A randomized trial in a massive online open course shows people don't know what a statistically significant relationship looks like, but they can learn

Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to statistically justify relationships identified between variables. Here we measure the ability to detect statistically significant relationships from scatterplots in a randomized trial of 2,039 students in a statistics massive open online course (MOOC). Each subject was shown a random set of scatterplots and asked to visually determine if the underlying relationships were statistically significant at the P < 0.05 level. Subjects correctly classified only 47.4% (95% CI: 45.1%-49.7%) of statistically significant relationships, and 74.6% (95% CI: 72.5%-76.6%) of non-significant relationships. Adding visual aids such as a best fit line or scatterplot smooth increased the probability a relationship was called significant, regardless of whether the relationship was actually significant. Classification of statistically significant relationships improved on repeat attempts of the survey, although classification of non-significant relationships did not. Our results suggest: (1) that evidence-based data analysis can be used to identify weaknesses in theoretical procedures in the hands of average users, (2) data analysts can be trained to improve detection of statistically significant results with practice, but (3) data analysts have incorrect intuition about what statistically significant relationships look like, particularly for small effects. We have built a web tool for people to compare scatterplots with their corresponding p-values which is available here: http://glimmer.rstudio.com/afisher/EDA/.Comment: 7 pages, including 2 figures and 1 tabl

Short-term Exposure to Particulate Matter Constituents and Mortality in a National Study of U.S. Urban Communities

Background: Although the association between PM2.5 mass and mortality has been extensively studied, few national-level analyses have estimated mortality effects of PM2.5 chemical constituents. Epidemiologic studies have reported that estimated effects of PM2.5 on mortality vary spatially and seasonally. We hypothesized that associations between PM2.5 constituents and mortality would not vary spatially or seasonally if variation in chemical composition contributes to variation in estimated PM2.5 mortality effects. Objectives: We aimed to provide the first national, season-specific, and region-specific associations between mortality and PM2.5 constituents. Methods: We estimated short-term associations between nonaccidental mortality and PM2.5 constituents across 72 urban U.S. communities from 2000 to 2005. Using U.S. Environmental Protection Agency (EPA) Chemical Speciation Network data, we analyzed seven constituents that together compose 79–85% of PM2.5 mass: organic carbon matter (OCM), elemental carbon (EC), silicon, sodium ion, nitrate, ammonium, and sulfate. We applied Poisson time-series regression models, controlling for time and weather, to estimate mortality effects. Results: Interquartile range increases in OCM, EC, silicon, and sodium ion were associated with estimated increases in mortality of 0.39% [95% posterior interval (PI): 0.08, 0.70%], 0.22% (95% PI: 0.00, 0.44), 0.17% (95% PI: 0.03, 0.30), and 0.16% (95% PI: 0.00, 0.32), respectively, based on single-pollutant models. We did not find evidence that associations between mortality and PM2.5 or PM2.5 constituents differed by season or region. Conclusions: Our findings indicate that some constituents of PM2.5 may be more toxic than others and, therefore, regulating PM total mass alone may not be sufficient to protect human health. Citation: Krall JR, Anderson GB, Dominici F, Bell ML, Peng RD. 2013. Short-term exposure to particulate matter constituents and mortality in a national study of U.S. urban communities. Environ Health Perspect 121:1148–1153; http://dx.doi.org/10.1289/ehp.120618

Heat-Related Mortality in a Warming Climate: Projections for 12 U.S. Cities

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience

The Impact of Heat Waves on Mortality in Seven Major Cities in Korea

Background: Understanding the health impacts of heat waves is important, especially given anticipated increases in the frequency, duration, and intensity of heat waves due to climate change

Combined Effects of Acute Temperature Change and Elevated pCO2 on the Metabolic Rates and Hypoxia Tolerances of Clearnose Skate (Rostaraja eglanteria), Summer Flounder (Paralichthys dentatus), and Thorny Skate (Amblyraja radiata)

Understanding how rising temperatures, ocean acidification, and hypoxia affect the performance of coastal fishes is essential to predicting species-specific responses to climate change. Although a population’s habitat influences physiological performance, little work has explicitly examined the multi-stressor responses of species from habitats differing in natural variability. Here, clearnose skate (Rostaraja eglanteria) and summer flounder (Paralichthys dentatus) from mid-Atlantic estuaries, and thorny skate (Amblyraja radiata) from the Gulf of Maine, were acutely exposed to current and projected temperatures (20, 24, or 28 °C; 22 or 30 °C; and 9, 13, or 15 °C, respectively) and acidification conditions (pH 7.8 or 7.4). We tested metabolic rates and hypoxia tolerance using intermittent-flow respirometry. All three species exhibited increases in standard metabolic rate under an 8 °C temperature increase (Q10 of 1.71, 1.07, and 2.56, respectively), although this was most pronounced in the thorny skate. At the lowest test temperature and under the low pH treatment, all three species exhibited significant increases in standard metabolic rate (44–105%; p \u3c 0.05) and decreases in hypoxia tolerance (60–84% increases in critical oxygen pressure; p \u3c 0.05). This study demonstrates the interactive effects of increasing temperature and changing ocean carbonate chemistry are species-specific, the implications of which should be considered within the context of habitat. Associated dataset: Gail D. Schweiterman, Daniel P. Crear et al. 2019. Metabolic Rates and Hypoxia Tolerences of clearnose skate (Rostaraja eglanteria), summer flounder (Paralichthys dentatus), and thorny skate (Amblyraja radiata) https://doi.org/10.25773/qmew-c18

Metabolic Rates and Hypoxia Tolerences of clearnose skate (Rostaraja eglanteria), summer flounder (Paralichthys dentatus), and thorny skate (Amblyraja radiata)

These data were collected following methods described in the associated publication: LINK “Combined Effects of Acute Temperature Change and Elevated pCO2 on the Metabolic Rates and Hypoxia Tolerances of Clearnose Skate (Rostaraja eglanteria), Summer Flounder (Paralichthys dentatus), and Thorny Skate (Amblyraja radiata)”. Schweiterman, G.D. et al. 2019 Biology, 8(3), 56

Assessing United States county-level exposure for research on tropical cyclones and human health

Includes bibliographical references (pages 067007-12-067007-13).Background: Tropical cyclone epidemiology can be advanced through exposure assessment methods that are comprehensive and consistent across space and time, as these facilitate multiyear, multistorm studies. Further, an understanding of patterns in and between exposure metrics that are based on specific hazards of the storm can help in designing tropical cyclone epidemiological research. Objectives: a) Provide an open-source data set for tropical cyclone exposure assessment for epidemiological research; and b) investigate patterns and agreement between county-level assessments of tropical cyclone exposure based on different storm hazards. Methods: We created an open-source data set with data at the county level on exposure to four tropical cyclone hazards: peak sustained wind, rainfall, flooding, and tornadoes. The data cover all eastern U.S. counties for all land-falling or near-land Atlantic basin storms, covering 1996–2011 for all metrics and up to 1988–2018 for specific metrics. We validated measurements against other data sources and investigated patterns and agreement among binary exposure classifications based on these metrics, as well as compared them to use of distance from the storm’s track, which has been used as a proxy for exposure in some epidemiological studies. Results: Our open-source data set was typically consistent with data from other sources, and we present and discuss areas of disagreement and other caveats. Over the study period and area, tropical cyclones typically brought different hazards to different counties. Therefore, when comparing exposure assessment between different hazard-specific metrics, agreement was usually low, as it also was when comparing exposure assessment based on a distance-based proxy measurement and any of the hazard-specific metrics. Discussion: Our results provide a multihazard data set that can be leveraged for epidemiological research on tropical cyclones, as well as insights that can inform the design and analysis for tropical cyclone epidemiological researc

Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States

Background: Most health effects studies of ozone and temperature have been performed in urban areas, due to the available monitoring data. We used observed and interpolated data to examine temperature, ozone, and mortality in 91 urban and non-urban counties. Methods: Ozone measurements were extracted from the Environmental Protection Agency's Air Quality System. Meteorological data were supplied by the National Center for Atmospheric Research. Observed data were spatially interpolated to county centroids. Daily internal-cause mortality counts were obtained from the National Center for Health Statistics (1988-1999). A two-stage Bayesian hierarchical model was used to estimate each county's increase in mortality risk from temperature and ozone. We examined county-level associations according to population density and compared urban (⩾1,000 persons/mile2) to non-urban (<1,000 persons/mile2) counties. Finally, we examined county-level characteristics that could explain variation in associations by county. Results: A 10 ppb increase in ozone was associated with a 0.45% increase in mortality (95% PI: 0.08, 0.83) in urban counties, while this same increase in ozone was associated with a 0.73% increase (95% PI: 0.19, 1.26) in non-urban counties. An increase in temperature from 70°F to 90°F (21.2°C 32.2°C) was associated with a 8.88% increase in mortality (95% PI: 7.38, 10.41) in urban counties and a 8.08% increase (95% PI: 6.16, 10.05) in nonurban counties. County characteristics, such as population density, percentage of families living in poverty, and percentage of elderly residents, partially explained the variation in county-level associations. Conclusions: While most prior studies of ozone and temperature have been performed in urban areas, the impacts in non-urban areas are significant, and, for ozone, potentially greater. The health risks of increasing temperature and air pollution brought on by climate change are not limited to urban areas

Dissipative effects on quantum glassy systems

We discuss the behavior of a quantum glassy system coupled to a bath of quantum oscillators. We show that the system localizes in the absence of interactions when coupled to a subOhmic bath. When interactions are switched on localization disappears and the system undergoes a phase transition towards a glassy phase. We show that the position of the critical line separating the disordered and the ordered phases strongly depends on the coupling to the bath. For a given type of bath, the ordered glassy phase is favored by a stronger coupling. Ohmic, subOhmic and superOhmic baths lead to different transition lines. We draw our conclusions from the analysis of the partition function using the replicated imaginary-time formalism and from the study of the real-time dynamics of the coupled system using the Schwinger-Keldysh closed time-path formalism.Comment: 39 pages, 13 figures, RevTe