shows that digital games can significantly enhance children's learning. The purpose of this study was to examine how design features in 12 digital math games influenced children's learning. The participants in this study were 193 children in Grades 2 through 6 (ages 8-12). During clinical interviews, children in the study completed pre-tests, interacted with digital math games, responded to questions about the digital math games, and completed posttests. We recorded the interactions using two video perspectives that recorded children's gameplay and responses to interviewers. We employed mixed methods to analyze the data and identify salient patterns in children's experiences with the digital math games. The analysis revealed significant gains for 9 of the 12 digital games and most children were aware of the design features in the games. There were eight prominent categories of design features in the video data that supported learning and mathematics connections. Six categories focused on how the design features supported learning in the digital games. These categories included: accuracy feedback, unlimited/multiple attempts, information tutorials and hints, focused constraint, progressive levels, and game efficiency. Two categories were more specific to embodied cognition and action with the mathematics, and focused on how design features promoted mathematics connections. These categories included: linked representations and linked physical actions. The digital games in this study that did not include linked representations and opportunities for linked physical actions as design features did not produce significant gains. These results suggest the key role of mathematics-specific design features in the design of digital math games. Highlights  Children made significant learning gains when using 9 of the 12 digital math games  Children's awareness of the mathematics in digital math games impacted learning  Eight categories of game design features supported children's learning  Learning gains were tied to design features that linked representations to the mathematics  Learning gains were tied to design features that linked physical actions to the mathematics

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Introduction: The purpose of this study was to evaluate the inter-rater reliability of hand

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures.

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LM plots are effective in representing complex and large volume birth defects data. Integration to birth defects surveillance systems will improve both presentation and interpretation.