Spatial Misalignment in time series studies of air pollution and health data

Time series studies of environmental exposures often involve comparing daily changes in a toxicant measured at a point in space with daily changes in an aggregate measure of health. Spatial misalignment of the exposure and response variables can bias the estimation of health risk and the magnitude of this bias depends on the spatial variation of the exposure of interest. In air pollution epidemiology, there is an increasing focus on estimating the health effects of the chemical components of particulate matter. One issue that is raised by this new focus is the spatial misalignment error introduced by the lack of spatial homogeneity in many of the particulate matter components. Current approaches to estimating short-term health risks via time series modeling do not take into account the spatial properties of the chemical components and therefore could result in biased estimation of those risks. We present a spatial-temporal statistical model for quantifying spatial misalignment error and show how adjusted heath risk estimates can be obtained using a regression calibration approach and a two-stage Bayesian model. We apply our methods to a database containing information on hospital admissions, air pollution, and weather for 20 large urban counties in the United States

Association of Osteoarthritis with Perfluorooctanoate and Perfluorooctane Sulfonate in NHANES 2003–2008

Background: Perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) are persistent, synthetic industrial chemicals. Perfluorinated compounds are linked to health impacts that may be relevant to osteoarthritis, cartilage repair, and inflammatory responses. Objectives: We investigated whether PFOA and PFOS exposures are associated with prevalence of osteoarthritis, and whether associations differ between men and women. Methods: We used multiple logistic regression to estimate associations between serum PFOA and PFOS concentrations and self-reported diagnosis of osteoarthritis in persons 20–84 years of age who participated in NHANES during 2003–2008. We adjusted for potential confounders including age, income, and race/ethnicity. Effects by sex were estimated using stratified models and interaction terms. Results: Those in the highest exposure quartile had higher odds of osteoarthritis compared with those in the lowest quartile [odds ratio (OR) for PFOA = 1.55; 95% CI: 0.99, 2.43; OR for PFOS = 1.77; 95% CI: 1.05, 2.96]. When stratifying by sex, we found positive associations for women, but not men. Women in the highest quartiles of PFOA and PFOS exposure had higher odds of osteoarthritis compared with those in the lowest quartiles (OR for PFOA = 1.98; 95% CI: 1.24, 3.19 and OR for PFOS = 1.73; 95% CI: 0.97, 3.10). Conclusions: Higher concentrations of serum PFOA were associated with osteoarthritis in women, but not men. PFOS was also associated with osteoarthritis in women only, though effect estimates for women were not significant. More research is needed to clarify potential differences in susceptibility between women and men with regard to possible effects of these and other endocrine-disrupting chemicals

The Exposure–Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations

Time-series analyses have shown that ozone is associated with increased risk of premature mortality, but little is known about how O(3) affects health at low concentrations. A critical scientific and policy question is whether a threshold level exists below which O(3) does not adversely affect mortality. We developed and applied several statistical models to data on air pollution, weather, and mortality for 98 U.S. urban communities for the period 1987–2000 to estimate the exposure–response curve for tropospheric O(3) and risk of mortality and to evaluate whether a “safe” threshold level exists. Methods included a linear approach and subset, threshold, and spline models. All results indicate that any threshold would exist at very low concentrations, far below current U.S. and international regulations and nearing background levels. For example, under a scenario in which the U.S. Environmental Protection Agency’s 8-hr regulation is met every day in each community, there was still a 0.30% increase in mortality per 10-ppb increase in the average of the same and previous days’ O(3) levels (95% posterior interval, 0.15–0.45%). Our findings indicate that even low levels of tropospheric O(3) are associated with increased risk of premature mortality. Interventions to further reduce O(3) pollution would benefit public health, even in regions that meet current regulatory standards and guidelines

Heat-Related Mortality and Adaptation to Heat in the United States

Background: In a changing climate, increasing temperatures are anticipated to have profound health impacts. These impacts could be mitigated if individuals and communities adapt to changing exposures; however, little is known about the extent to which the population may be adapting. Objective: We investigated the hypothesis that if adaptation is occurring, then heat-related mortality would be decreasing over time. Methods: We used a national database of daily weather, air pollution, and age-stratified mortality rates for 105 U.S. cities (covering 106 million people) during the summers of 1987–2005. Time-varying coefficient regression models and Bayesian hierarchical models were used to estimate city-specific, regional, and national temporal trends in heat-related mortality and to identify factors that might explain variation across cities. Results: On average across cities, the number of deaths (per 1,000 deaths) attributable to each 10°F increase in same-day temperature decreased from 51 [95% posterior interval (PI): 42, 61] in 1987 to 19 (95% PI: 12, 27) in 2005. This decline was largest among those ≥ 75 years of age, in northern regions, and in cities with cooler climates. Although central air conditioning (AC) prevalence has increased, we did not find statistically significant evidence of larger temporal declines among cities with larger increases in AC prevalence. Conclusions: The population has become more resilient to heat over time. Yet even with this increased resilience, substantial risks of heat-related mortality remain. Based on 2005 estimates, an increase in average temperatures by 5°F (central climate projection) would lead to an additional 1,907 deaths per summer across all cities. Citation: Bobb JF, Peng RD, Bell ML, Dominici F. 2014. Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122:811–816; http://dx.doi.org/10.1289/ehp.130739

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

Declaring a Patient Brain Dead on Extracorporeal Membrane Oxygenation (ECMO): Are There Guidelines or Misconceptions

Objectives: To review the clinical practice variations and trends with declaring patients brain dead on ECMO To highlight the need for the development of consensus guidelines to assist clinicians in the accurate diagnosis of brain death in this specific patient populatio

Shape of the concentration–response association between fine particulate matter pollution and human mortality in Beijing, China, and its implications for health impact assessment, The

Includes bibliographical references (pages 107009-12-107009-14).Publisher version: https://doi.org/10.1289/EHP4464.Background: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration–response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear. Objectives: We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter ≤2.5μm (PM2.5) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions. Methods: We modeled the C-R association between PM2.5 and cause-specific mortality in Beijing, China (2009–2012), using generalized linear models (GLM). PM2.5 was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated PM2.5-attributable deaths using both linear- and nonlinear-based C-R associations between PM2.5 and mortality. Results: We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of PM2.5, but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of PM2.5, but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term PM2.5 exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption. Conclusions: Our results demonstrate some evidence of nonlinearity in PM2.5–mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the PM2.5–mortality association at the high concentrations of PM2.5 in developing megacities like Beijing. https://doi.org/10.1289/EHP446

Associations of PM2.5 Constituents and Sources with Hospital Admissions: Analysis of Four Counties in Connecticut and Massachusetts (USA) for Persons ≥ 65 Years of Age

Background: Epidemiological studies have demonstrated associations between short-term exposure to PM2.5 and hospital admissions. The chemical composition of particles varies across locations and time periods. Identifying the most harmful constituents and sources is an important health and regulatory concern. Objectives: We examined pollutant sources for associations with risk of hospital admissions for cardiovascular and respiratory causes. Methods: We obtained PM2.5 filter samples for four counties in Connecticut and Massachusetts and analyzed them for PM2.5 elements. Source apportionment was used to estimate daily PM2.5 contributions from sources (traffic, road dust, oil combustion, and sea salt as well as a regional source representing coal combustion and other sources). Associations between daily PM2.5 constituents and sources and risk of cardiovascular and respiratory hospitalizations for the Medicare population (> 333,000 persons ≥ 65 years of age) were estimated with time-series analyses (August 2000–February 2004). Results: PM2.5 total mass and PM2.5 road dust contribution were associated with cardiovascular hospitalizations, as were the PM2.5 constituents calcium, black carbon, vanadium, and zinc. For respiratory hospitalizations, associations were observed with PM2.5 road dust, and sea salt as well as aluminum, calcium, chlorine, black carbon, nickel, silicon, titanium, and vanadium. Effect estimates were generally robust to adjustment by co-pollutants of other constituents. An interquartile range increase in same-day PM2.5 road dust (1.71 μg/m3) was associated with a 2.11% (95% CI: 1.09, 3.15%) and 3.47% (95% CI: 2.03, 4.94%) increase in cardiovascular and respiratory admissions, respectively. Conclusions: Our results suggest some particle sources and constituents are more harmful than others and that in this Connecticut/Massachusetts region the most harmful particles include black carbon, calcium, and road dust PM2.5. Citation: Bell ML, Ebisu K, Leaderer BP, Gent JF, Lee HJ, Koutrakis P, Wang Y, Dominici F, Peng RD. 2014. Associations of PM2.5 constituents and sources with hospital admissions: analysis of four counties in Connecticut and Massachusetts (USA) for persons ≥ 65 years of age. Environ Health Perspect 122:138–144; http://dx.doi.org/10.1289/ehp.130665

International expert workshop on the analysis of the economic and public health impacts of air pollution: workshop summary.

Forty-nine experts from 18 industrial and developing countries met on 6 September 2001 in Garmisch-Partenkirchen, Germany, to discuss the economic and public health impacts of air pollution, particularly with respect to assessing the public health benefits from technologies and policies that reduce greenhouse gas (GHG) emissions. Such measures would provide immediate public health benefits, such as reduced premature mortality and chronic morbidity, through improved local air quality. These mitigation strategies also allow long-term goals--for example, reducing the buildup of GHG emissions--to be achieved alongside short-term aims, such as immediate improvements in air quality, and therefore benefits to public health. The workshop aimed to foster research partnerships by improving collaboration and communication among various agencies and researchers; providing a forum for presentations by sponsoring agencies and researchers regarding research efforts and agency activities; identifying key issues, knowledge gaps, methodological shortcomings, and research needs; and recommending activities and initiatives for research, collaboration, and communication. This workshop summary briefly describes presentations made by workshop participants and the conclusions of three separate working groups: economics, benefits transfer, and policy; indoor air quality issues and susceptible populations; and development and transfer of dose-response relationships and exposure models in developing countries. Several common themes emerged from the working group sessions and subsequent discussion. Key recommendations include the need for improved communication and extended collaboration, guidance and support for researchers, advances in methods, and resource support for data collection, assessment, and research

Advanced imaging capabilities by incorporating plasmonics and metamaterials in detectors

Ultraviolet detection is often required to be made in the presence of a strong background of solar radiation which needs to be suppressed, but materials limitations at these wavelengths can impact both filter and sensor performance. In this work, we explore the use of 1D photonic bandgap structures integrated directly onto a Si sensor that can operate with solar blindness. These filters take advantage of the improved admittance with silicon to significantly improve throughput over conventional stand-alone bandpass filter elements. At far ultraviolet wavelengths these filters require the use of non-absorbing dielectrics such as the metal fluoride materials of MgF_2, AlF_3 and LiF. The latest performance of these 1D multilayer filters on Si photodiodes and CCD imaging sensors is demonstrated. We have also extended these 1D structures to more complex multilayers guided by the design concepts of metamaterials and metatronics, and to 2D patterned plasmonic hole array filters fabricated in aluminum. The performance of sensors and test filter structures is presented with an emphasis on UV throughput