473 research outputs found

    Geocoding Large Population‐level Administrative Datasets at Highly Resolved Spatial Scales

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    Using geographic information systems to link administrative databases with demographic, social, and environmental data allows researchers to use spatial approaches to explore relationships between exposures and health. Traditionally, spatial analysis in public health has focused on the county, ZIP code, or tract level because of limitations to geocoding at highly resolved scales. Using 2005 birth and death data from North Carolina, we examine our ability to geocode population‐level datasets at three spatial resolutions – zip code, street, and parcel. We achieve high geocoding rates at all three resolutions, with statewide street geocoding rates of 88.0% for births and 93.2% for deaths. We observe differences in geocoding rates across demographics and health outcomes, with lower geocoding rates in disadvantaged populations and the most dramatic differences occurring across the urban‐rural spectrum. Our results suggest that highly resolved spatial data architectures for population‐level datasets are viable through geocoding individual street addresses. We recommend routinely geocoding administrative datasets to the highest spatial resolution feasible, allowing public health researchers to choose the spatial resolution used in analysis based on an understanding of the spatial dimensions of the health outcomes and exposures being investigated. Such research, however, must acknowledge how disparate geocoding success across subpopulations may affect findings.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108258/1/tgis12052.pd

    Making the Environmental Justice Grade: The Relative Burden of Air Pollution Exposure in the United States

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    This paper assesses whether the Clean Air Act and its Amendments have been equally successful in ensuring the right to healthful air quality in both advantaged and disadvantaged communities in the United States. Using a method to rank air quality established by the American Lung Association in its 2009 State of the Air report along with EPA air quality data, we assess the environmental justice dimensions of air pollution exposure and access to air quality information in the United States. We focus on the race, age, and poverty demographics of communities with differing levels of ozone and particulate matter exposure, as well as communities with and without air quality information. Focusing on PM2.5 and ozone, we find that within areas covered by the monitoring networks, non-Hispanic blacks are consistently overrepresented in communities with the poorest air quality. The results for older and younger age as well as poverty vary by the pollution metric under consideration. Rural areas are typically outside the bounds of air quality monitoring networks leaving large segments of the population without information about their ambient air quality. These results suggest that substantial areas of the United States lack monitoring data, and among areas where monitoring data are available, low income and minority communities tend to experience higher ambient pollution levels

    Short- and long-term temperature responses of soil denitrifier net N2O efflux rates, inter-profile N2O dynamics, and microbial genetic potentials

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    Production and reduction of nitrous oxide (N2O) by soil denitrifiers influence atmospheric concentrations of this potent greenhouse gas. Accurate projections of the net N2O flux have three key uncertainties: (1) short- vs. long-term responses to warming, (2) interactions among soil horizons, and (3) temperature responses of different steps in the denitrification pathway. We addressed these uncertainties by sampling soil from a boreal forest climate transect encompassing a 5.2 ∘C difference in the mean annual temperature and incubating the soil horizons in isolation and together at three ecologically relevant temperatures in conditions that promote denitrification. Both short-term exposure to warmer temperatures and long-term exposure to a warmer climate increased N2O emissions from organic and mineral soils; an isotopic tracer suggested that an increase in N2O production was more important than a decline in N2O reduction. Short-term warming promoted the reduction of organic horizon-derived N2O by mineral soil when these horizons were incubated together. The abundance of nirS (a precursor gene for N2O production) was not sensitive to temperature, whereas that of nosZ clade I (a gene for N2O reduction) decreased with short-term warming in both horizons and was higher from a warmer climate. These results suggest a decoupling of gene abundance and process rates in these soils that differs across horizons and timescales. In spite of these variations, our results suggest a consistent, positive response of denitrifier-mediated net N2O efflux rates to temperature across timescales in these boreal forests. Our work also highlights the importance of understanding cross-horizon N2O fluxes for developing a predictive understanding of net N2O efflux from soils

    Short- and long-term temperature responses of soil denitrifier net N2O efflux rates, inter2 profile N2O dynamics, and microbial genetic potentials

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    Production and reduction of nitrous oxide (N2O) by soil denitrifiers influence atmospheric concentrations of this potent greenhouse gas. Accurate projections of the net N2O flux have three key uncertainties: (1) short- vs. long-term responses to warming, (2) interactions among soil horizons, and (3) temperature responses of different steps in the denitrification pathway. We addressed these uncertainties by sampling soil from a boreal forest climate transect encompassing a 5.2 ∘C difference in the mean annual temperature and incubating the soil horizons in isolation and together at three ecologically relevant temperatures in conditions that promote denitrification. Both short-term exposure to warmer temperatures and long-term exposure to a warmer climate increased N2O emissions from organic and mineral soils; an isotopic tracer suggested that an increase in N2O production was more important than a decline in N2O reduction. Short-term warming promoted the reduction of organic horizon-derived N2O by mineral soil when these horizons were incubated together. The abundance of nirS (a precursor gene for N2O production) was not sensitive to temperature, whereas that of nosZ clade I (a gene for N2O reduction) decreased with short-term warming in both horizons and was higher from a warmer climate. These results suggest a decoupling of gene abundance and process rates in these soils that differs across horizons and timescales. In spite of these variations, our results suggest a consistent, positive response of denitrifier-mediated net N2O efflux rates to temperature across timescales in these boreal forests. Our work also highlights the importance of understanding cross-horizon N2O fluxes for developing a predictive understanding of net N2O efflux from soils

    Climate Warming Can Accelerate Carbon Fluxes without Changing Soil Carbon Stocks

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    Climate warming enhances multiple ecosystem C fluxes, but the net impact of changing C fluxes on soil organic carbon (SOC) stocks over decadal to centennial time scales remains unclear. We investigated the effects of climate on C fluxes and soil C stocks using space-for-time substitution along a boreal forest climate gradient encompassing spatially replicated sites at each of three latitudes. All regions had similar SOC concentrations and stocks (5.6 to 6.7 kg C m−2). The three lowest latitude forests exhibited the highest productivity across the transect, with tree biomass:age ratios and litterfall rates 300 and 125% higher than those in the highest latitude forests, respectively. Likewise, higher soil respiration rates (~55%) and dissolved organic C fluxes (~300%) were observed in the lowest latitude forests compared to those in the highest latitude forests. The mid-latitude forests exhibited intermediate values for these indices and fluxes. The mean radiocarbon content (Δ14C) of mineral-associated SOC (+9.6‰) was highest in the lowest latitude forests, indicating a more rapid turnover of soil C compared to the mid- and highest latitude soils (Δ14C of −35 and −30‰, respectively). Indicators of the extent of soil organic matter decomposition, including C:N, ή13C, and amino acid and alkyl-C:O-alkyl-C indices, revealed highly decomposed material across all regions. These data indicate that the lowest latitude forests experience accelerated C fluxes that maintain relatively young but highly decomposed SOC. Collectively, these observations of within-biome soil C responses to climate demonstrate that the enhanced rates of SOC loss that typically occur with warming can be balanced on decadal to centennial time scales by enhanced rates of C inputs

    Creating a database of internet-based clinical trials to support a public-led research programme: A descriptive analysis

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    Background: Online trials are rapidly growing in number, offering potential benefits but also methodological, ethical and social challenges. The International Network for Knowledge on Well-being (ThinkWellℱ) aims to increase public and patient participation in the prioritisation, design and conduct of research through the use of technologies. Objective: We aim to provide a baseline understanding of the online trial environment, determining how many trials have used internet-based technologies; how they have been used; and how use has developed over time. Methods: We searched a range of bibliographic databases to March 2015, with no date limits, supplemented by citation searching and references provided by experts in the field. Results were screened against inclusion and exclusion criteria, and included studies mapped against a number of key dimensions, with key themes developed iteratively throughout the process. Results: We identified 1992 internet-based trials to March 2015. The number of reported studies increased substantially over the study timeframe. The largest number of trials were conducted in the USA (49.7%), followed by The Netherlands (10.2%); Australia (8.5%); the United Kingdom (5.8%); Sweden (4.6%); Canada (4%); and Germany (2.6%). South Korea (1.5%) has the highest number of reported trials for other continents. There is a predominance of interventions addressing core public health challenges including obesity (8.6%), smoking cessation (5.9%), alcohol abuse (7.7%) and physical activity (10.2%); in mental health issues such as depression (10.9%) and anxiety (5.6%); and conditions where self-management (16.6%) or monitoring (8.1%) is a major feature of care. Conclusions: The results confirm an increase in the use of the internet in trials. Key themes have emerged from the analysis and further research will be undertaken in order to investigate how the data can be used to improve trial design and recruitment, and to build an open access resource to support the public-led research agenda

    Cadmium levels in a North Carolina cohort: Identifying risk factors for elevated levels during pregnancy

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    The objectives of this study were to examine cadmium (Cd) levels and relationships to demographics in an observational, prospective pregnancy cohort study in Durham County, North Carolina. Multivariable models were used to compare blood Cd levels across demographic characteristics. The relative risk of having a blood Cd level that exceeds the US national median (0.32 ÎŒg/l) was estimated. Overall, >60% of the women had an elevated (>0.32 ÎŒg/l) blood Cd level. Controlling for confounding variables, smoking was associated with 21% (95% CI: 15–28%) increased risk for an elevated blood Cd level. High Cd levels were also observed in non-smokers and motivated smoking status-stratified models. Race, age, education, relationship status, insurance status and cotinine level were not associated with risk of elevated Cd levels among smokers; however, older age and higher cotinine levels were associated with elevated Cd levels among non-smokers. Taken together, more than half of pregnant women in this cohort had elevated blood Cd levels. Additionally, among non-smokers, 53% of the women had elevated levels of Cd, highlighting other potential sources of exposure. This study expands on the limited data describing Cd levels in pregnant populations and highlights the importance of understanding Cd exposures among non-smokers. Given the latent health risks of both smoking and Cd exposure, this study further highlights the need to biomonitor for exposure to toxic metals during pregnancy among all women of child-bearing age

    CowPI::A rumen microbiome focussed version of the PICRUSt functional inference software

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    Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and over 500 fully sequenced microbial genomes from this environment. Using this information we have developed ?CowPI? a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and captures the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to both the metagenomic and metatranscriptome data and so we recommend where possible, functional inferences from 16S data should not replace metagenomic and metatranscriptomic approaches. The tool can be accessed at http://www.cowpi.org and is provided to the wider scientific community for use in the study of the rumen microbiomepublishersversionPeer reviewe
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