A two-phase Poisson process model and its application to analysis of cancer mortality among A-bomb survivors.

PubMed

Ohtaki, Megu; Tonda, Tetsuji; Aihara, Kazuyuki

2015-10-01

We consider a two-phase Poisson process model where only early successive transitions are assumed to be sensitive to exposure. In the case where intensity transitions are low, we derive analytically an approximate formula for the distribution of time to event for the excess hazard ratio (EHR) due to a single point exposure. The formula for EHR is a polynomial in exposure dose. Since the formula for EHR contains no unknown parameters except for the number of total stages, number of exposure-sensitive stages, and a coefficient of exposure effect, it is applicable easily under a variety of situations where there exists a possible latency time from a single point exposure to occurrence of event. Based on the multistage hypothesis of cancer, we formulate a radiation carcinogenesis model in which only some early consecutive stages of the process are sensitive to exposure, whereas later stages are not affected. An illustrative analysis using the proposed model is given for cancer mortality among A-bomb survivors. Copyright © 2015 Elsevier Inc. All rights reserved.

RECEPTOR MODELING OF AMBIENT AND PERSONAL EXPOSURE SAMPLES: 1998 BALTIMORE PARTICULATE MATTER EPIDEMIOLOGY-EXPOSURE STUDY

EPA Science Inventory

Sources of particulate matter exposure for an elderly population in a city north of Baltimore, MD were evaluated using advanced factor analysis models. Data collected with Versatile Air Pollutant Samplers (VAPS) positioned at a community site, outside and inside of an elderly ...

Modeling population exposures to outdoor sources of hazardous air pollutants.

PubMed

Ozkaynak, Halûk; Palma, Ted; Touma, Jawad S; Thurman, James

2008-01-01

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time-activity, commuting, and exposure factors data, for the purposes of assigning exposures in air pollution health studies.

Plasma Vehicle Charging Analysis for Orion Flight Test 1

NASA Technical Reports Server (NTRS)

Lallement, L.; McDonald, T.; Norgard, J.; Scully, B.

2014-01-01

In preparation for the upcoming experimental test flight for the Orion crew module, considerable interest was raised over the possibility of exposure to elevated levels of plasma activity and vehicle charging both externally on surfaces and internally on dielectrics during the flight test orbital operations. Initial analysis using NASCAP-2K indicated very high levels of exposure, and this generated additional interest in refining/defining the plasma and spacecraft models used in the analysis. This refinement was pursued, resulting in the use of specific AE8 and AP8 models, rather than SCATHA models, as well as consideration of flight trajectory, time duration, and other parameters possibly affecting the levels of exposure and the magnitude of charge deposition. Analysis using these refined models strongly indicated that, for flight test operations, no special surface coatings were necessary for the thermal protection system, but would definitely be required for future GEO, trans-lunar, and extra-lunar missions...

Plasma Vehicle Charging Analysis for Orion Flight Test 1

NASA Technical Reports Server (NTRS)

Scully, B.; Norgard, J.

2015-01-01

In preparation for the upcoming experimental test flight for the Orion crew module, considerable interest was raised over the possibility of exposure to elevated levels of plasma activity and vehicle charging both externally on surfaces and internally on dielectrics during the flight test orbital operations. Initial analysis using NASCAP-2K indicated very high levels of exposure, and this generated additional interest in refining/defining the plasma and spacecraft models used in the analysis. This refinement was pursued, resulting in the use of specific AE8 and AP8 models, rather than SCATHA models, as well as consideration of flight trajectory, time duration, and other parameters possibly affecting the levels of exposure and the magnitude of charge deposition. Analysis using these refined models strongly indicated that, for flight test operations, no special surface coatings were necessary for the Thermal Protection System (TPS), but would definitely be required for future GEO, trans-lunar, and extra-lunar missions.

Time series analysis of personal exposure to ambient air pollution and mortality using an exposure simulator.

PubMed

Chang, Howard H; Fuentes, Montserrat; Frey, H Christopher

2012-09-01

This paper describes a modeling framework for estimating the acute effects of personal exposure to ambient air pollution in a time series design. First, a spatial hierarchical model is used to relate Census tract-level daily ambient concentrations and simulated exposures for a subset of the study period. The complete exposure time series is then imputed for risk estimation. Modeling exposure via a statistical model reduces the computational burden associated with simulating personal exposures considerably. This allows us to consider personal exposures at a finer spatial resolution to improve exposure assessment and for a longer study period. The proposed approach is applied to an analysis of fine particulate matter of <2.5 μm in aerodynamic diameter (PM(2.5)) and daily mortality in the New York City metropolitan area during the period 2001-2005. Personal PM(2.5) exposures were simulated from the Stochastic Human Exposure and Dose Simulation. Accounting for exposure uncertainty, the authors estimated a 2.32% (95% posterior interval: 0.68, 3.94) increase in mortality per a 10 μg/m(3) increase in personal exposure to PM(2.5) from outdoor sources on the previous day. The corresponding estimates per a 10 μg/m(3) increase in PM(2.5) ambient concentration was 1.13% (95% confidence interval: 0.27, 2.00). The risks of mortality associated with PM(2.5) were also higher during the summer months.

Comparison of screening-level and Monte Carlo approaches for wildlife food web exposure modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pastorok, R.; Butcher, M.; LaTier, A.

1995-12-31

The implications of using quantitative uncertainty analysis (e.g., Monte Carlo) and site-specific tissue residue data for wildlife exposure modeling were examined with data on trace elements at the Clark Fork River Superfund Site. Exposure of white-tailed deer, red fox, and American kestrel was evaluated using three approaches. First, a screening-level exposure model was based on conservative estimates of exposure parameters, including estimates of dietary residues derived from bioconcentration factors (BCFs) and soil chemistry. A second model without Monte Carlo was based on site-specific data for tissue residues of trace elements (As, Cd, Cu, Pb, Zn) in key dietary species andmore » plausible assumptions for habitat spatial segmentation and other exposure parameters. Dietary species sampled included dominant grasses (tufted hairgrass and redtop), willows, alfalfa, barley, invertebrates (grasshoppers, spiders, and beetles), and deer mice. Third, the Monte Carlo analysis was based on the site-specific residue data and assumed or estimated distributions for exposure parameters. Substantial uncertainties are associated with several exposure parameters, especially BCFS, such that exposure and risk may be greatly overestimated in screening-level approaches. The results of the three approaches are compared with respect to realism, practicality, and data gaps. Collection of site-specific data on trace elements concentrations in plants and animals eaten by the target wildlife receptors is a cost-effective way to obtain realistic estimates of exposure. Implications of the results for exposure and risk estimates are discussed relative to use of wildlife exposure modeling and evaluation of remedial actions at Superfund sites.« less

75 FR 40745 - Cyazofamid; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-14

... Model/Exposure Analysis Modeling System (PRZM/EXAMS) model for surface water and the Screening... listed in this unit could also be affected. The North American Industrial Classification System (NAICS... there is reliable information.'' This includes exposure through drinking water and in residential...

A modular Human Exposure Model (HEM) framework to characterize near-field chemical exposure in LCIA and CAA

EPA Science Inventory

Life Cycle Impact Analysis (LCIA) has proven to be a valuable tool for systematically comparing processes and products, and has been proposed for use in Chemical Alternatives Analysis (CAA). The exposure assessment portion of the human health impact scores of LCIA has historicall...

76 FR 70890 - Fenamidone; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-16

.../models/water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM... listed in this unit could also be affected. The North American Industrial Classification System (NAICS... there is reliable information.'' This includes exposure through drinking water and in residential...

78 FR 29049 - Streptomycin; Pesticide Tolerances for Emergency Exemptions

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-17

... exposures for which there is reliable information.'' This includes exposure through drinking water and in... commodities. 2. Dietary exposure from drinking water. The Agency used screening level water exposure models in the dietary exposure analysis and risk assessment for streptomycin in drinking water. These simulation...

Targeted and Non-Targeted Analysis of Serum Pools to Provide Chemical Exposure Data for Exposure Modeling and Chemical Prioritization

EPA Science Inventory

Biomonitoring data can help inform the development and calibration of high-throughput exposure modeling for use in prioritization and risk evaluation. A pilot project was conducted to evaluate the feasibility of using pooled banked blood samples to generate initial data on popul...

Modeling approaches for characterizing and evaluating environmental exposure to engineered nanomaterials in support of risk-based decision making.

PubMed

Hendren, Christine Ogilvie; Lowry, Michael; Grieger, Khara D; Money, Eric S; Johnston, John M; Wiesner, Mark R; Beaulieu, Stephen M

2013-02-05

As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.

Effects of exposure to malathion on blood glucose concentration: a meta-analysis.

PubMed

Ramirez-Vargas, Marco Antonio; Flores-Alfaro, Eugenia; Uriostegui-Acosta, Mayrut; Alvarez-Fitz, Patricia; Parra-Rojas, Isela; Moreno-Godinez, Ma Elena

2018-02-01

Exposure to malathion (an organophosphate pesticide widely used around the world) has been associated with alterations in blood glucose concentration in animal models. However, the results are inconsistent. The aim of this meta-analysis was to evaluate whether malathion exposure can disturb the concentrations of blood glucose in exposed rats. We performed a literature search of online databases including PubMed, EBSCO, and Google Scholar and reviewed original articles that analyzed the relation between malathion exposure and glucose levels in animal models. The selection of articles was based on inclusion and exclusion criteria. The database search identified thirty-five possible articles, but only eight fulfilled our inclusion criteria, and these studies were included in the meta-analysis. The effect of malathion on blood glucose concentration showed a non-monotonic dose-response curve. In addition, pooled analysis showed that blood glucose concentrations were 3.3-fold higher in exposed rats than in the control group (95% CI, 2-5; Z = 3.9; p < 0.0001) in a random-effect model. This result suggested that alteration of glucose homeostasis is a possible mechanism of toxicity associated with exposure to malathion.

Radiometric analysis of photographic data by the effective exposure method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Constantine, B J

1972-04-01

The effective exposure method provides for radiometric analysis of photographic data. A three-dimensional model, where density is a function of energy and wavelength, is postulated to represent the film response function. Calibration exposures serve to eliminate the other factors which affect image density. The effective exposure causing an image can be determined by comparing the image density with that of a calibration exposure. If the relative spectral distribution of the source is known, irradiance and/or radiance can be unfolded from the effective exposure expression.

Total Risk Integrated Methodology (TRIM) - TRIM.Expo

EPA Pesticide Factsheets

The Exposure Event module of TRIM (TRIM.Expo), similar to most human exposure models, provides an analysis of the relationships between various chemical concentrations in the environment and exposure levels of humans.

Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models

NASA Astrophysics Data System (ADS)

Beckx, Carolien; Int Panis, Luc; Uljee, Inge; Arentze, Theo; Janssens, Davy; Wets, Geert

Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated model chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport model) and about ambient pollutant concentrations (obtained from a dispersion model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all models under consideration. The evaluation of population level exposure in The Netherlands to NO 2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO 2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification.

APPLICATION AND EVALUATION OF AN AGGREGATE PHYSICALLY-BASED TWO-STAGE MONTE CARLO PROBABILISTIC MODEL FOR QUANTIFYING CHILDREN'S RESIDENTIAL EXPOSURE AND DOSE TO CHLORPYRIFOS

EPA Science Inventory

Critical voids in exposure data and models lead risk assessors to rely on conservative assumptions. Risk assessors and managers need improved tools beyond the screening level analysis to address aggregate exposures to pesticides as required by the Food Quality Protection Act o...

Analysis of Coupled Model Uncertainties in Source to Dose Modeling of Human Exposures to Ambient Air Pollution: a PM2.5 Case-Study

EPA Science Inventory

Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into acco...

[The methods of assessment of health risk from exposure to radon and radon daughters].

PubMed

Demin, V F; Zhukovskiy, M V; Kiselev, S M

2014-01-01

The critical analysis of existing models of the relationship dose-effect (RDE) for radon exposure on human health has been performed. Conclusion about the necessity and possibility of improving these models has been made. A new improved version ofthe RDE has been developed. A technique for assessing the human health risk of exposure to radon, including the method for estimating of exposure doses of radon, an improved model of RDE, proper methodology risk assessment has been described. Methodology is proposed for the use in the territory of Russia.

A Meta-Analysis of Children's Object-to-Mouth Frequency Data for Estimating Non-Dietary Ingestion Exposure

EPA Science Inventory

To improve estimates of non-dietary ingestion in probabilistic exposure modeling, a meta-analysis of children's object-to-mouth frequency was conducted using data from seven available studies representing 438 participants and ~ 1500 h of behavior observation. The analysis repres...

Time series regression studies in environmental epidemiology.

PubMed

Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben

2013-08-01

Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed ('lagged') associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.

SENSITIVITY ANALYSIS AND EVALUATION OF MICROFACO: A MICROSCALE MOTOR VEHICLE EMISSION FACTOR MODEL FOR CO EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source t...

COMPARING THE UTILITY OF MULTIMEDIA MODELS FOR HUMAN AND ECOLOGICAL EXPOSURE ANALYSIS: TWO CASES

EPA Science Inventory

A number of models are available for exposure assessment; however, few are used as tools for both human and ecosystem risks. This discussion will consider two modeling frameworks that have recently been used to support human and ecological decision making. The study will compare ...

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

Revealing the underlying drivers of disaster risk: a global analysis

NASA Astrophysics Data System (ADS)

Peduzzi, Pascal

2017-04-01

Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL) and Probable Maximum Losses (PML) in GAR 2013 and GAR 2015. In parallel similar methodologies were developed to highlitght the role of ecosystems for Climate Change Adaptation (CCA) and Disaster Risk Reduction (DRR). New developments may include slow hazards (such as e.g. soil degradation and droughts), natech hazards (by intersecting with georeferenced critical infrastructures) The various global hazard, exposure and risk models can be visualized and download through the PREVIEW Global Risk Data Platform.

The impact of composite AUC estimates on the prediction of systemic exposure in toxicology experiments.

PubMed

Sahota, Tarjinder; Danhof, Meindert; Della Pasqua, Oscar

2015-06-01

Current toxicity protocols relate measures of systemic exposure (i.e. AUC, Cmax) as obtained by non-compartmental analysis to observed toxicity. A complicating factor in this practice is the potential bias in the estimates defining safe drug exposure. Moreover, it prevents the assessment of variability. The objective of the current investigation was therefore (a) to demonstrate the feasibility of applying nonlinear mixed effects modelling for the evaluation of toxicokinetics and (b) to assess the bias and accuracy in summary measures of systemic exposure for each method. Here, simulation scenarios were evaluated, which mimic toxicology protocols in rodents. To ensure differences in pharmacokinetic properties are accounted for, hypothetical drugs with varying disposition properties were considered. Data analysis was performed using non-compartmental methods and nonlinear mixed effects modelling. Exposure levels were expressed as area under the concentration versus time curve (AUC), peak concentrations (Cmax) and time above a predefined threshold (TAT). Results were then compared with the reference values to assess the bias and precision of parameter estimates. Higher accuracy and precision were observed for model-based estimates (i.e. AUC, Cmax and TAT), irrespective of group or treatment duration, as compared with non-compartmental analysis. Despite the focus of guidelines on establishing safety thresholds for the evaluation of new molecules in humans, current methods neglect uncertainty, lack of precision and bias in parameter estimates. The use of nonlinear mixed effects modelling for the analysis of toxicokinetics provides insight into variability and should be considered for predicting safe exposure in humans.

ANALYSIS OF DISCRIMINATING FACTORS IN HUMAN ACTIVITIES THAT AFFECT EXPOSURE

EPA Science Inventory

Accurately modeling exposure to particulate matter (PM) and other pollutants ultimately involves the utilization of human location-activity databases to assist in understanding the potential variability of microenvironmental exposures. This paper critically considers and stati...

On the equivalence of case-crossover and time series methods in environmental epidemiology.

PubMed

Lu, Yun; Zeger, Scott L

2007-04-01

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.

77 FR 21670 - Acibenzolar-S-

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-11

.../Exposure Analysis Modeling System and Screening Concentration in Ground Water (SCI-GROW) models, the... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... reliable information.'' This includes exposure through drinking water and in residential settings, but does...

Noise Exposure Model MOD-5 : Volume 1

DOT National Transportation Integrated Search

1971-06-01

The report contains three sections. The first two sections are contained in Volume 1. It contains an airport analysis which describes the noise exposure model MOD-5 from the perspective of analysing an airport in order to develop the program input mo...

Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

NASA Astrophysics Data System (ADS)

Milando, Chad W.; Batterman, Stuart A.

2018-05-01

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

The Toxicological Evaluation of Realistic Emissions of Source Aerosols Study: Statistical Methods

PubMed Central

Coull, Brent A.; Wellenius, Gregory A.; Gonzalez-Flecha, Beatriz; Diaz, Edgar; Koutrakis, Petros; Godleski, John J.

2013-01-01

The Toxicological Evaluation of Realistic Emissions of Source Aerosols (TERESA) study involved withdrawal, aging, and atmospheric transformation of emissions of three coal-fired power plants. Toxicological evaluations were carried out in rats exposed to different emission scenarios with extensive exposure characterization. Data generated had multiple levels of resolution: exposure, scenario and constituent chemical composition. Here, we outline a multilayered approach to analyze the associations between exposure and health effects beginning with standard ANOVA models that treat exposure as a categorical variable. The model assessed differences in exposure effects across scenarios (by plant). To assess unadjusted associations between pollutant concentrations and health, univariate analyses were conducted using the difference between the response means under exposed and control conditions and a single constituent concentration as the predictor. Then, a novel multivariate analysis of exposure composition and health was used based on random forests, a recent extension of classification and regression trees that were applied to the outcome differences. For each exposure constituent, this approach yielded a nonparametric measure of the importance of that constituent in predicting differences in response on a given day, controlling for the other measured constituent concentrations in the model. Finally, an R2 analysis compared the relative importance of exposure scenario, plant, and constituent concentrations on each outcome. Peak expiratory flow is used to demonstrate how the multiple levels of the analysis complement each other to assess constituents most strongly associated with health effects. PMID:21913820

The toxicological evaluation of realistic emissions of source aerosols study: statistical methods.

PubMed

Coull, Brent A; Wellenius, Gregory A; Gonzalez-Flecha, Beatriz; Diaz, Edgar; Koutrakis, Petros; Godleski, John J

2011-08-01

The Toxicological Evaluation of Realistic Emissions of Source Aerosols (TERESA) study involved withdrawal, aging, and atmospheric transformation of emissions of three coal-fired power plants. Toxicological evaluations were carried out in rats exposed to different emission scenarios with extensive exposure characterization. Data generated had multiple levels of resolution: exposure, scenario, and constituent chemical composition. Here, we outline a multilayered approach to analyze the associations between exposure and health effects beginning with standard ANOVA models that treat exposure as a categorical variable. The model assessed differences in exposure effects across scenarios (by plant). To assess unadjusted associations between pollutant concentrations and health, univariate analyses were conducted using the difference between the response means under exposed and control conditions and a single constituent concentration as the predictor. Then, a novel multivariate analysis of exposure composition and health was used based on Random Forests(™), a recent extension of classification and regression trees that were applied to the outcome differences. For each exposure constituent, this approach yielded a nonparametric measure of the importance of that constituent in predicting differences in response on a given day, controlling for the other measured constituent concentrations in the model. Finally, an R(2) analysis compared the relative importance of exposure scenario, plant, and constituent concentrations on each outcome. Peak expiratory flow (PEF) is used to demonstrate how the multiple levels of the analysis complement each other to assess constituents most strongly associated with health effects.

Strengthening the weak link: Built Environment modelling for loss analysis

NASA Astrophysics Data System (ADS)

Millinship, I.

2012-04-01

Methods to analyse insured losses from a range of natural perils, including pricing by primary insurers and catastrophe modelling by reinsurers, typically lack sufficient exposure information. Understanding the hazard intensity in terms of spatial severity and frequency is only the first step towards quantifying the risk of a catastrophic event. For any given event we need to know: Are any structures affected? What type of buildings are they? How much damaged occurred? How much will the repairs cost? To achieve this, detailed exposure information is required to assess the likely damage and to effectively calculate the resultant loss. Modelling exposures in the Built Environment therefore plays as important a role in understanding re/insurance risk as characterising the physical hazard. Across both primary insurance books and aggregated reinsurance portfolios, the location of a property (a risk) and its monetary value is typically known. Exactly what that risk is in terms of detailed property descriptors including structure type and rebuild cost - and therefore its vulnerability to loss - is often omitted. This data deficiency is a primary source of variations between modelled losses and the actual claims value. Built Environment models are therefore required at a high resolution to describe building attributes that relate vulnerability to property damage. However, national-scale household-level datasets are often not computationally practical in catastrophe models and data must be aggregated. In order to provide more accurate risk analysis, we have developed and applied a methodology for Built Environment modelling for incorporation into a range of re/insurance applications, including operational models for different international regions and different perils and covering residential, commercial and industry exposures. Illustrated examples are presented, including exposure modelling suitable for aggregated reinsurance analysis for the UK and bespoke high resolution modelling for industrial sites in Germany. A range of attributes are included following detailed claims analysis and engineering research with property type, age and condition identified as important differentiators of damage from flood, wind and freeze events.

Lung Cancer Mortality (1950–1999) among Eldorado Uranium Workers: A Comparison of Models of Carcinogenesis and Empirical Excess Risk Models

PubMed Central

Eidemüller, Markus; Jacob, Peter; Lane, Rachel S. D.; Frost, Stanley E.; Zablotska, Lydia B.

2012-01-01

Lung cancer mortality after exposure to radon decay products (RDP) among 16,236 male Eldorado uranium workers was analyzed. Male workers from the Beaverlodge and Port Radium uranium mines and the Port Hope radium and uranium refinery and processing facility who were first employed between 1932 and 1980 were followed up from 1950 to 1999. A total of 618 lung cancer deaths were observed. The analysis compared the results of the biologically-based two-stage clonal expansion (TSCE) model to the empirical excess risk model. The spontaneous clonal expansion rate of pre-malignant cells was reduced at older ages under the assumptions of the TSCE model. Exposure to RDP was associated with increase in the clonal expansion rate during exposure but not afterwards. The increase was stronger for lower exposure rates. A radiation-induced bystander effect could be a possible explanation for such an exposure response. Results on excess risks were compared to a linear dose-response parametric excess risk model with attained age, time since exposure and dose rate as effect modifiers. In all models the excess relative risk decreased with increasing attained age, increasing time since exposure and increasing exposure rate. Large model uncertainties were found in particular for small exposure rates. PMID:22936975

Biomarker Utility Analysis Using an Exposure-PBPK/PD Model: A Carbaryl Case Study

EPA Science Inventory

There are two common biomarkers: markers of exposure and markers of health effects. The strength of the correlation between exposure or effect and a biomarker measurement determines the utility of a biomarker for assessing exposures or risks. In the current study, a linked expo...

Children's Lead Exposure: A Multimedia Modeling Analysis to Guide Public Health Decision-Making.

PubMed

Zartarian, Valerie; Xue, Jianping; Tornero-Velez, Rogelio; Brown, James

2017-09-12

Drinking water and other sources for lead are the subject of public health concerns around the Flint, Michigan, drinking water and East Chicago, Indiana, lead in soil crises. In 2015, the U.S. Environmental Protection Agency (EPA)'s National Drinking Water Advisory Council (NDWAC) recommended establishment of a "health-based, household action level" for lead in drinking water based on children's exposure. The primary objective was to develop a coupled exposure-dose modeling approach that can be used to determine what drinking water lead concentrations keep children's blood lead levels (BLLs) below specified values, considering exposures from water, soil, dust, food, and air. Related objectives were to evaluate the coupled model estimates using real-world blood lead data, to quantify relative contributions by the various media, and to identify key model inputs. A modeling approach using the EPA's Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia and Integrated Exposure Uptake and Biokinetic (IEUBK) models was developed using available data. This analysis for the U.S. population of young children probabilistically simulated multimedia exposures and estimated relative contributions of media to BLLs across all population percentiles for several age groups. Modeled BLLs compared well with nationally representative BLLs (0-23% relative error). Analyses revealed relative importance of soil and dust ingestion exposure pathways and associated Pb intake rates; water ingestion was also a main pathway, especially for infants. This methodology advances scientific understanding of the relationship between lead concentrations in drinking water and BLLs in children. It can guide national health-based benchmarks for lead and related community public health decisions. https://doi.org/10.1289/EHP1605.

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

PubMed Central

2010-01-01

Background The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Methods/Design Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Discussion Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis. PMID:20950449

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes.

PubMed

Ribeiro, Manuel C; Pereira, Maria J; Soares, Amílcar; Branquinho, Cristina; Augusto, Sofia; Llop, Esteve; Fonseca, Susana; Nave, Joaquim G; Tavares, António B; Dias, Carlos M; Silva, Ana; Selemane, Ismael; de Toro, Joaquin; Santos, Mário J; Santos, Fernanda

2010-10-15

The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.

Evaluation of High-Throughput Chemical Exposure Models via Analysis of Matched Environmental and Biological Media Measurements

EPA Science Inventory

The U.S. EPA, under its ExpoCast program, is developing high-throughput near-field modeling methods to estimate human chemical exposure and to provide real-world context to high-throughput screening (HTS) hazard data. These novel modeling methods include reverse methods to infer ...

Validity of empirical models of exposure in asphalt paving

PubMed Central

Burstyn, I; Boffetta, P; Burr, G; Cenni, A; Knecht, U; Sciarra, G; Kromhout, H

2002-01-01

Aims: To investigate the validity of empirical models of exposure to bitumen fume and benzo(a)pyrene, developed for a historical cohort study of asphalt paving in Western Europe. Methods: Validity was evaluated using data from the USA, Italy, and Germany not used to develop the original models. Correlation between observed and predicted exposures was examined. Bias and precision were estimated. Results: Models were imprecise. Furthermore, predicted bitumen fume exposures tended to be lower (-70%) than concentrations found during paving in the USA. This apparent bias might be attributed to differences between Western European and USA paving practices. Evaluation of the validity of the benzo(a)pyrene exposure model revealed a similar to expected effect of re-paving and a larger than expected effect of tar use. Overall, benzo(a)pyrene models underestimated exposures by 51%. Conclusions: Possible bias as a result of underestimation of the impact of coal tar on benzo(a)pyrene exposure levels must be explored in sensitivity analysis of the exposure–response relation. Validation of the models, albeit limited, increased our confidence in their applicability to exposure assessment in the historical cohort study of cancer risk among asphalt workers. PMID:12205236

Appraisal of levels and patterns of occupational exposure to 1,3-butadiene.

PubMed

Scarselli, Alberto; Corfiati, Marisa; Di Marzi, Davide; Iavicoli, Sergio

2017-09-01

Objectives 1,3-butadiene is classified as carcinogenic to human by inhalation and the association with leukemia has been observed in several epidemiological studies. The aim of this study was to evaluate data about occupational exposure levels to 1,3-butadiene in the Italian working force. Methods Airborne concentrations of 1,3-butadiene were extracted from the Italian database on occupational exposure to carcinogens in the period 1996-2015. Descriptive statistics were calculated for exposure-related variables. An analysis through linear mixed model was performed to determine factors influencing the exposure level. The probability of exceeding the exposure limit was predicted using a mixed-effects logistic model. Concurrent exposures with other occupational carcinogens were investigated using the two-step cluster analysis. Results The total number of exposure measurements selected was 23 885, with an overall arithmetic mean of 0.12 mg/m3. The economic sector with the highest number of measurements was manufacturing of chemicals (18 744). The most predictive variables of the exposure level resulted to be the occupational group and its interaction with the measurement year. The highest likelihood of exceeding the exposure limit was found in the manufacture of coke and refined petroleum products. Concurrent exposures were frequently detected, mainly with benzene, acrylonitrile and ethylene dichloride, and three main clusters were identified. Conclusions Exposure to 1,3-butadiene occurs in a wide variety of activity sectors and occupational groups. The use of several statistical analysis methods applied to occupational exposure databases can help to identify exposure situations at high risk for workers' health and better target preventive interventions and research projects.

High‐resolution trench photomosaics from image‐based modeling: Workflow and error analysis

USGS Publications Warehouse

Reitman, Nadine G.; Bennett, Scott E. K.; Gold, Ryan D.; Briggs, Richard; Duross, Christopher

2015-01-01

Photomosaics are commonly used to construct maps of paleoseismic trench exposures, but the conventional process of manually using image‐editing software is time consuming and produces undesirable artifacts and distortions. Herein, we document and evaluate the application of image‐based modeling (IBM) for creating photomosaics and 3D models of paleoseismic trench exposures, illustrated with a case‐study trench across the Wasatch fault in Alpine, Utah. Our results include a structure‐from‐motion workflow for the semiautomated creation of seamless, high‐resolution photomosaics designed for rapid implementation in a field setting. Compared with conventional manual methods, the IBM photomosaic method provides a more accurate, continuous, and detailed record of paleoseismic trench exposures in approximately half the processing time and 15%–20% of the user input time. Our error analysis quantifies the effect of the number and spatial distribution of control points on model accuracy. For this case study, an ∼87  m2 exposure of a benched trench photographed at viewing distances of 1.5–7 m yields a model with <2  cm root mean square error (rmse) with as few as six control points. Rmse decreases as more control points are implemented, but the gains in accuracy are minimal beyond 12 control points. Spreading control points throughout the target area helps to minimize error. We propose that 3D digital models and corresponding photomosaics should be standard practice in paleoseismic exposure archiving. The error analysis serves as a guide for future investigations that seek balance between speed and accuracy during photomosaic and 3D model construction.

USER MANUAL FOR EXPRESS, THE EXAMS-PRZM EXPOSURE SIMULATION SHELL

EPA Science Inventory

The Environmental Fate and Effects Division (EFED) of EPA's Office of Pesticide Programs(OPP) uses a suite of ORD simulation models for the exposure analysis portion of regulatory risk assessments. These models (PRZM, EXAMS, AgDisp) are complex, process-based simulation codes tha...

77 FR 10962 - Flazasulfuron; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-24

.../water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... reliable information.'' This includes exposure through drinking water and in residential settings, but does...

Space Shuttle and Space Station Radio Frequency (RF) Exposure Analysis

NASA Technical Reports Server (NTRS)

Hwu, Shian U.; Loh, Yin-Chung; Sham, Catherine C.; Kroll, Quin D.

2005-01-01

This paper outlines the modeling techniques and important parameters to define a rigorous but practical procedure that can verify the compliance of RF exposure to the NASA standards for astronauts and electronic equipment. The electromagnetic modeling techniques are applied to analyze RF exposure in Space Shuttle and Space Station environments with reasonable computing time and resources. The modeling techniques are capable of taking into account the field interactions with Space Shuttle and Space Station structures. The obtained results illustrate the multipath effects due to the presence of the space vehicle structures. It's necessary to include the field interactions with the space vehicle in the analysis for an accurate assessment of the RF exposure. Based on the obtained results, the RF keep out zones are identified for appropriate operational scenarios, flight rules and necessary RF transmitter constraints to ensure a safe operating environment and mission success.

Analysis of an Environmental Exposure Health Questionnaire in a Metropolitan Minority Population Utilizing Logistic Regression and Support Vector Machines

PubMed Central

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D.; Hood, Darryl B.; Skelton, Tyler

2014-01-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire. PMID:23395953

Analysis of an environmental exposure health questionnaire in a metropolitan minority population utilizing logistic regression and Support Vector Machines.

PubMed

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D; Hood, Darryl B; Skelton, Tyler

2013-02-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire.

[Applying temporally-adjusted land use regression models to estimate ambient air pollution exposure during pregnancy].

PubMed

Zhang, Y J; Xue, F X; Bai, Z P

2017-03-06

The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.

Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential

PubMed Central

Mitchell, Jade; Arnot, Jon A.; Jolliet, Olivier; Georgopoulos, Panos G.; Isukapalli, Sastry; Dasgupta, Surajit; Pandian, Muhilan; Wambaugh, John; Egeghy, Peter; Cohen Hubal, Elaine A.; Vallero, Daniel A.

2014-01-01

While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA’s need to develop novel approaches and tools for rapidly prioritizing chemicals, a “Challenge” was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA’s effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches. PMID:23707726

Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential.

PubMed

Mitchell, Jade; Arnot, Jon A; Jolliet, Olivier; Georgopoulos, Panos G; Isukapalli, Sastry; Dasgupta, Surajit; Pandian, Muhilan; Wambaugh, John; Egeghy, Peter; Cohen Hubal, Elaine A; Vallero, Daniel A

2013-08-01

While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA's need to develop novel approaches and tools for rapidly prioritizing chemicals, a "Challenge" was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA's effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches. Copyright © 2013 Elsevier B.V. All rights reserved.

Study of temperature distributions in wafer exposure process

NASA Astrophysics Data System (ADS)

Lin, Zone-Ching; Wu, Wen-Jang

During the exposure process of photolithography, wafer absorbs the exposure energy, which results in rising temperature and the phenomenon of thermal expansion. This phenomenon was often neglected due to its limited effect in the previous generation of process. However, in the new generation of process, it may very likely become a factor to be considered. In this paper, the finite element model for analyzing the transient behavior of the distribution of wafer temperature during exposure was established under the assumption that the wafer was clamped by a vacuum chuck without warpage. The model is capable of simulating the distribution of the wafer temperature under different exposure conditions. The flowchart of analysis begins with the simulation of transient behavior in a single exposure region to the variation of exposure energy, interval of exposure locations and interval of exposure time under continuous exposure to investigate the distribution of wafer temperature. The simulation results indicate that widening the interval of exposure locations has a greater impact in improving the distribution of wafer temperature than extending the interval of exposure time between neighboring image fields. Besides, as long as the distance between the field center locations of two neighboring exposure regions exceeds the straight distance equals to three image fields wide, the interacting thermal effect during wafer exposure can be ignored. The analysis flow proposed in this paper can serve as a supporting reference tool for engineers in planning exposure paths.

MIXED MODELS ANALYSIS OR URBANIZATION LEVEL ON CHLORPYRIFOS EXPOSURE

EPA Science Inventory

The National Human Exposure Assessment Survey (NHEXAS) pilot studies were conducted from 1995 through 1997 to examine human population exposure to a wide range of environmental contaminants. In one of the studies, NHEXAS-Maryland, a longitudinal design was used to repeatedly m...

77 FR 4248 - Cyazofamid; Pesticide Tolerances for Emergency Exemptions

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-27

.../water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... reliable information.'' This includes exposure through drinking water and in residential settings, but does...

Selection Criteria for Mathematical Models Used in Exposure Assessments: Atmospheric Dispersion Models

EPA Science Inventory

Before the U.S. Environmental Protection Agency issued the 1988 Guidelines for Estimating Exposures, it published proposed guidelines in the Federal Register for public review and comment. he guidelines are intended to give risk analysis a basic framework and the tools they need ...

Fetal exposure to propoxur and abnormal child neurodevelopment at 2 years of age

PubMed Central

Ostrea, Enrique M.; Reyes, Alexis; Villanueva-Uy, Esterlita; Pacifico, Rochelle; Benitez, Bernadette; Ramos, Essie; Bernardo, Rommel C.; Bielawski, Dawn M.; Delaney-Black, Virginia; Chiodo, Lisa; Janisse, James J.; Ager, Joel W.

2012-01-01

Objective Our aim was to determine the effects of fetal exposure to propoxur and pyrethroids, on child neurodevelopment at 2 years of age. Patients and Methods Mothers were prospectively recruited during mid-pregnancy in Bulacan, Philippines where multiple pesticides including propoxur, cyfluthrin, chlorpyrifos, cypermethrin, pretilachlor, bioallethrin, malathion, diazinon and transfluthrin are used. To detect prenatal exposure to these pesticides, maternal hair and blood, infant’s hair, cord blood, and meconium were analyzed for the pesticides by gas chromatography/mass spectrometry. Infants were examined at 2 years of age with 95.1% follow up rate and their neurodevelopment outcome was assessed by the Griffiths Mental Developmental Scale (N=754). Results Meconium analysis was the most sensitive method to detect fetal exposure to pesticides and exposure was highest for propoxur (21.3%) and the grouped pyrethroids (2.5% - bioallethrin, transfluthrin, cyfluthrin and cypermethrin). Path analysis modeling was performed to determine the effects of fetal exposure to propoxur and pyrethroids on the child’s neurodevelopment at 24 months of age while controlling for confounders. Only singletons and those with complete data for the path analysis were included (N=696). Using a path analysis model, there was a significant negative (β= −0.14, p<0.001) relationship between prenatal pesticide exposure to propoxur and motor development at 2 years of age after controlling for confounders, e.g., infant gender, socioeconomic status, maternal intelligence, home stimulation (HOME), postnatal exposure to propoxur and blood lead level at 2 years of age. Conclusion At 2 years of age, prenatal exposure to propoxur was associated with poorer motor development in children. PMID:22155319

Hair analysis for the biomonitoring of pesticide exposure: comparison with blood and urine in a rat model.

PubMed

Appenzeller, Brice M R; Hardy, Emilie M; Grova, Nathalie; Chata, Caroline; Faÿs, François; Briand, Olivier; Schroeder, Henri; Duca, Radu-Corneliu

2017-08-01

Urine and plasma have been used to date for the biomonitoring of exposure to pollutants and are still the preferred fluids for this purpose; however, these fluids mainly provide information on the short term and may present a high level of variability regarding pesticide concentrations, especially for nonpersistent compounds. Hair analysis may provide information about chronic exposure that is averaged over several months; therefore, this method has been proposed as an alternative to solely relying on these fluids. Although the possibility of detecting pesticides in hair has been demonstrated over the past few years, the unknown linkage between exposure and pesticides concentration in hair has limited the recognition of this matrix as a relevant tool for assessing human exposure. Based on a rat model in which there was controlled exposure to a mixture of pesticides composed of lindane, β-hexachlorocyclohexane, β-endosulfan, p,p'-DDT, p,p'-DDE, dieldrin, pentachlorophenol, diazinon, chlorpyrifos, cyhalothrin, permethrin, cypermethrin, propiconazole, fipronil, oxadiazon, diflufenican, trifluralin, carbofuran, and propoxur, the current work demonstrates the association between exposure intensity and resulting pesticide concentration in hair. We also compared the results obtained from a hair analysis to urine and plasma collected from the same rats. Hair, blood, and urine were collected from rats submitted to 90-day exposure by gavage to the aforementioned mixture of common pesticides at different levels. We observed a linear relationship between exposure intensity and the concentration of pesticides in the rats' hair (R Pearson 0.453-0.978, p < 0.01). A comparison with results from urine and plasma samples demonstrated the relevance of hair analysis and, for many chemicals, its superiority over using fluids for differentiating animals from different groups and for re-attributing animals to their correct groups of exposure based on pesticide concentrations in the matrix. Therefore, this study strongly supports hair analysis as a reliable tool to be used during epidemiological studies to investigate exposure-associated adverse health effects.

A review of air exchange rate models for air pollution exposure assessments.

PubMed

Breen, Michael S; Schultz, Bradley D; Sohn, Michael D; Long, Thomas; Langstaff, John; Williams, Ronald; Isaacs, Kristin; Meng, Qing Yu; Stallings, Casson; Smith, Luther

2014-11-01

A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.

Children’s Lead Exposure: A Multimedia Modeling Analysis to Guide Public Health Decision-Making

PubMed Central

Xue, Jianping; Tornero-Velez, Rogelio; Brown, James

2017-01-01

Background: Drinking water and other sources for lead are the subject of public health concerns around the Flint, Michigan, drinking water and East Chicago, Indiana, lead in soil crises. In 2015, the U.S. Environmental Protection Agency (EPA)’s National Drinking Water Advisory Council (NDWAC) recommended establishment of a “health-based, household action level” for lead in drinking water based on children’s exposure. Objectives: The primary objective was to develop a coupled exposure–dose modeling approach that can be used to determine what drinking water lead concentrations keep children’s blood lead levels (BLLs) below specified values, considering exposures from water, soil, dust, food, and air. Related objectives were to evaluate the coupled model estimates using real-world blood lead data, to quantify relative contributions by the various media, and to identify key model inputs. Methods: A modeling approach using the EPA’s Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia and Integrated Exposure Uptake and Biokinetic (IEUBK) models was developed using available data. This analysis for the U.S. population of young children probabilistically simulated multimedia exposures and estimated relative contributions of media to BLLs across all population percentiles for several age groups. Results: Modeled BLLs compared well with nationally representative BLLs (0–23% relative error). Analyses revealed relative importance of soil and dust ingestion exposure pathways and associated Pb intake rates; water ingestion was also a main pathway, especially for infants. Conclusions: This methodology advances scientific understanding of the relationship between lead concentrations in drinking water and BLLs in children. It can guide national health-based benchmarks for lead and related community public health decisions. https://doi.org/10.1289/EHP1605 PMID:28934096

GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice

PubMed Central

Dolinoy, Dana C.; Miranda, Marie Lynn

2004-01-01

The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines. PMID:15579419

Predicting dredging-associated effects to coral reefs in Apra Harbor, Guam - Part 1: Sediment exposure modeling.

PubMed

Gailani, Joseph Z; Lackey, Tahirih C; King, David B; Bryant, Duncan; Kim, Sung-Chan; Shafer, Deborah J

2016-03-01

Model studies were conducted to investigate the potential coral reef sediment exposure from dredging associated with proposed development of a deepwater wharf in Apra Harbor, Guam. The Particle Tracking Model (PTM) was applied to quantify the exposure of coral reefs to material suspended by the dredging operations at two alternative sites. Key PTM features include the flexible capability of continuous multiple releases of sediment parcels, control of parcel/substrate interaction, and the ability to efficiently track vast numbers of parcels. This flexibility has facilitated simulating the combined effects of sediment released from clamshell dredging and chiseling within Apra Harbor. Because the rate of material released into the water column by some of the processes is not well understood or known a priori, the modeling approach was to bracket parameters within reasonable ranges to produce a suite of potential results from multiple model runs. Sensitivity analysis to model parameters is used to select the appropriate parameter values for bracketing. Data analysis results include mapping the time series and the maximum values of sedimentation, suspended sediment concentration, and deposition rate. Data were used to quantify various exposure processes that affect coral species in Apra Harbor. The goal of this research is to develop a robust methodology for quantifying and bracketing exposure mechanisms to coral (or other receptors) from dredging operations. These exposure values were utilized in an ecological assessment to predict effects (coral reef impacts) from various dredging scenarios. Copyright © 2015. Published by Elsevier Ltd.

Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation

PubMed Central

McNally, Kevin; Cotton, Richard; Cocker, John; Jones, Kate; Bartels, Mike; Rick, David; Price, Paul; Loizou, George

2012-01-01

There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biological guidance values. Exposure reconstruction or reverse dosimetry is the retrospective interpretation of external exposure consistent with biomonitoring data. We investigated the integration of physiologically based pharmacokinetic modelling, global sensitivity analysis, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of inhalation exposure to m-xylene. We used exhaled breath and venous blood m-xylene and urinary 3-methylhippuric acid measurements from a controlled human volunteer study in order to evaluate the ability of our computational framework to predict known inhalation exposures. We also investigated the importance of model structure and dimensionality with respect to its ability to reconstruct exposure. PMID:22719759

Analysis of Biomarker Utility using a PBPK Model for Carbaryl

EPA Science Inventory

There are many types of biomarkers; the two common ones are biomarkers of exposure and biomarkers of effect. The utility of a biomarker for estimating exposures or predicting risks depends on the strength of the correlation between biomarker concentrations and exposure/effects. I...

HESI EXPOSURE FACTORS DATABASE FOR AGGREGATE AND CUMULATIVE RISK ASSESSMENT

EPA Science Inventory

In recent years, the risk analysis community has broadened its use of complex aggregate and cumulative residential exposure models (e.g., to meet the requirements of the 1996 Food Quality Protection Act). The value of these models is their ability to incorporate a range of inp...

Model of spacecraft atomic oxygen and solar exposure microenvironments

NASA Technical Reports Server (NTRS)

Bourassa, R. J.; Pippin, H. G.

1993-01-01

Computer models of environmental conditions in Earth orbit are needed for the following reasons: (1) derivation of material performance parameters from orbital test data, (2) evaluation of spacecraft hardware designs, (3) prediction of material service life, and (4) scheduling spacecraft maintenance. To meet these needs, Boeing has developed programs for modeling atomic oxygen (AO) and solar radiation exposures. The model allows determination of AO and solar ultraviolet (UV) radiation exposures for spacecraft surfaces (1) in arbitrary orientations with respect to the direction of spacecraft motion, (2) overall ranges of solar conditions, and (3) for any mission duration. The models have been successfully applied to prediction of experiment environments on the Long Duration Exposure Facility (LDEF) and for analysis of selected hardware designs for deployment on other spacecraft. The work on these models has been reported at previous LDEF conferences. Since publication of these reports, a revision has been made to the AO calculation for LDEF, and further work has been done on the microenvironments model for solar exposure.

Modelling the exposure to chemicals for risk assessment: a comprehensive library of multimedia and PBPK models for integration, prediction, uncertainty and sensitivity analysis - the MERLIN-Expo tool.

PubMed

Ciffroy, P; Alfonso, B; Altenpohl, A; Banjac, Z; Bierkens, J; Brochot, C; Critto, A; De Wilde, T; Fait, G; Fierens, T; Garratt, J; Giubilato, E; Grange, E; Johansson, E; Radomyski, A; Reschwann, K; Suciu, N; Tanaka, T; Tediosi, A; Van Holderbeke, M; Verdonck, F

2016-10-15

MERLIN-Expo is a library of models that was developed in the frame of the FP7 EU project 4FUN in order to provide an integrated assessment tool for state-of-the-art exposure assessment for environment, biota and humans, allowing the detection of scientific uncertainties at each step of the exposure process. This paper describes the main features of the MERLIN-Expo tool. The main challenges in exposure modelling that MERLIN-Expo has tackled are: (i) the integration of multimedia (MM) models simulating the fate of chemicals in environmental media, and of physiologically based pharmacokinetic (PBPK) models simulating the fate of chemicals in human body. MERLIN-Expo thus allows the determination of internal effective chemical concentrations; (ii) the incorporation of a set of functionalities for uncertainty/sensitivity analysis, from screening to variance-based approaches. The availability of such tools for uncertainty and sensitivity analysis aimed to facilitate the incorporation of such issues in future decision making; (iii) the integration of human and wildlife biota targets with common fate modelling in the environment. MERLIN-Expo is composed of a library of fate models dedicated to non biological receptor media (surface waters, soils, outdoor air), biological media of concern for humans (several cultivated crops, mammals, milk, fish), as well as wildlife biota (primary producers in rivers, invertebrates, fish) and humans. These models can be linked together to create flexible scenarios relevant for both human and wildlife biota exposure. Standardized documentation for each model and training material were prepared to support an accurate use of the tool by end-users. One of the objectives of the 4FUN project was also to increase the confidence in the applicability of the MERLIN-Expo tool through targeted realistic case studies. In particular, we aimed at demonstrating the feasibility of building complex realistic exposure scenarios and the accuracy of the modelling predictions through a comparison with actual measurements. Copyright © 2016 Elsevier B.V. All rights reserved.

Sea lice and salmon population dynamics: effects of exposure time for migratory fish.

PubMed

Krkosek, Martin; Morton, Alexandra; Volpe, John P; Lewis, Mark A

2009-08-07

The ecological impact of parasite transmission from fish farms is probably mediated by the migration of wild fishes, which determines the period of exposure to parasites. For Pacific salmon and the parasitic sea louse, Lepeophtheirus salmonis, analysis of the exposure period may resolve conflicting observations of epizootic mortality in field studies and parasite rejection in experiments. This is because exposure periods can differ by 2-3 orders of magnitude, ranging from months in the field to hours in experiments. We developed a mathematical model of salmon-louse population dynamics, parametrized by a study that monitored naturally infected juvenile salmon held in ocean enclosures. Analysis of replicated trials indicates that lice suffer high mortality, particularly during pre-adult stages. The model suggests louse populations rapidly decline following brief exposure of juvenile salmon, similar to laboratory study designs and data. However, when the exposure period lasts for several weeks, as occurs when juvenile salmon migrate past salmon farms, the model predicts that lice accumulate to abundances that can elevate salmon mortality and depress salmon populations. The duration of parasite exposure is probably critical to salmon-louse population dynamics, and should therefore be accommodated in coastal planning and management where fish farms are situated on wild fish migration routes.

PREMOR: a point reactor exposure model computer code for survey analysis of power plant performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vondy, D.R.

1979-10-01

The PREMOR computer code was written to exploit a simple, two-group point nuclear reactor power plant model for survey analysis. Up to thirteen actinides, fourteen fission products, and one lumped absorber nuclide density are followed over a reactor history. Successive feed batches are accounted for with provision for from one to twenty batches resident. The effect of exposure of each of the batches to the same neutron flux is determined.

A model to systematically employ professional judgment in the Bayesian Decision Analysis for a semiconductor industry exposure assessment.

PubMed

Torres, Craig; Jones, Rachael; Boelter, Fred; Poole, James; Dell, Linda; Harper, Paul

2014-01-01

Bayesian Decision Analysis (BDA) uses Bayesian statistics to integrate multiple types of exposure information and classify exposures within the exposure rating categorization scheme promoted in American Industrial Hygiene Association (AIHA) publications. Prior distributions for BDA may be developed from existing monitoring data, mathematical models, or professional judgment. Professional judgments may misclassify exposures. We suggest that a structured qualitative risk assessment (QLRA) method can provide consistency and transparency in professional judgments. In this analysis, we use a structured QLRA method to define prior distributions (priors) for BDA. We applied this approach at three semiconductor facilities in South Korea, and present an evaluation of the performance of structured QLRA for determination of priors, and an evaluation of occupational exposures using BDA. Specifically, the structured QLRA was applied to chemical agents in similar exposure groups to identify provisional risk ratings. Standard priors were developed for each risk rating before review of historical monitoring data. Newly collected monitoring data were used to update priors informed by QLRA or historical monitoring data, and determine the posterior distribution. Exposure ratings were defined by the rating category with the highest probability--i.e., the most likely. We found the most likely exposure rating in the QLRA-informed priors to be consistent with historical and newly collected monitoring data, and the posterior exposure ratings developed with QLRA-informed priors to be equal to or greater than those developed with data-informed priors in 94% of comparisons. Overall, exposures at these facilities are consistent with well-controlled work environments. That is, the 95th percentile of exposure distributions are ≤50% of the occupational exposure limit (OEL) for all chemical-SEG combinations evaluated; and are ≤10% of the limit for 94% of chemical-SEG combinations evaluated.

Modelling of human exposure to air pollution in the urban environment: a GPS-based approach.

PubMed

Dias, Daniela; Tchepel, Oxana

2014-03-01

The main objective of this work was the development of a new modelling tool for quantification of human exposure to traffic-related air pollution within distinct microenvironments by using a novel approach for trajectory analysis of the individuals. For this purpose, mobile phones with Global Positioning System technology have been used to collect daily trajectories of the individuals with higher temporal resolution and a trajectory data mining, and geo-spatial analysis algorithm was developed and implemented within a Geographical Information System to obtain time-activity patterns. These data were combined with air pollutant concentrations estimated for several microenvironments. In addition to outdoor, pollutant concentrations in distinct indoor microenvironments are characterised using a probabilistic approach. An example of the application for PM2.5 is presented and discussed. The results obtained for daily average individual exposure correspond to a mean value of 10.6 and 6.0-16.4 μg m(-3) in terms of 5th-95th percentiles. Analysis of the results shows that the use of point air quality measurements for exposure assessment will not explain the intra- and inter-variability of individuals' exposure levels. The methodology developed and implemented in this work provides time-sequence of the exposure events thus making possible association of the exposure with the individual activities and delivers main statistics on individual's air pollution exposure with high spatio-temporal resolution.

Development of hypertension after long-term exposure to static magnetic fields among workers from a magnetic resonance imaging device manufacturing facility.

PubMed

Bongers, Suzan; Slottje, Pauline; Kromhout, Hans

2018-07-01

To assess the association between long-term exposure to static magnetic fields (SMF) in a magnetic resonance imaging (MRI)-manufacturing environment and hypertension. In an occupational cohort of male workers (n = 538) of an MRI-manufacturing facility, the first and last available blood pressure measurements from the facility's medical surveillance scheme were associated with modeled cumulative exposure to SMF. Exposure modeling was based on linkage of individual job histories from the facility's personnel records with a facility specific historical job exposure matrix. Hypertension was defined as a systolic pressure of above 140 mm Hg and/or a diastolic blood pressure above 90 mm Hg. Logistic regression models were used to associate cumulative SMF exposure to hypertension while adjusting for age, body mass index and blood pressure at time of first blood pressure measurement. Stratified analysis by exposure duration was performed similarly. High cumulative exposure to SMF (≥ 7.4 K Tesla minutes) was positively associated with development of hypertension (Odds Ratio [OR] 2.32, 95% confidence interval [CI] 1.27 - 4.25, P = 0.006). Stratified analysis showed a stronger association for those with high cumulative SMF exposure within a period up to 10 years (OR 3.96, 95% CI 1.62 - 9.69, P = 0.003), but no significant association was found for (high) cumulative exposure accumulated in a period of 10 or more years. Our findings suggest SMF exposure intensity to be more important than exposure duration for the risk of developing hypertension. Our data revealed that exposure to high levels of MRI-related SMF during MRI-manufacturing might be associated with developing hypertension. Copyright © 2018 Elsevier Inc. All rights reserved.

Estimation of Particulate Mass and Manganese Exposure Levels among Welders

PubMed Central

Hobson, Angela; Seixas, Noah; Sterling, David; Racette, Brad A.

2011-01-01

Background: Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature. Methods: Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models. Results: A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data. Conclusions: This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data. PMID:20870928

Improvements in Modelling Bystander and Resident Exposure to Pesticide Spray Drift: Investigations into New Approaches for Characterizing the 'Collection Efficiency' of the Human Body.

PubMed

Butler Ellis, M Clare; Kennedy, Marc C; Kuster, Christian J; Alanis, Rafael; Tuck, Clive R

2018-05-28

The BREAM (Bystander and Resident Exposure Assessment Model) (Kennedy et al. in BREAM: A probabilistic bystander and resident exposure assessment model of spray drift from an agricultural boom sprayer. Comput Electron Agric 2012;88:63-71) for bystander and resident exposure to spray drift from boom sprayers has recently been incorporated into the European Food Safety Authority (EFSA) guidance for determining non-dietary exposures of humans to plant protection products. The component of BREAM, which relates airborne spray concentrations to bystander and resident dermal exposure, has been reviewed to identify whether it is possible to improve this and its description of variability captured in the model. Two approaches have been explored: a more rigorous statistical analysis of the empirical data and a semi-mechanistic model based on established studies combined with new data obtained in a wind tunnel. A statistical comparison between field data and model outputs was used to determine which approach gave the better prediction of exposures. The semi-mechanistic approach gave the better prediction of experimental data and resulted in a reduction in the proposed regulatory values for the 75th and 95th percentiles of the exposure distribution.

HEALTH AND ENVIRONMENTAL SCIENCES INSTITUTE'S EXPOSURE FACTORS DATABASE FOR AGGREGATE AND CUMULATIVE RISK ASSESSMENT

EPA Science Inventory

In recent years, the risk analysis community has broadened its use of complex aggregate and cumulative residential exposure models (e.g., to meet the requirements of the 1996 Food Quality Protection Act). The value of these models is their ability to incorporate a range of input...

Mercury Dispersion Modeling And Purge Ventilation Stack Height Determination For Tank 40H

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivera-Giboyeaux, A.

2017-05-19

The SRNL Atmospheric Technologies Group performed an analysis for mercury emissions from H-Tank Farm - Tank 40 ventilation system exhaust in order to assess whether the Short Term Exposure Limit (STEL), or Threshold Limit Value (TLV) levels for mercury will be exceeded during bulk sludge slurry mixing and sludge removal operations. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the main dispersion modelling tool for this analysis. The results indicated that a 45-foot stack is sufficient to raise the plume centerline from the Tank 40 release to prevent mercury exposure problems for any of the stackmore » discharge scenarios provided. However, a 42-foot stack at Tank 40 is sufficient to prevent mercury exposure concerns in all emission scenarios except the 50 mg/m 3 release. At a 42-foot stack height, values exceeding the exposure standards are only measured on receptors located above 34 feet.« less

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

PubMed

Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

2016-11-01

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

A European model and case studies for aggregate exposure assessment of pesticides.

PubMed

Kennedy, Marc C; Glass, C Richard; Bokkers, Bas; Hart, Andy D M; Hamey, Paul Y; Kruisselbrink, Johannes W; de Boer, Waldo J; van der Voet, Hilko; Garthwaite, David G; van Klaveren, Jacob D

2015-05-01

Exposures to plant protection products (PPPs) are assessed using risk analysis methods to protect public health. Traditionally, single sources, such as food or individual occupational sources, have been addressed. In reality, individuals can be exposed simultaneously to multiple sources. Improved regulation therefore requires the development of new tools for estimating the population distribution of exposures aggregated within an individual. A new aggregate model is described, which allows individual users to include as much, or as little, information as is available or relevant for their particular scenario. Depending on the inputs provided by the user, the outputs can range from simple deterministic values through to probabilistic analyses including characterisations of variability and uncertainty. Exposures can be calculated for multiple compounds, routes and sources of exposure. The aggregate model links to the cumulative dietary exposure model developed in parallel and is implemented in the web-based software tool MCRA. Case studies are presented to illustrate the potential of this model, with inputs drawn from existing European data sources and models. These cover exposures to UK arable spray operators, Italian vineyard spray operators, Netherlands users of a consumer spray and UK bystanders/residents. The model could also be adapted to handle non-PPP compounds. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Prioritizing Chemicals and Data Requirements for Screening-Level Exposure and Risk Assessment

PubMed Central

Brown, Trevor N.; Wania, Frank; Breivik, Knut; McLachlan, Michael S.

2012-01-01

Background: Scientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioritization is challenging because of the large number of chemicals requiring evaluation and limited data and resources. Objectives: We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments. Methods: We used a multimedia mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified. Results: Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients. Conclusions: Mechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner. PMID:23008278

Operational and environmental determinants of in-vehicle CO and PM2.5 exposure.

PubMed

Alameddine, I; Abi Esber, L; Bou Zeid, E; Hatzopoulou, M; El-Fadel, M

2016-05-01

This study presents a modeling framework to quantify the complex roles that traffic, seasonality, vehicle characteristics, ventilation, meteorology, and ambient air quality play in dictating in-vehicle commuter exposure to CO and PM2.5. For this purpose, a comprehensive one-year monitoring program of 25 different variables was coupled with a multivariate regression analysis to develop models to predict in-vehicle CO and PM2.5 exposure using a database of 119 mobile tests and 120 fume leakage tests. The study aims to improve the understanding of in-cabin exposure, as well as interior-exterior pollutant exchange. Model results highlighted the strong correlation between out-vehicle and in-vehicle concentrations, with the effect of ventilation type only discerned for PM2.5 levels. Car type, road conditions, as well as meteorological conditions all played a significant role in modulating in-vehicle exposure. The CO and PM2.5 exposure models were able to explain 72 and 92% of the variability in measured concentrations, respectively. Both models exhibited robustness and no-evidence of over-fitting. Copyright © 2016 Elsevier B.V. All rights reserved.

Vessel Noise Affects Beaked Whale Behavior: Results of a Dedicated Acoustic Response Study

DTIC Science & Technology

2012-08-01

the analysis. Gaussian Models Shapiro-Wilk test (Normality) Breusch - Pagan test (Heteroscedasticity) Durbin-Watson test (Independence) Foraging duration...noise) may disrupt behavior. An experiment involving the exposure of target whale groups to intense vessel-generated noise tested how these exposures...exposure of target whale groups to intense vessel-generated noise tested how these exposures influenced the foraging behavior of Blainville?s beaked

A Bayesian Model and Stochastic Exposure (Dose) Estimation for Relative Exposure Risk Comparison Involving Asbestos-Containing Dropped Ceiling Panel Installation and Maintenance Tasks.

PubMed

Boelter, Fred W; Xia, Yulin; Persky, Jacob D

2017-09-01

Assessing exposures to hazards in order to characterize risk is at the core of occupational hygiene. Our study examined dropped ceiling systems commonly used in schools and commercial buildings and lay-in ceiling panels that may have contained asbestos prior to the mid to late 1970s. However, most ceiling panels and tiles do not contain asbestos. Since asbestos risk relates to dose, we estimated the distribution of eight-hour TWA concentrations and one-year exposures (a one-year dose equivalent) to asbestos fibers (asbestos f/cc-years) for five groups of workers who may encounter dropped ceilings: specialists, generalists, maintenance workers, nonprofessional do-it-yourself (DIY) persons, and other tradespersons who are bystanders to ceiling work. Concentration data (asbestos f/cc) were obtained through two exposure assessment studies in the field and one chamber study. Bayesian and stochastic models were applied to estimate distributions of eight-hour TWAs and annual exposures (dose). The eight-hour TWAs for all work categories were below current and historic occupational exposure limits (OELs). Exposures to asbestos fibers from dropped ceiling work would be categorized as "highly controlled" for maintenance workers and "well controlled" for remaining work categories, according to the American Industrial Hygiene Association exposure control rating system. Annual exposures (dose) were found to be greatest for specialists, followed by maintenance workers, generalists, bystanders, and DIY. On a comparative basis, modeled dose and thus risk from dropped ceilings for all work categories were orders of magnitude lower than published exposures for other sources of banned friable asbestos-containing building material commonly encountered in construction trades. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Assessment on personal exposure to particulate compounds using an empirical exposure model in an elderly community in Tianjin, China.

PubMed

Xu, Jia; Zhang, Nan; Han, Bin; You, Yan; Zhou, Jian; Zhang, Jiefeng; Niu, Can; Liu, Yating; He, Fei; Ding, Xiao; Bai, Zhipeng

2016-12-01

Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (F inf ) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (F pex ) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300μg/m 3 ), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of F pex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds. Copyright © 2016 Elsevier B.V. All rights reserved.

Probabilistic assessment of wildfire hazard and municipal watershed exposure

Treesearch

Joe Scott; Don Helmbrecht; Matthew P. Thompson; David E. Calkin; Kate Marcille

2012-01-01

The occurrence of wildfires within municipal watersheds can result in significant impacts to water quality and ultimately human health and safety. In this paper, we illustrate the application of geospatial analysis and burn probability modeling to assess the exposure of municipal watersheds to wildfire. Our assessment of wildfire exposure consists of two primary...

Prioritization of pesticides based on daily dietary exposure potential as determined from the SHEDS model.

PubMed

Melnyk, Lisa Jo; Wang, Zhaohui; Li, Zhilin; Xue, Jianping

2016-10-01

A major pathway for exposure to many pesticides is through diet. The objectives were to rank pesticides by comparing their calculated daily dietary exposure as determined by EPA's Stochastic Human Exposure and Dose Simulation (SHEDS) to single pesticides for different age groups to acceptable daily intakes (ADI), characterize pesticide trends in exposures over different time periods, and determine commodities contributing to pesticide exposures. SHEDS was applied, using Pesticide Data Program (PDP) (1991-2011) and pesticide usage data on crops from USDA combined with NHANES dietary consumption data, to generate exposure estimates by age group. ADI data collected from EPA, WHO, and other sources were used to rank pesticides based on relativeness of the dietary exposure potential to ADI by age groups. Sensitivity analysis provided trends in pesticide exposures. Within SHEDS, commodities contributing the majority of pesticides with greatest exposure potential were determined. The results indicated that the highest ranking pesticides were methamidophos and diazinon which exceeded 100% of the ADI. Sensitivity analysis indicated that exposure to methamidophos, diazinon, malathion, ethion and formetanate hydrochloride had a marked decrease from 1991-1999 to 2000-2011. Contributions analysis indicated that apples, mushroom, carrots, and lettuce contributed to diazinon exposure. Beans and pepper contributed to methamidophos exposure. Published by Elsevier Ltd.

In vivo Assessment and Potential Diagnosis of Xenobiotics that Perturb the Thyroid Pathway: Proteomic Analysis of Xenopus laevis Brain Tissue following Exposure to Model T4 Inhibitors

EPA Science Inventory

As part of a multi-endpoint systems approach to develop comprehensive methods for assessing endocrine stressors in vertebrates, differential protein profiling was used to investigate expression profiles in the brain of an amphibian model (Xenopus laevis) following in vivo exposur...

Mediation analysis with time varying exposures and mediators

PubMed Central

VanderWeele, Tyler J.; Tchetgen Tchetgen, Eric J.

2016-01-01

Summary In this paper we consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are time-varying confounders affected by prior exposure and mediator, natural direct and indirect effects are not identified. However, we define a randomized interventional analogue of natural direct and indirect effects that are identified in this setting. The formula that identifies these effects we refer to as the “mediational g-formula.” When there is no mediation, the mediational g-formula reduces to Robins’ regular g-formula for longitudinal data. When there are no time-varying confounders affected by prior exposure and mediator values, then the mediational g-formula reduces to a longitudinal version of Pearl’s mediation formula. However, the mediational g-formula itself can accommodate both mediation and time-varying confounders and constitutes a general approach to mediation analysis with time-varying exposures and mediators. PMID:28824285

Mediation analysis with time varying exposures and mediators.

PubMed

VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J

2017-06-01

In this paper we consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are time-varying confounders affected by prior exposure and mediator, natural direct and indirect effects are not identified. However, we define a randomized interventional analogue of natural direct and indirect effects that are identified in this setting. The formula that identifies these effects we refer to as the "mediational g-formula." When there is no mediation, the mediational g-formula reduces to Robins' regular g-formula for longitudinal data. When there are no time-varying confounders affected by prior exposure and mediator values, then the mediational g-formula reduces to a longitudinal version of Pearl's mediation formula. However, the mediational g-formula itself can accommodate both mediation and time-varying confounders and constitutes a general approach to mediation analysis with time-varying exposures and mediators.

A modular Human Exposure Model (HEM) framework to ...

EPA Pesticide Factsheets

Life Cycle Impact Analysis (LCIA) has proven to be a valuable tool for systematically comparing processes and products, and has been proposed for use in Chemical Alternatives Analysis (CAA). The exposure assessment portion of the human health impact scores of LCIA has historically focused on far-field sources (environmentally mediated exposures) while research has shown that use related exposures, (near-field exposures) typically dominate population exposure. Characterizing the human health impacts of chemicals in consumer products over the life cycle of these products requires an evaluation of both near-field as well far-field sources. Assessing the impacts of the near-field exposures requires bridging the scientific and technical gaps that currently prevent the harmonious use of the best available methods and tools from the fields of LCIA and human health exposure and risk assessment. The U.S. EPA’s Chemical Safety and Sustainability LC-HEM project is developing the Human Exposure Model (HEM) to assess near-field exposures to chemicals that occur to various populations over the life cycle of a commercial product. The HEM will be a publically available, web-based, modular system which will allow for the evaluation of chemical/product impacts in a LCIA framework to support CAA. We present here an overview of the framework for the modular HEM system. The framework includes a data flow diagram of in-progress and future planned modules, the definition of each mod

Early-life Sodium-exposure Unmasks Susceptibility to Stroke in hyperlipidemic-hypertensive Tg[hCETP]25-Rats

PubMed Central

Decano, Julius L.; Viereck, Jason C.; McKee, Ann C.; Hamilton, James A.; Ruiz-Opazo, Nelson; Herrera, Victoria L.M.

2009-01-01

Background Early-life risk factor exposure increases aortic atherosclerosis and blood pressure in humans and animal models, however, limited insight has been made into end-organ complications. Methods and Results We investigated the effects of early-life Na-exposure (0.23% vs 0.4%NaCl regular-rat chow) on vascular disease outcomes using the inbred, transgenic[hCETP]25 Dahl salt-sensitive hypertensive rat model of male-predominant coronary atherosclerosis, Tg25. Rather than the expected increased coronary heart disease, fetal 0.4%Na-exposure (≤2g-Na/2000cal/diet/day) induced adult-onset stroke in both sexes (ANOVA P<0.0001), with earlier stroke-onset in Tg25-females. Analysis of later onsets of 0.4%Na-exposure resulted in decreased stroke-risk and later stroke-onsets, despite longer 0.4%Na-exposure durations, indicating increasing risk with earlier onsets of 0.4%Na-exposure. Histological analysis of stroke+rat brains revealed cerebral cortical hemorrhagic infarctions, microhemorrhages, neuronal ischemia, microvascular injury. Ex-vivo MRI of stroke+ rat brains detected cerebral hemorrhages, microhemorrhages and ischemia with middle cerebral artery-distribution, and cerebellar non-involvement. Ultrasound micro-imaging detected carotid artery disease. Pre-stroke analysis detected neuronal ischemia, and decreased mass of isolated cerebral, but not cerebellar, microvessels. Conclusions Early-life Na-exposure exacerbated hypertension and unmasked stroke susceptibility with greater female vulnerability in hypertensive-hyperlipidemic Tg25-rats. The reproducible modeling in Tg25sp rats of carotid artery disease, cerebral hemorrhagic-infarctions, neuronal ischemia, microhemorrhages, and microvascular alterations suggests a pathogenic spectrum with causal interrelationships. This “mixed-stroke” spectrum could represent paradigms of ischemic-hemorrhagic transformation, and/or a microangiopathic basis for the association of ischemic-lesions, microhemorrhages, and strokes in humans. Altogether, the data reveal early-life Na-exposure as a significant modifier of hypertension and stroke disease-course, hence a potential modifiable prevention target deserving systematic study. PMID:19273719

High-Throughput Models for Exposure-Based Chemical ...

EPA Pesticide Factsheets

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlie

QMRA for Drinking Water: 1. Revisiting the Mathematical Structure of Single-Hit Dose-Response Models.

PubMed

Nilsen, Vegard; Wyller, John

2016-01-01

Dose-response models are essential to quantitative microbial risk assessment (QMRA), providing a link between levels of human exposure to pathogens and the probability of negative health outcomes. In drinking water studies, the class of semi-mechanistic models known as single-hit models, such as the exponential and the exact beta-Poisson, has seen widespread use. In this work, an attempt is made to carefully develop the general mathematical single-hit framework while explicitly accounting for variation in (1) host susceptibility and (2) pathogen infectivity. This allows a precise interpretation of the so-called single-hit probability and precise identification of a set of statistical independence assumptions that are sufficient to arrive at single-hit models. Further analysis of the model framework is facilitated by formulating the single-hit models compactly using probability generating and moment generating functions. Among the more practically relevant conclusions drawn are: (1) for any dose distribution, variation in host susceptibility always reduces the single-hit risk compared to a constant host susceptibility (assuming equal mean susceptibilities), (2) the model-consistent representation of complete host immunity is formally demonstrated to be a simple scaling of the response, (3) the model-consistent expression for the total risk from repeated exposures deviates (gives lower risk) from the conventional expression used in applications, and (4) a model-consistent expression for the mean per-exposure dose that produces the correct total risk from repeated exposures is developed. © 2016 Society for Risk Analysis.

Dermal Exposure Assessment to Pesticides in Farming Systems in Developing Countries: Comparison of Models

PubMed Central

Lesmes Fabian, Camilo; Binder, Claudia R.

2015-01-01

In the field of occupational hygiene, researchers have been working on developing appropriate methods to estimate human exposure to pesticides in order to assess the risk and therefore to take the due decisions to improve the pesticide management process and reduce the health risks. This paper evaluates dermal exposure models to find the most appropriate. Eight models (i.e., COSHH, DERM, DREAM, EASE, PHED, RISKOFDERM, STOFFENMANAGER and PFAM) were evaluated according to a multi-criteria analysis and from these results five models (i.e., DERM, DREAM, PHED, RISKOFDERM and PFAM) were selected for the assessment of dermal exposure in the case study of the potato farming system in the Andean highlands of Vereda La Hoya, Colombia. The results show that the models provide different dermal exposure estimations which are not comparable. However, because of the simplicity of the algorithm and the specificity of the determinants, the DERM, DREAM and PFAM models were found to be the most appropriate although their estimations might be more accurate if specific determinants are included for the case studies in developing countries. PMID:25938911

Potential for Bias When Estimating Critical Windows for Air Pollution in Children's Health.

PubMed

Wilson, Ander; Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Wright, Robert O; Wright, Rosalind J; Coull, Brent A

2017-12-01

Evidence supports an association between maternal exposure to air pollution during pregnancy and children's health outcomes. Recent interest has focused on identifying critical windows of vulnerability. An analysis based on a distributed lag model (DLM) can yield estimates of a critical window that are different from those from an analysis that regresses the outcome on each of the 3 trimester-average exposures (TAEs). Using a simulation study, we assessed bias in estimates of critical windows obtained using 3 regression approaches: 1) 3 separate models to estimate the association with each of the 3 TAEs; 2) a single model to jointly estimate the association between the outcome and all 3 TAEs; and 3) a DLM. We used weekly fine-particulate-matter exposure data for 238 births in a birth cohort in and around Boston, Massachusetts, and a simulated outcome and time-varying exposure effect. Estimates using separate models for each TAE were biased and identified incorrect windows. This bias arose from seasonal trends in particulate matter that induced correlation between TAEs. Including all TAEs in a single model reduced bias. DLM produced unbiased estimates and added flexibility to identify windows. Analysis of body mass index z score and fat mass in the same cohort highlighted inconsistent estimates from the 3 methods. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effects of glyphosate exposure on sperm concentration in rodents: A systematic review and meta-analysis.

PubMed

Cai, Wenyan; Ji, Ying; Song, Xianping; Guo, Haoran; Han, Lei; Zhang, Feng; Liu, Xin; Zhang, Hengdong; Zhu, Baoli; Xu, Ming

2017-10-01

Correlation between exposure to glyphosate and sperm concentrations is important in reproductive toxicity risk assessment for male reproductive functions. Many studies have focused on reproductive toxicity on glyphosate, however, results are still controversial. We conducted a systematic review of epidemiological studies on the association between glyphosate exposure and sperm concentrations of rodents. The aim of this study is to explore the potential adverse effects of glyphosate on reproductive function of male rodents. Systematic and comprehensive literature search was performed in MEDLINE, TOXLINE, Embase, WANFANG and CNKI databases with different combinations of glyphosate exposure and sperm concentration. 8 studies were eventually identified and random-effect model was conducted. Heterogeneity among study results was calculated via chi-square tests. Ten independent experimental datasets from these eight studies were acquired to synthesize the random-effect model. A decrease in sperm concentrations was found with mean difference of sperm concentrations(MDsperm)=-2.774×10 6 /sperm/g/testis(95%CI=-0.969 to -4.579) in random-effect model after glyphosate exposure. There was also a significant decrease after fitting the random-effect model: MDsperm=-1.632×10 6 /sperm/g/testis (95%CI=-0.662 to -2.601). The results of meta-analysis support the hypothesis that glyphosate exposure decreased sperm concentration in rodents. Therefore, we conclude that glyphosate is toxic to male rodent's reproductive system. Copyright © 2017. Published by Elsevier B.V.

Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

Risk assessments using the Strain Index and the TLV for HAL, Part I: Task and multi-task job exposure classifications.

PubMed

Kapellusch, Jay M; Bao, Stephen S; Silverstein, Barbara A; Merryweather, Andrew S; Thiese, Mathew S; Hegmann, Kurt T; Garg, Arun

2017-12-01

The Strain Index (SI) and the American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Value for Hand Activity Level (TLV for HAL) use different constituent variables to quantify task physical exposures. Similarly, time-weighted-average (TWA), Peak, and Typical exposure techniques to quantify physical exposure from multi-task jobs make different assumptions about each task's contribution to the whole job exposure. Thus, task and job physical exposure classifications differ depending upon which model and technique are used for quantification. This study examines exposure classification agreement, disagreement, correlation, and magnitude of classification differences between these models and techniques. Data from 710 multi-task job workers performing 3,647 tasks were analyzed using the SI and TLV for HAL models, as well as with the TWA, Typical and Peak job exposure techniques. Physical exposures were classified as low, medium, and high using each model's recommended, or a priori limits. Exposure classification agreement and disagreement between models (SI, TLV for HAL) and between job exposure techniques (TWA, Typical, Peak) were described and analyzed. Regardless of technique, the SI classified more tasks as high exposure than the TLV for HAL, and the TLV for HAL classified more tasks as low exposure. The models agreed on 48.5% of task classifications (kappa = 0.28) with 15.5% of disagreement between low and high exposure categories. Between-technique (i.e., TWA, Typical, Peak) agreement ranged from 61-93% (kappa: 0.16-0.92) depending on whether the SI or TLV for HAL was used. There was disagreement between the SI and TLV for HAL and between the TWA, Typical and Peak techniques. Disagreement creates uncertainty for job design, job analysis, risk assessments, and developing interventions. Task exposure classifications from the SI and TLV for HAL might complement each other. However, TWA, Typical, and Peak job exposure techniques all have limitations. Part II of this article examines whether the observed differences between these models and techniques produce different exposure-response relationships for predicting prevalence of carpal tunnel syndrome.

The use of aquatic bioconcentration factors in ecological risk assessments: Confounding issues, laboratory v/s modeled results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brandt, C.; Blanton, M.L.; Dirkes, R.

1995-12-31

Bioconcentration in aquatic systems is generally taken to refer to contaminant uptake through non-ingestion pathways (i.e., dermal and respiration uptake). Ecological risk assessments performed on aquatic systems often rely on published data on bioconcentration factors to calibrate models of exposure. However, many published BCFs, especially those from in situ studies, are confounded by uptake from ingestion of prey. As part of exposure assessment and risk analysis of the Columbia River`s Hanford Reach, the authors tested a methodology to estimate radionuclide BCFs for several aquatic species in the Hanford Reach of the Columbia River. The iterative methodology solves for BCFs frommore » known body burdens and environmental media concentrations. This paper provides BCF methodology description comparisons of BCF from literature and modeled values and how they were used in the exposure assessment and risk analysis of the Columbia River`s Hanford Reach.« less

On the use of a PM2.5 exposure simulator to explain birthweight

PubMed Central

Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.; Burke, Janet; Miranda, Marie Lynn

2010-01-01

In relating pollution to birth outcomes, maternal exposure has usually been described using monitoring data. Such characterization provides a misrepresentation of exposure as it (i) does not take into account the spatial misalignment between an individual’s residence and monitoring sites, and (ii) it ignores the fact that individuals spend most of their time indoors and typically in more than one location. In this paper, we break with previous studies by using a stochastic simulator to describe personal exposure (to particulate matter) and then relate simulated exposures at the individual level to the health outcome (birthweight) rather than aggregating to a selected spatial unit. We propose a hierarchical model that, at the first stage, specifies a linear relationship between birthweight and personal exposure, adjusting for individual risk factors and introduces random spatial effects for the census tract of maternal residence. At the second stage, our hierarchical model specifies the distribution of each individual’s personal exposure using the empirical distribution yielded by the stochastic simulator as well as a model for the spatial random effects. We have applied our framework to analyze birthweight data from 14 counties in North Carolina in years 2001 and 2002. We investigate whether there are certain aspects and time windows of exposure that are more detrimental to birthweight by building different exposure metrics which we incorporate, one by one, in our hierarchical model. To assess the difference in relating ambient exposure to birthweight versus personal exposure to birthweight, we compare estimates of the effect of air pollution obtained from hierarchical models that linearly relate ambient exposure and birthweight versus those obtained from our modeling framework. Our analysis does not show a significant effect of PM2.5 on birthweight for reasons which we discuss. However, our modeling framework serves as a template for analyzing the relationship between personal exposure and longer term health endpoints. PMID:21691413

Visible lesion thresholds and model predictions for Q-switched 1318-nm and 1540-nm laser exposures to porcine skin

NASA Astrophysics Data System (ADS)

Zohner, Justin J.; Schuster, Kurt J.; Chavey, Lucas J.; Stolarski, David J.; Kumru, Semih S.; Rockwell, Benjamin A.; Thomas, Robert J.; Cain, Clarence P.

2006-02-01

Skin damage thresholds were measured and compared with theoretical predictions using a skin thermal model for near-IR laser pulses at 1318 nm and 1540 nm. For the 1318-nm data, a Q-switched, 50-ns pulse with a spot size of 5 mm was applied to porcine skin and the damage thresholds were determined at 1 hour and 24 hours postexposure using Probit analysis. The same analysis was conducted for a Q-switched, 30-ns pulse at 1540 nm with a spot size of 5 mm. The Yucatan mini-pig was used as the skin model for human skin due to its similarity to pigmented human skin. The ED 50 for these skin exposures at 24 hours postexposure was 10.5 J/cm2 for the 1318-nm exposures, and 6.1 J/cm2 for the 1540-nm exposures. These results were compared to thermal model predictions. We show that the thermal model fails to account for the ED 50 values observed. A brief discussion of the possible causes of this discrepancy is presented. These thresholds are also compared with previously published skin minimum visible lesion (MVL) thresholds and with the ANSI Standard's MPE for 1318-nm lasers at 50 ns and 1540-nm lasers at 30 ns.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teng, S.; Tebby, C.

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-timemore » cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.« less

An empirical analysis of thermal protective performance of fabrics used in protective clothing.

PubMed

Mandal, Sumit; Song, Guowen

2014-10-01

Fabric-based protective clothing is widely used for occupational safety of firefighters/industrial workers. The aim of this paper is to study thermal protective performance provided by fabric systems and to propose an effective model for predicting the thermal protective performance under various thermal exposures. Different fabric systems that are commonly used to manufacture thermal protective clothing were selected. Laboratory simulations of the various thermal exposures were created to evaluate the protective performance of the selected fabric systems in terms of time required to generate second-degree burns. Through the characterization of selected fabric systems in a particular thermal exposure, various factors affecting the performances were statistically analyzed. The key factors for a particular thermal exposure were recognized based on the t-test analysis. Using these key factors, the performance predictive multiple linear regression and artificial neural network (ANN) models were developed and compared. The identified best-fit ANN models provide a basic tool to study thermal protective performance of a fabric. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Using the Integrative Model to Explain How Exposure to Sexual Media Content Influences Adolescent Sexual Behavior

PubMed Central

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin; Jordan, Amy

2017-01-01

Published research demonstrates an association between exposure to media sexual content and a variety of sex-related outcomes for adolescents. What is not known is the mechanism through which sexual content produces this “media effect” on adolescent beliefs, attitudes, and behavior. Using the Integrative Model of Behavioral Prediction, this paper uses data from a longitudinal study of adolescents ages 16–18 (n=460) to determine how exposure to sexual media content influences sexual behavior. Path analysis and structural equation modeling demonstrated that intention to engage in sexual intercourse is determined by a combination of attitudes, normative pressure, and self efficacy but that exposure to sexual media content only affects normative pressure beliefs. By applying the Integrative Model, we are able to identify which beliefs are influenced by exposure to media sex and improve the ability of health educators, researchers, and others to design effective messages for health communication campaigns and messages pertaining to adolescents’ engaging in sexual intercourse. PMID:21606378

A murine inhalation model to characterize pulmonary exposure to dry Aspergillus fumigatus conidia.

PubMed

Buskirk, Amanda D; Green, Brett J; Lemons, Angela R; Nayak, Ajay P; Goldsmith, W Travis; Kashon, Michael L; Anderson, Stacey E; Hettick, Justin M; Templeton, Steven P; Germolec, Dori R; Beezhold, Donald H

2014-01-01

Most murine models of fungal exposure are based on the delivery of uncharacterized extracts or liquid conidia suspensions using aspiration or intranasal approaches. Studies that model exposure to dry fungal aerosols using whole body inhalation have only recently been described. In this study, we aimed to characterize pulmonary immune responses following repeated inhalation of conidia utilizing an acoustical generator to deliver dry fungal aerosols to mice housed in a nose only exposure chamber. Immunocompetent female BALB/cJ mice were exposed to conidia derived from Aspergillus fumigatus wild-type (WT) or a melanin-deficient (Δalb1) strain. Conidia were aerosolized and delivered to mice at an estimated deposition dose of 1×105 twice a week for 4 weeks (8 total). Histopathological and immunological endpoints were assessed 4, 24, 48, and 72 hours after the final exposure. Histopathological analysis showed that conidia derived from both strains induced lung inflammation, especially at 24 and 48 hour time points. Immunological endpoints evaluated in bronchoalveolar lavage fluid (BALF) and the mediastinal lymph nodes showed that exposure to WT conidia led to elevated numbers of macrophages, granulocytes, and lymphocytes. Importantly, CD8+ IL17+ (Tc17) cells were significantly higher in BALF and positively correlated with germination of A. fumigatus WT spores. Germination was associated with specific IgG to intracellular proteins while Δalb1 spores elicited antibodies to cell wall hydrophobin. These data suggest that inhalation exposures may provide a more representative analysis of immune responses following exposures to environmentally and occupationally prevalent fungal contaminants.

Animal models of maternal high fat diet exposure and effects on metabolism in offspring: a meta-regression analysis.

PubMed

Ribaroff, G A; Wastnedge, E; Drake, A J; Sharpe, R M; Chambers, T J G

2017-06-01

Animal models of maternal high fat diet (HFD) demonstrate perturbed offspring metabolism although the effects differ markedly between models. We assessed studies investigating metabolic parameters in the offspring of HFD fed mothers to identify factors explaining these inter-study differences. A total of 171 papers were identified, which provided data from 6047 offspring. Data were extracted regarding body weight, adiposity, glucose homeostasis and lipidaemia. Information regarding the macronutrient content of diet, species, time point of exposure and gestational weight gain were collected and utilized in meta-regression models to explore predictive factors. Publication bias was assessed using Egger's regression test. Maternal HFD exposure did not affect offspring birthweight but increased weaning weight, final bodyweight, adiposity, triglyceridaemia, cholesterolaemia and insulinaemia in both female and male offspring. Hyperglycaemia was found in female offspring only. Meta-regression analysis identified lactational HFD exposure as a key moderator. The fat content of the diet did not correlate with any outcomes. There was evidence of significant publication bias for all outcomes except birthweight. Maternal HFD exposure was associated with perturbed metabolism in offspring but between studies was not accounted for by dietary constituents, species, strain or maternal gestational weight gain. Specific weaknesses in experimental design predispose many of the results to bias. © 2017 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.

MODELING OF HUMAN EXPOSURE TO IN-VEHICLE PM2.5 FROM ENVIRONMENTAL TOBACCO SMOKE

PubMed Central

Cao, Ye; Frey, H. Christopher

2012-01-01

Environmental tobacco smoke (ETS) is estimated to be a significant contributor to in-vehicle human exposure to fine particulate matter of 2.5 µm or smaller (PM2.5). A critical assessment was conducted of a mass balance model for estimating PM2.5 concentration with smoking in a motor vehicle. Recommendations for the range of inputs to the mass-balance model are given based on literature review. Sensitivity analysis was used to determine which inputs should be prioritized for data collection. Air exchange rate (ACH) and the deposition rate have wider relative ranges of variation than other inputs, representing inter-individual variability in operations, and inter-vehicle variability in performance, respectively. Cigarette smoking and emission rates, and vehicle interior volume, are also key inputs. The in-vehicle ETS mass balance model was incorporated into the Stochastic Human Exposure and Dose Simulation for Particulate Matter (SHEDS-PM) model to quantify the potential magnitude and variability of in-vehicle exposures to ETS. The in-vehicle exposure also takes into account near-road incremental PM2.5 concentration from on-road emissions. Results of probabilistic study indicate that ETS is a key contributor to the in-vehicle average and high-end exposure. Factors that mitigate in-vehicle ambient PM2.5 exposure lead to higher in-vehicle ETS exposure, and vice versa. PMID:23060732

Incorporating twitter-based human activity information in spatial analysis of crashes in urban areas.

PubMed

Bao, Jie; Liu, Pan; Yu, Hao; Xu, Chengcheng

2017-09-01

The primary objective of this study was to investigate how to incorporate human activity information in spatial analysis of crashes in urban areas using Twitter check-in data. This study used the data collected from the City of Los Angeles in the United States to illustrate the procedure. The following five types of data were collected: crash data, human activity data, traditional traffic exposure variables, road network attributes and social-demographic data. A web crawler by Python was developed to collect the venue type information from the Twitter check-in data automatically. The human activities were classified into seven categories by the obtained venue types. The collected data were aggregated into 896 Traffic Analysis Zones (TAZ). Geographically weighted regression (GWR) models were developed to establish a relationship between the crash counts reported in a TAZ and various contributing factors. Comparative analyses were conducted to compare the performance of GWR models which considered traditional traffic exposure variables only, Twitter-based human activity variables only, and both traditional traffic exposure and Twitter-based human activity variables. The model specification results suggested that human activity variables significantly affected the crash counts in a TAZ. The results of comparative analyses suggested that the models which considered both traditional traffic exposure and human activity variables had the best goodness-of-fit in terms of the highest R 2 and lowest AICc values. The finding seems to confirm the benefits of incorporating human activity information in spatial analysis of crashes using Twitter check-in data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation and recommendation of sensitivity analysis methods for application to Stochastic Human Exposure and Dose Simulation models.

PubMed

Mokhtari, Amirhossein; Christopher Frey, H; Zheng, Junyu

2006-11-01

Sensitivity analyses of exposure or risk models can help identify the most significant factors to aid in risk management or to prioritize additional research to reduce uncertainty in the estimates. However, sensitivity analysis is challenged by non-linearity, interactions between inputs, and multiple days or time scales. Selected sensitivity analysis methods are evaluated with respect to their applicability to human exposure models with such features using a testbed. The testbed is a simplified version of a US Environmental Protection Agency's Stochastic Human Exposure and Dose Simulation (SHEDS) model. The methods evaluated include the Pearson and Spearman correlation, sample and rank regression, analysis of variance, Fourier amplitude sensitivity test (FAST), and Sobol's method. The first five methods are known as "sampling-based" techniques, wheras the latter two methods are known as "variance-based" techniques. The main objective of the test cases was to identify the main and total contributions of individual inputs to the output variance. Sobol's method and FAST directly quantified these measures of sensitivity. Results show that sensitivity of an input typically changed when evaluated under different time scales (e.g., daily versus monthly). All methods provided similar insights regarding less important inputs; however, Sobol's method and FAST provided more robust insights with respect to sensitivity of important inputs compared to the sampling-based techniques. Thus, the sampling-based methods can be used in a screening step to identify unimportant inputs, followed by application of more computationally intensive refined methods to a smaller set of inputs. The implications of time variation in sensitivity results for risk management are briefly discussed.

Fumonisin B1 Toxicity in Grower-Finisher Pigs: A Comparative Analysis of Genetically Engineered Bt Corn and non-Bt Corn by Using Quantitative Dietary Exposure Assessment Modeling

PubMed Central

Delgado, James E.; Wolt, Jeffrey D.

2011-01-01

In this study, we investigate the long-term exposure (20 weeks) to fumonisin B1 (FB1) in grower-finisher pigs by conducting a quantitative exposure assessment (QEA). Our analytical approach involved both deterministic and semi-stochastic modeling for dietary comparative analyses of FB1 exposures originating from genetically engineered Bacillus thuringiensis (Bt)-corn, conventional non-Bt corn and distiller’s dried grains with solubles (DDGS) derived from Bt and/or non-Bt corn. Results from both deterministic and semi-stochastic demonstrated a distinct difference of FB1 toxicity in feed between Bt corn and non-Bt corn. Semi-stochastic results predicted the lowest FB1 exposure for Bt grain with a mean of 1.5 mg FB1/kg diet and the highest FB1 exposure for a diet consisting of non-Bt grain and non-Bt DDGS with a mean of 7.87 mg FB1/kg diet; the chronic toxicological incipient level of concern is 1.0 mg of FB1/kg of diet. Deterministic results closely mirrored but tended to slightly under predict the mean result for the semi-stochastic analysis. This novel comparative QEA model reveals that diet scenarios where the source of grain is derived from Bt corn presents less potential to induce FB1 toxicity than diets containing non-Bt corn. PMID:21909298

Analysis of intervention strategies for inhalation exposure to polycyclic aromatic hydrocarbons and associated lung cancer risk based on a Monte Carlo population exposure assessment model.

PubMed

Zhou, Bin; Zhao, Bin

2014-01-01

It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs), a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF) and potential impact fraction (PIF) of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making.

Atmospheric pollutants and hospital admissions due to pneumonia in children

PubMed Central

Negrisoli, Juliana; Nascimento, Luiz Fernando C.

2013-01-01

OBJECTIVE: To analyze the relationship between exposure to air pollutants and hospitalizations due to pneumonia in children of Sorocaba, São Paulo, Brazil. METHODS: Time series ecological study, from 2007 to 2008. Daily data were obtained from the State Environmental Agency for Pollution Control for particulate matter, nitric oxide, nitrogen dioxide, ozone, besides air temperature and relative humidity. The data concerning pneumonia admissions were collected in the public health system of Sorocaba. Correlations between the variables of interest using Pearson cofficient were calculated. Models with lags from zero to five days after exposure to pollutants were performed to analyze the association between the exposure to environmental pollutants and hospital admissions. The analysis used the generalized linear model of Poisson regression, being significant p<0.05. RESULTS: There were 1,825 admissions for pneumonia, with a daily mean of 2.5±2.1. There was a strong correlation between pollutants and hospital admissions, except for ozone. Regarding the Poisson regression analysis with the multi-pollutant model, only nitrogen dioxide was statistically significant in the same day (relative risk - RR=1.016), as well as particulate matter with a lag of four days (RR=1.009) after exposure to pollutants. CONCLUSIONS: There was an acute effect of exposure to nitrogen dioxide and a later effect of exposure to particulate matter on children hospitalizations for pneumonia in Sorocaba. PMID:24473956

The properties of human body phantoms used in calculations of electromagnetic fields exposure by wireless communication handsets or hand-operated industrial devices.

PubMed

Zradziński, Patryk

2013-06-01

According to international guidelines, the assessment of biophysical effects of exposure to electromagnetic fields (EMF) generated by hand-operated sources needs the evaluation of induced electric field (E(in)) or specific energy absorption rate (SAR) caused by EMF inside a worker's body and is usually done by the numerical simulations with different protocols applied to these two exposure cases. The crucial element of these simulations is the numerical phantom of the human body. Procedures of E(in) and SAR evaluation due to compliance analysis with exposure limits have been defined in Institute of Electrical and Electronics Engineers standards and International Commission on Non-Ionizing Radiation Protection guidelines, but a detailed specification of human body phantoms has not been described. An analysis of the properties of over 30 human body numerical phantoms was performed which has been used in recently published investigations related to the assessment of EMF exposure by various sources. The differences in applicability of these phantoms in the evaluation of E(in) and SAR while operating industrial devices and SAR while using mobile communication handsets are discussed. The whole human body numerical phantom dimensions, posture, spatial resolution and electric contact with the ground constitute the key parameters in modeling the exposure related to industrial devices, while modeling the exposure from mobile communication handsets, which needs only to represent the exposed part of the human body nearest to the handset, mainly depends on spatial resolution of the phantom. The specification and standardization of these parameters of numerical human body phantoms are key requirements to achieve comparable and reliable results from numerical simulations carried out for compliance analysis against exposure limits or within the exposure assessment in EMF-related epidemiological studies.

Polynomial Chaos decomposition applied to stochastic dosimetry: study of the influence of the magnetic field orientation on the pregnant woman exposure at 50 Hz.

PubMed

Liorni, I; Parazzini, M; Fiocchi, S; Guadagnin, V; Ravazzani, P

2014-01-01

Polynomial Chaos (PC) is a decomposition method used to build a meta-model, which approximates the unknown response of a model. In this paper the PC method is applied to the stochastic dosimetry to assess the variability of human exposure due to the change of the orientation of the B-field vector respect to the human body. In detail, the analysis of the pregnant woman exposure at 7 months of gestational age is carried out, to build-up a statistical meta-model of the induced electric field for each fetal tissue and in the fetal whole-body by means of the PC expansion as a function of the B-field orientation, considering a uniform exposure at 50 Hz.

Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

PubMed

Cao, Ying; Rajan, Suja S; Wei, Peng

2016-12-01

A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.

A MULTISTAGE BIOLOGICALLY BASED MATHEMATICAL MODEL FOR MOUSE LIVER TUMORS INDUCED BY DICHLOROACETIC ACID (DCA) - EXPLORATION OF THE MODEL

EPA Science Inventory

A biologically based mathematical model for the induction of liver tumors in mice by dichloroacetic acid (DCA) has been developed from histopathologic analysis of the livers of exposed mice. This analysis suggests that following chronic exposure to DCA, carcinomas can arise dire...

Electromagnetic absorption in a multilayered slab model of tissue under near-field exposure conditions.

PubMed

Chatterjee, I; Hagmann, M J; Gandhi, O P

1980-01-01

The electromagnetic energy deposited in a semi-infinite slab model consisting of skin, fat, and muscle layers is calculated for both plane-wave and near-field exposures. The plane-wave spectrum (PWS) approach is used to calculate the energy deposited in the model by fields present due to leakage from equipment using electromagnetic energy. This analysis applies to near-field exposures where coupling of the target to the leakage source can be neglected. Calculations were made for 2,450 MHz, at which frequency the layered slab adequately models flat regions of the human body. Resonant absorption due to layering is examined as a function of the skin and fat thicknesses for plane-wave exposure and as a function of the physical extent of the near-field distribution. Calculations show that for fields that are nearly constant over at least a free-space wavelength, the energy deposition (for skin, fat, and muscle combination that gives resonant absorption) is equal to or less than that resulting from plane-wave exposure, but is appreciably greater than that obtained for a homogeneous muscle slab model.

Spatio-temporal modelling of residential exposure to particulate matter and gaseous pollutants for the Heinz Nixdorf Recall Cohort

NASA Astrophysics Data System (ADS)

Nonnemacher, Michael; Jakobs, Hermann; Viehmann, Anja; Vanberg, Irene; Kessler, Christoph; Moebus, Susanne; Möhlenkamp, Stefan; Erbel, Raimund; Hoffmann, Barbara; Memmesheimer, Michael

2014-07-01

For the simultaneous analysis of short- and long-term effects of air pollution in the Heinz Nixdorf Recall Cohort a sophisticated exposure modelling was performed. The dispersion and chemistry transport model EURAD (European Air Pollution Dispersion) was used for the estimation of hourly concentrations of a number of pollutants for a horizontal grid with a cell size of 1 km² covering the whole study area (three large adjacent cities in a highly urbanized region in Western Germany) for the years 2000-2003 and 2006-2008. For each 1 km² cell we estimated the mean concentration by calculating daily means from the hourly concentrations modelled by the EURAD process. The modelled concentrations showed an overall tendency to decrease from 2001 to 2008 whereas the trend in the single grid cells and study period was inhomogeneous. Participant-related exposure slightly increased from 2001 to 2003 followed by a decrease from 2006 to 2008. The exposure modelling enables a very flexible exposure assessment compared to conventional modelling approaches which either use central monitoring or temporally static spatial contrasts. The modelling allows the calculation of an average exposure concentration for any place and time within the study region and study period with a high spatial and temporal resolution. This is important for the assessment of short-, medium and long-term effects of air pollution on human health in epidemiological studies.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

PubMed

Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Risk of breast cancer following exposure to tetrachloroethylene-contaminated drinking water in Cape Cod, Massachusetts: reanalysis of a case-control study using a modified exposure assessment

PubMed Central

2011-01-01

Background Tetrachloroethylene (PCE) is an important occupational chemical used in metal degreasing and drycleaning and a prevalent drinking water contaminant. Exposure often occurs with other chemicals but it occurred alone in a pattern that reduced the likelihood of confounding in a unique scenario on Cape Cod, Massachusetts. We previously found a small to moderate increased risk of breast cancer among women with the highest exposures using a simple exposure model. We have taken advantage of technical improvements in publically available software to incorporate a more sophisticated determination of water flow and direction to see if previous results were robust to more accurate exposure assessment. Methods The current analysis used PCE exposure estimates generated with the addition of water distribution modeling software (EPANET 2.0) to test model assumptions, compare exposure distributions to prior methods, and re-examine the risk of breast cancer. In addition, we applied data smoothing to examine nonlinear relationships between breast cancer and exposure. We also compared a set of measured PCE concentrations in water samples collected in 1980 to modeled estimates. Results Thirty-nine percent of individuals considered unexposed in prior epidemiological analyses were considered exposed using the current method, but mostly at low exposure levels. As a result, the exposure distribution was shifted downward resulting in a lower value for the 90th percentile, the definition of "high exposure" in prior analyses. The current analyses confirmed a modest increase in the risk of breast cancer for women with high PCE exposure levels defined by either the 90th percentile (adjusted ORs 1.0-1.5 for 0-19 year latency assumptions) or smoothing analysis cut point (adjusted ORs 1.3-2.0 for 0-15 year latency assumptions). Current exposure estimates had a higher correlation with PCE concentrations in water samples (Spearman correlation coefficient = 0.65, p < 0.0001) than estimates generated using the prior method (0.54, p < 0.0001). Conclusions The incorporation of sophisticated flow estimates in the exposure assessment method shifted the PCE exposure distribution downward, but did not meaningfully affect the exposure ranking of subjects or the strength of the association with the risk of breast cancer found in earlier analyses. Thus, the current analyses show a slightly elevated breast cancer risk for highly exposed women, with strengthened exposure assessment and minimization of misclassification by using the latest technology. PMID:21600013

Population Pharmacokinetics and Exposure Response Assessment of CC-292, a Potent BTK Inhibitor, in Patients With Chronic Lymphocytic Leukemia.

PubMed

Li, Yan; Ramírez-Valle, Francisco; Xue, Yongjun; Ventura, Judith I; Gouedard, Olivier; Mei, Jay; Takeshita, Kenichi; Palmisano, Maria; Zhou, Simon

2017-10-01

CC-292, a potent Bruton tyrosine kinase inhibitor, is under development for the treatment of B-cell malignancies. An analysis was performed to develop a population pharmacokinetic model of CC-292 and assess the influence of demographics and disease-related covariates on CC-292 exposure and to assess the exposure-response (overall response rate) relationship in patients with chronic lymphocytic leukemia. Population pharmacokinetic analysis was based on a 2-compartment base model conducted in NONMEM. Categorical exposure-response analysis was performed using logistic regression in SAS. The population pharmacokinetic analysis results indicated that CC-292 pharmacokinetic disposition is similar between healthy subjects and patients. CC-292 showed a larger central compartment volume of distribution than the peripheral compartment volume of distribution (158 L and 72 L, respectively) and a faster clearance than intercompartmental clearance (134 L/h and 18.7 L/h, respectively), indicating that for CC-292, clearance from blood occurs faster than distribution into deep tissues and organs. CC-292 clearance is not affected by demographics or baseline clinical lab factors, except for sex. Although sex significantly reduced variation of apparent clearance, the sex effect on apparent clearance is unlikely to be clinically relevant. The exposure-response analysis suggested that higher drug exposure is linearly correlated with higher overall response rate. A twice-daily dose regimen showed higher overall response rate as compared to once-daily dosing, consistent with a threshold concentration of approximately 300 ng/mL, above which the probability of overall response rate significantly increases. © 2017, The Authors. The Journal of Clinical Pharmacology Published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.

Estimation of personal PM2.5 and BC exposure by a modeling approach - Results of a panel study in Shanghai, China.

PubMed

Chen, Chen; Cai, Jing; Wang, Cuicui; Shi, Jingjin; Chen, Renjie; Yang, Changyuan; Li, Huichu; Lin, Zhijing; Meng, Xia; Zhao, Ang; Liu, Cong; Niu, Yue; Xia, Yongjie; Peng, Li; Zhao, Zhuohui; Chillrud, Steven; Yan, Beizhan; Kan, Haidong

2018-06-06

Epidemiologic studies of PM 2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested. We aimed to investigate effects of potential determinants and to estimate PM 2.5 and BC exposure by a modeling approach. We collected 417 24 h personal PM 2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R 2 and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV). Personal PM 2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) μg/m 3 ; whereas personal BC (6.1 (±2.8) μg/m 3 ) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM 2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM 2.5 and 72 h personal BC. LOOCV analysis showed an R 2 (RMSE) of 0.73 (0.40) for PM 2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R 2 (RMSE) of 0.73 (0.41) for PM 2.5 and 0.68 (0.26) for BC. We used readily accessible data and established intuitive models that can predict PM 2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Movie Exposure to Alcohol Cues and Adolescent Alcohol Problems: A Longitudinal Analysis in a National Sample

PubMed Central

Wills, Thomas A.; Sargent, James D.; Gibbons, Frederick X.; Gerrard, Meg; Stoolmiller, Mike

2009-01-01

The authors tested a theoretical model of how exposure to alcohol cues in movies predicts level of alcohol use (ever use plus ever and recent binge drinking) and alcohol-related problems. A national sample of younger adolescents was interviewed by telephone with 4 repeated assessments spaced at 8-month intervals. A structural equation modeling analysis performed for ever-drinkers at Time 3 (N = 961) indicated that, controlling for a number of covariates, movie alcohol exposure at Time 1 was related to increases in peer alcohol use and adolescent alcohol use at Time 2. Movie exposure had indirect effects to alcohol use and problems at Times 3 and 4 through these pathways, with direct effects to problems from Time 1 rebelliousness and Time 2 movie exposure also found. Prospective risk-promoting effects were also found for alcohol expectancies, peer alcohol use, and availability of alcohol in the home; protective effects were found for mother’s responsiveness and for adolescent’s school performance and self-control. Theoretical and practical implications are discussed. PMID:19290687

Movie exposure to alcohol cues and adolescent alcohol problems: a longitudinal analysis in a national sample.

PubMed

Wills, Thomas A; Sargent, James D; Gibbons, Frederick X; Gerrard, Meg; Stoolmiller, Mike

2009-03-01

The authors tested a theoretical model of how exposure to alcohol cues in movies predicts level of alcohol use (ever use plus ever and recent binge drinking) and alcohol-related problems. A national sample of younger adolescents was interviewed by telephone with 4 repeated assessments spaced at 8-month intervals. A structural equation modeling analysis performed for ever-drinkers at Time 3 (N = 961) indicated that, controlling for a number of covariates, movie alcohol exposure at Time 1 was related to increases in peer alcohol use and adolescent alcohol use at Time 2. Movie exposure had indirect effects to alcohol use and problems at Times 3 and 4 through these pathways, with direct effects to problems from Time 1 rebelliousness and Time 2 movie exposure also found. Prospective risk-promoting effects were also found for alcohol expectancies, peer alcohol use, and availability of alcohol in the home; protective effects were found for mother's responsiveness and for adolescent's school performance and self-control. Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Long- and short-term exposure to PM2.5 and mortality: using novel exposure models.

PubMed

Kloog, Itai; Ridgway, Bill; Koutrakis, Petros; Coull, Brent A; Schwartz, Joel D

2013-07-01

Many studies have reported associations between ambient particulate matter (PM) and adverse health effects, focused on either short-term (acute) or long-term (chronic) PM exposures. For chronic effects, the studied cohorts have rarely been representative of the population. We present a novel exposure model combining satellite aerosol optical depth and land-use data to investigate both the long- and short-term effects of PM2.5 exposures on population mortality in Massachusetts, United States, for the years 2000-2008. All deaths were geocoded. We performed two separate analyses: a time-series analysis (for short-term exposure) where counts in each geographic grid cell were regressed against cell-specific short-term PM2.5 exposure, temperature, socioeconomic data, lung cancer rates (as a surrogate for smoking), and a spline of time (to control for season and trends). In addition, for long-term exposure, we performed a relative incidence analysis using two long-term exposure metrics: regional 10 × 10 km PM2.5 predictions and local deviations from the cell average based on land use within 50 m of the residence. We tested whether these predicted the proportion of deaths from PM-related causes (cardiovascular and respiratory diseases). For short-term exposure, we found that for every 10-µg/m increase in PM 2.5 exposure there was a 2.8% increase in PM-related mortality (95% confidence interval [CI] = 2.0-3.5). For the long-term exposure at the grid cell level, we found an odds ratio (OR) for every 10-µg/m increase in long-term PM2.5 exposure of 1.6 (CI = 1.5-1.8) for particle-related diseases. Local PM2.5 had an OR of 1.4 (CI = 1.3-1.5), which was independent of and additive to the grid cell effect. We have developed a novel PM2.5 exposure model based on remote sensing data to assess both short- and long-term human exposures. Our approach allows us to gain spatial resolution in acute effects and an assessment of long-term effects in the entire population rather than a selective sample from urban locations.

An optimal sampling approach to modelling whole-body vibration exposure in all-terrain vehicle driving.

PubMed

Lü, Xiaoshu; Takala, Esa-Pekka; Toppila, Esko; Marjanen, Ykä; Kaila-Kangas, Leena; Lu, Tao

2017-08-01

Exposure to whole-body vibration (WBV) presents an occupational health risk and several safety standards obligate to measure WBV. The high cost of direct measurements in large epidemiological studies raises the question of the optimal sampling for estimating WBV exposures given by a large variation in exposure levels in real worksites. This paper presents a new approach to addressing this problem. A daily exposure to WBV was recorded for 9-24 days among 48 all-terrain vehicle drivers. Four data-sets based on root mean squared recordings were obtained from the measurement. The data were modelled using semi-variogram with spectrum analysis and the optimal sampling scheme was derived. The optimum sampling period was 140 min apart. The result was verified and validated in terms of its accuracy and statistical power. Recordings of two to three hours are probably needed to get a sufficiently unbiased daily WBV exposure estimate in real worksites. The developed model is general enough that is applicable to other cumulative exposures or biosignals. Practitioner Summary: Exposure to whole-body vibration (WBV) presents an occupational health risk and safety standards obligate to measure WBV. However, direct measurements can be expensive. This paper presents a new approach to addressing this problem. The developed model is general enough that is applicable to other cumulative exposures or biosignals.

Profiles of Nature Exposure and Outdoor Activities Associated With Occupational Well-Being Among Employees

PubMed Central

Hyvönen, Katriina; Törnroos, Kaisa; Salonen, Kirsi; Korpela, Kalevi; Feldt, Taru; Kinnunen, Ulla

2018-01-01

This research addresses the profiles of nature exposure and outdoor activities in nature among Finnish employees (N = 783). The profiles were formed on the bases of nature exposure at work and the frequency and type of outdoor activities in nature engaged in during leisure time. The profiles were investigated in relation to work engagement and burnout. The latent profile analysis identified a five-class solution as the best model: High exposure (8%), Versatile exposure (22%), Unilateral exposure (38%), Average exposure (13%), and Low exposure (19%). An Analysis of Covariance (ANCOVA) was conducted for each well-being outcome in order to evaluate how the identified profiles related to occupational well-being. Participants with a High, Versatile, or Unilateral exposure profile reported significantly higher work engagement in the dimensions of vigor and dedication than did the participants with a Low exposure profile. The participants with the High exposure profile also reported lower burnout in the dimensions of cynicism and professional inadequacy than the participants with the Low exposure profile. Nature exposure during the workday and leisure time is an under researched but important aspect in promoting occupational well-being. PMID:29867699

Single-Nucleotide Polymorphisms Associated with Skin Naphthyl–Keratin Adduct Levels in Workers Exposed to Naphthalene

PubMed Central

Jiang, Rong; French, John E.; Stober, Vandy P.; Kang-Sickel, Juei-Chuan C.; Zou, Fei

2012-01-01

Background: Individual genetic variation that results in differences in systemic response to xenobiotic exposure is not accounted for as a predictor of outcome in current exposure assessment models. Objective: We developed a strategy to investigate individual differences in single-nucleotide polymorphisms (SNPs) as genetic markers associated with naphthyl–keratin adduct (NKA) levels measured in the skin of workers exposed to naphthalene. Methods: The SNP-association analysis was conducted in PLINK using candidate-gene analysis and genome-wide analysis. We identified significant SNP–NKA associations and investigated the potential impact of these SNPs along with personal and workplace factors on NKA levels using a multiple linear regression model and the Pratt index. Results: In candidate-gene analysis, a SNP (rs4852279) located near the CYP26B1 gene contributed to the 2-naphthyl–keratin adduct (2NKA) level. In the multiple linear regression model, the SNP rs4852279, dermal exposure, exposure time, task replacing foam, age, and ethnicity all were significant predictors of 2NKA level. In genome-wide analysis, no single SNP reached genome-wide significance for NKA levels (all p ≥ 1.05 × 10–5). Pathway and network analyses of SNPs associated with NKA levels were predicted to be involved in the regulation of cellular processes and homeostasis. Conclusions: These results provide evidence that a quantitative biomarker can be used as an intermediate phenotype when investigating the association between genetic markers and exposure–dose relationship in a small, well-characterized exposed worker population. PMID:22391508

Vulnerability of Thai rice production to simultaneous climate and socioeconomic changes: a double exposure analysis

NASA Astrophysics Data System (ADS)

Sangpenchan, R.

2011-12-01

This research explores the vulnerability of Thai rice production to simultaneous exposure by climate and socioeconomic change -- so-called "double exposure." Both processes influence Thailand's rice production system, but the vulnerabilities associated with their interactions are unknown. To understand this double exposure, I adopts a mixed-method, qualitative-quantitative analytical approach consisting of three phases of analysis involving a Vulnerability Scoping Diagram, a Principal Component Analysis, and the EPIC crop model using proxy datasets collected from secondary data sources at provincial scales.The first and second phases identify key variables representing each of the three dimensions of vulnerability -- exposure, sensitivity, and adaptive capacity indicating that the greatest vulnerability in the rice production system occurs in households and areas with high exposure to climate change, high sensitivity to climate and socioeconomic stress, and low adaptive capacity. In the third phase, the EPIC crop model simulates rice yields associated with future climate change projected by CSIRO and MIROC climate models. Climate change-only scenarios project the decrease in yields by 10% from the current productivity during 2016-2025 and 30% during 2045-2054. Scenarios applying both climate change and improved technology and management practices show that a 50% increase in rice production is possible, but requires strong collaboration between sectors to advance agricultural research and technology and requires strong adaptive capacity in the rice production system characterized by well-developed social capital, social networks, financial capacity, and infrastructure and household mobility at the local scale. The vulnerability assessment and climate and crop adaptation simulations used here provide useful information to decision makers developing vulnerability reduction plans in the face of concurrent climate and socioeconomic change.

Environmental hazards and stress: evidence from the Texas City Stress and Health Study.

PubMed

Peek, M K; Cutchin, M P; Freeman, D; Stowe, R P; Goodwin, J S

2009-10-01

Substantial research has suggested that exposure to environmental health hazards, such as polluting industrial activity, has deleterious effects on psychological and physiological well-being. However, one gap in the existing literature is comparative analysis of objective and subjective exposure's relative association with various measurable outcomes of exposure. These relationships were explored within a community sample of 2604 respondents living near a large petrochemical complex in Texas City, Texas, USA. Objective exposure was investigated using distance of residence from a cluster of petrochemical plants and subjective exposure using residents' concern about potential health effects from those plants. Regression models were then used to examine how each type of exposure predicts perceived stress, physiological markers of stress and perceived health. Results suggest that objective exposure was associated primarily with markers of physiological stress (interleukin-6 and viral reactivation), and subjective exposure (concern about petrochemical health risk) was associated with variables assessing perceived health. From the analysis, it can be inferred that, in the context of an environmental hazard of this type, subjective exposure may be at least as important a predictor of poor health outcomes as objective exposure.

Occupational exposure and risk of chronic obstructive pulmonary disease: a systematic review and meta-analysis.

PubMed

Alif, Sheikh M; Dharmage, Shyamali C; Bowatte, Gayan; Karahalios, Amalia; Benke, Geza; Dennekamp, Martine; Mehta, Amar J; Miedinger, David; Künzli, Nino; Probst-Hensch, Nicole; Matheson, Melanie C

2016-08-01

Due to contradictory literature we have performed a systematic review and meta-analyse of population-based studies that have used Job Exposure Matrices to assess occupational exposure and risk of Chronic Obstructive Pulmonary Disease (COPD). Two researchers independently searched databases for published articles using predefined inclusion criteria. Study quality was assessed, and results pooled for COPD and chronic bronchitis for exposure to biological dust, mineral dust, and gases/fumes using a fixed and random effect model. Five studies met predetermined inclusion criteria. The meta-analysis showed low exposure to mineral dust, and high exposure to gases/fumes were associated with an increased risk of COPD. We also found significantly increased the risk of chronic bronchitis for low and high exposure to biological dust and mineral dust. Expert commentary: The relationship between occupational exposure assessed by the JEM and the risk of COPD and chronic bronchitis shows significant association with occupational exposure. However, the heterogeneity of the meta-analyses suggests more wide population-based studies with older age groups and longitudinal phenotype assessment of COPD to clarify the role of occupational exposure to COPD risk.

Air Pollution and Lung Function in Dutch Children: A Comparison of Exposure Estimates and Associations Based on Land Use Regression and Dispersion Exposure Modeling Approaches

PubMed Central

Gehring, Ulrike; Hoek, Gerard; Keuken, Menno; Jonkers, Sander; Beelen, Rob; Eeftens, Marloes; Postma, Dirkje S.; Brunekreef, Bert

2015-01-01

Background There is limited knowledge about the extent to which estimates of air pollution effects on health are affected by the choice for a specific exposure model. Objectives We aimed to evaluate the correlation between long-term air pollution exposure estimates using two commonly used exposure modeling techniques [dispersion and land use regression (LUR) models] and, in addition, to compare the estimates of the association between long-term exposure to air pollution and lung function in children using these exposure modeling techniques. Methods We used data of 1,058 participants of a Dutch birth cohort study with measured forced expiratory volume in 1 sec (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF) measurements at 8 years of age. For each child, annual average outdoor air pollution exposure [nitrogen dioxide (NO2), mass concentration of particulate matter with diameters ≤ 2.5 and ≤ 10 μm (PM2.5, PM10), and PM2.5 soot] was estimated for the current addresses of the participants by a dispersion and a LUR model. Associations between exposures to air pollution and lung function parameters were estimated using linear regression analysis with confounder adjustment. Results Correlations between LUR- and dispersion-modeled pollution concentrations were high for NO2, PM2.5, and PM2.5 soot (R = 0.86–0.90) but low for PM10 (R = 0.57). Associations with lung function were similar for air pollutant exposures estimated using LUR and dispersion modeling, except for associations of PM2.5 with FEV1 and FVC, which were stronger but less precise for exposures based on LUR compared with dispersion model. Conclusions Predictions from LUR and dispersion models correlated very well for PM2.5, NO2, and PM2.5 soot but not for PM10. Health effect estimates did not depend on the type of model used to estimate exposure in a population of Dutch children. Citation Wang M, Gehring U, Hoek G, Keuken M, Jonkers S, Beelen R, Eeftens M, Postma DS, Brunekreef B. 2015. Air pollution and lung function in Dutch children: a comparison of exposure estimates and associations based on land use regression and dispersion exposure modeling approaches. Environ Health Perspect 123:847–851; http://dx.doi.org/10.1289/ehp.1408541 PMID:25839747

Gene expression profiles following exposure to a developmental neurotoxicant, Aroclor 1254: Pathway analysis for possible mode(s) of action.

EPA Science Inventory

Epidemiological studies indicate that low levels of polychlorinated biphenyl (PCB) exposure can adversely affect neurocognitive development. In animal models, perturbations in calcium signaling, neurotransmitters, and thyroid hormones have been postulated as potential mechanisms...

Arsenic Metabolism by Human Gut Microbiota upon in Vitro Digestion of Contaminated Soils

EPA Science Inventory

Speciation analysis is essential when evaluating risks from, arsenic (As) exposure. In an oral exposure scenario, the importance of presystemic metabolism by gut microorganisms has been evidenced with in vivo animal models and in vitro experiments with animal microbiota. Howeve...

Pesticide exposure and risk of Alzheimer’s disease: a systematic review and meta-analysis

NASA Astrophysics Data System (ADS)

Yan, Dandan; Zhang, Yunjian; Liu, Liegang; Yan, Hong

2016-09-01

Evidence suggests that lifelong cumulative exposure to pesticides may generate lasting toxic effects on the central nervous system and contribute to the development of Alzheimer’s disease (AD). A number of reports indicate a potential association between long-term/low-dose pesticide exposure and AD, but the results are inconsistent. Therefore, we conducted a meta-analysis to clarify this association. Relevant studies were identified according to inclusion criteria. Summary odds ratios (ORs) were calculated using fixed-effects models. A total of seven studies were included in our meta-analysis. A positive association was observed between pesticide exposure and AD (OR = 1.34 95% confidence interval [CI] = 1.08, 1.67; n = 7). The summary ORs with 95% CIs from the crude and adjusted effect size studies were 1.14 (95% CI = 0.94, 1.38; n = 7) and 1.37 (95% CI = 1.09, 1.71; n = 5), respectively. The sensitivity analyses of the present meta-analysis did not substantially modify the association between pesticide exposure and AD. Subgroup analyses revealed that high-quality studies tended to show significant relationships. The present meta-analysis suggested a positive association between pesticide exposure and AD, confirming the hypothesis that pesticide exposure is a risk factor for AD. Further high-quality cohort and case-control studies are required to validate a causal relationship.

Nuclear Radiation Fields on the Mars Surface: Risk Analysis for Long-term Living Environment

NASA Technical Reports Server (NTRS)

Anderson, Brooke M.; Clowdsley, Martha S.; Qualls, Garry D.; Nealy, John E.

2005-01-01

Mars, our nearest planet outward from the sun, has been targeted for several decades as a prospective site for expanded human habitation. Background space radiation exposures on Mars are expected to be orders of magnitude higher than on Earth. Recent risk analysis procedures based on detailed dosimetric techniques applicable to sensitive human organs have been developed along with experimental data regarding cell mutation rates resulting from exposures to a broad range of particle types and energy spectra. In this context, simulated exposure and subsequent risk for humans in residence on Mars are examined. A conceptual habitat structure, CAD-modeled with duly considered inherent shielding properties, has been implemented. Body self-shielding is evaluated using NASA standard computerized male and female models. The background environment is taken to consist not only of exposure from incident cosmic ray ions and their secondaries, but also include the contribution from secondary neutron fields produced in the tenuous atmosphere and the underlying regolith.

Proteomic profiling of halloysite clay nanotube exposure in intestinal cell co-culture

PubMed Central

Lai, Xianyin; Agarwal, Mangilal; Lvov, Yuri M.; Pachpande, Chetan; Varahramyan, Kody; Witzmann, Frank A.

2013-01-01

Halloysite is aluminosilicate clay with a hollow tubular structure with nanoscale internal and external diameters. Assessment of halloysite biocompatibility has gained importance in view of its potential application in oral drug delivery. To investigate the effect of halloysite nanotubes on an in vitro model of the large intestine, Caco-2/HT29-MTX cells in monolayer co-culture were exposed to nanotubes for toxicity tests and proteomic analysis. Results indicate that halloysite exhibits a high degree of biocompatibility characterized by an absence of cytotoxicity, in spite of elevated pro-inflammatory cytokine release. Exposure-specific changes in expression were observed among 4081 proteins analyzed. Bioinformatic analysis of differentially expressed protein profiles suggest that halloysite stimulates processes related to cell growth and proliferation, subtle responses to cell infection, irritation and injury, enhanced antioxidant capability, and an overall adaptive response to exposure. These potentially relevant functional effects warrant further investigation in in vivo models and suggest that chronic or bolus occupational exposure to halloysite nanotubes may have unintended outcomes. PMID:23606564

Climate-Related Hazards: A Method for Global Assessment of Urban and Rural Population Exposure to Cyclones, Droughts, and Floods

PubMed Central

Christenson, Elizabeth; Elliott, Mark; Banerjee, Ovik; Hamrick, Laura; Bartram, Jamie

2014-01-01

Global climate change (GCC) has led to increased focus on the occurrence of, and preparation for, climate-related extremes and hazards. Population exposure, the relative likelihood that a person in a given location was exposed to a given hazard event(s) in a given period of time, was the outcome for this analysis. Our objectives were to develop a method for estimating the population exposure at the country level to the climate-related hazards cyclone, drought, and flood; develop a method that readily allows the addition of better datasets to an automated model; differentiate population exposure of urban and rural populations; and calculate and present the results of exposure scores and ranking of countries based on the country-wide, urban, and rural population exposures to cyclone, drought, and flood. Gridded global datasets on cyclone, drought and flood occurrence as well as population density were combined and analysis was carried out using ArcGIS. Results presented include global maps of ranked country-level population exposure to cyclone, drought, flood and multiple hazards. Analyses by geography and human development index (HDI) are also included. The results and analyses of this exposure assessment have implications for country-level adaptation. It can also be used to help prioritize aid decisions and allocation of adaptation resources between countries and within a country. This model is designed to allow flexibility in applying cyclone, drought and flood exposure to a range of outcomes and adaptation measures. PMID:24566046

Impact of Hurricane Exposure on Reproductive Health Outcomes, Florida, 2004.

PubMed

Grabich, Shannon C; Robinson, Whitney R; Konrad, Charles E; Horney, Jennifer A

2017-08-01

Prenatal hurricane exposure may be an increasingly important contributor to poor reproductive health outcomes. In the current literature, mixed associations have been suggested between hurricane exposure and reproductive health outcomes. This may be due, in part, to residual confounding. We assessed the association between hurricane exposure and reproductive health outcomes by using a difference-in-difference analysis technique to control for confounding in a cohort of Florida pregnancies. We implemented a difference-in-difference analysis to evaluate hurricane weather and reproductive health outcomes including low birth weight, fetal death, and birth rate. The study population for analysis included all Florida pregnancies conceived before or during the 2003 and 2004 hurricane season. Reproductive health data were extracted from vital statistics records from the Florida Department of Health. In 2004, 4 hurricanes (Charley, Frances, Ivan, and Jeanne) made landfall in rapid succession; whereas in 2003, no hurricanes made landfall in Florida. Overall models using the difference-in-difference analysis showed no association between exposure to hurricane weather and reproductive health. The inconsistency of the literature on hurricane exposure and reproductive health may be in part due to biases inherent in pre-post or regression-based county-level comparisons. We found no associations between hurricane exposure and reproductive health. (Disaster Med Public Health Preparedness. 2017;11:407-411).

Longitudinal analysis of respiratory outcomes among bauxite exposed workers in Western Australia.

PubMed

Dennekamp, Martine; de Klerk, Nicholas Hubert; Reid, Alison; Abramson, Michael John; Cui, Jisheng; Del Monaco, Anthony; Fritschi, Lin; Benke, Geza Paul; Sim, Malcolm Ross; Musk, Arthur William

2015-08-01

Occupational exposure to bauxite is common in the aluminium industry but little is known about the associated health effects. This study investigates respiratory health in relation to respirable bauxite dust exposure longitudinally over a 13 year period. An inception cohort study recruited 91 male bauxite miners and 363 male alumina refinery workers. Annual measurements of respiratory symptoms and lung function were made. Cumulative exposure to bauxite was derived from job histories and air monitoring data. Mixed-effects modeling was used. No associations were found between cumulative bauxite exposure and respiratory symptoms or lung function. However, when analysis was restricted to the first three rounds, FEV1 was significantly lower in all exposure groups than in those unexposed but with no significant trend. Increasing exposure to bauxite dust in the aluminum industry was not associated with respiratory symptoms or consistent decrements in lung function. © 2015 Wiley Periodicals, Inc.

Reconstructing population exposures to environmental chemicals from biomarkers: challenges and opportunities.

PubMed

Georgopoulos, Panos G; Sasso, Alan F; Isukapalli, Sastry S; Lioy, Paul J; Vallero, Daniel A; Okino, Miles; Reiter, Larry

2009-02-01

A conceptual/computational framework for exposure reconstruction from biomarker data combined with auxiliary exposure-related data is presented, evaluated with example applications, and examined in the context of future needs and opportunities. This framework employs physiologically based toxicokinetic (PBTK) modeling in conjunction with numerical "inversion" techniques. To quantify the value of different types of exposure data "accompanying" biomarker data, a study was conducted focusing on reconstructing exposures to chlorpyrifos, from measurements of its metabolite levels in urine. The study employed biomarker data as well as supporting exposure-related information from the National Human Exposure Assessment Survey (NHEXAS), Maryland, while the MENTOR-3P system (Modeling ENvironment for TOtal Risk with Physiologically based Pharmacokinetic modeling for Populations) was used for PBTK modeling. Recently proposed, simple numerical reconstruction methods were applied in this study, in conjunction with PBTK models. Two types of reconstructions were studied using (a) just the available biomarker and supporting exposure data and (b) synthetic data developed via augmenting available observations. Reconstruction using only available data resulted in a wide range of variation in estimated exposures. Reconstruction using synthetic data facilitated evaluation of numerical inversion methods and characterization of the value of additional information, such as study-specific data that can be collected in conjunction with the biomarker data. Although the NHEXAS data set provides a significant amount of supporting exposure-related information, especially when compared to national studies such as the National Health and Nutrition Examination Survey (NHANES), this information is still not adequate for detailed reconstruction of exposures under several conditions, as demonstrated here. The analysis presented here provides a starting point for introducing improved designs for future biomonitoring studies, from the perspective of exposure reconstruction; identifies specific limitations in existing exposure reconstruction methods that can be applied to population biomarker data; and suggests potential approaches for addressing exposure reconstruction from such data.

Structural equation modelling of lower back pain due to whole-body vibration exposure in the construction industry.

PubMed

Vitharana, Vitharanage Hashini Paramitha; Chinda, Thanwadee

2017-09-21

Whole-body vibration (WBV) exposure is a health hazard among workers, causing lower back pain (LBP) in the construction industry. This study examines key factors affecting LBP due to WBV exposure using exploratory factor analysis and structural equation modelling. The results confirm five key factors (equipment, job related, organizational, personal, social context) with their 17 associated items. The organizational factor is found the most important, as it influences the other four factors. The results also show that appropriate seat type, specific training programme, job rotation, workers' satisfaction and workers' physical condition are crucial in reducing LBP due to WBV exposure. Moreover, provision of new machines without proper training and good working condition might not help reduce LBP due to WBV exposure. The results help the construction companies to better understand key factors affecting LBP due to WBV exposure, and to plan for a better health improvement programme.

Combined Effects of Prenatal Exposures to Environmental Chemicals on Birth Weight.

PubMed

Govarts, Eva; Remy, Sylvie; Bruckers, Liesbeth; Den Hond, Elly; Sioen, Isabelle; Nelen, Vera; Baeyens, Willy; Nawrot, Tim S; Loots, Ilse; Van Larebeke, Nick; Schoeters, Greet

2016-05-12

Prenatal chemical exposure has been frequently associated with reduced fetal growth by single pollutant regression models although inconsistent results have been obtained. Our study estimated the effects of exposure to single pollutants and mixtures on birth weight in 248 mother-child pairs. Arsenic, copper, lead, manganese and thallium were measured in cord blood, cadmium in maternal blood, methylmercury in maternal hair, and five organochlorines, two perfluorinated compounds and diethylhexyl phthalate metabolites in cord plasma. Daily exposure to particulate matter was modeled and averaged over the duration of gestation. In single pollutant models, arsenic was significantly associated with reduced birth weight. The effect estimate increased when including cadmium, and mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) co-exposure. Combining exposures by principal component analysis generated an exposure factor loaded by cadmium and arsenic that was associated with reduced birth weight. MECPP induced gender specific effects. In girls, the effect estimate was doubled with co-exposure of thallium, PFOS, lead, cadmium, manganese, and mercury, while in boys, the mixture of MECPP with cadmium showed the strongest association with birth weight. In conclusion, birth weight was consistently inversely associated with exposure to pollutant mixtures. Chemicals not showing significant associations at single pollutant level contributed to stronger effects when analyzed as mixtures.

Causal mediation analysis for longitudinal data with exogenous exposure

PubMed Central

Bind, M.-A. C.; Vanderweele, T. J.; Coull, B. A.; Schwartz, J. D.

2016-01-01

Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation. PMID:26272993

Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods.

PubMed

Keogh, Ruth H; Daniel, Rhian M; VanderWeele, Tyler J; Vansteelandt, Stijn

2018-05-01

Estimation of causal effects of time-varying exposures using longitudinal data is a common problem in epidemiology. When there are time-varying confounders, which may include past outcomes, affected by prior exposure, standard regression methods can lead to bias. Methods such as inverse probability weighted estimation of marginal structural models have been developed to address this problem. However, in this paper we show how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates. We refer to the resulting estimation approach as sequential conditional mean models (SCMMs), which can be fitted using generalized estimating equations. We outline this approach and describe how including propensity score adjustment is advantageous. We compare the causal effects being estimated using SCMMs and marginal structural models, and we compare the two approaches using simulations. SCMMs enable more precise inferences, with greater robustness against model misspecification via propensity score adjustment, and easily accommodate continuous exposures and interactions. A new test for direct effects of past exposures on a subsequent outcome is described.

Probabilistic modelling of human exposure to intense sweeteners in Italian teenagers: validation and sensitivity analysis of a probabilistic model including indicators of market share and brand loyalty.

PubMed

Arcella, D; Soggiu, M E; Leclercq, C

2003-10-01

For the assessment of exposure to food-borne chemicals, the most commonly used methods in the European Union follow a deterministic approach based on conservative assumptions. Over the past few years, to get a more realistic view of exposure to food chemicals, risk managers are getting more interested in the probabilistic approach. Within the EU-funded 'Monte Carlo' project, a stochastic model of exposure to chemical substances from the diet and a computer software program were developed. The aim of this paper was to validate the model with respect to the intake of saccharin from table-top sweeteners and cyclamate from soft drinks by Italian teenagers with the use of the software and to evaluate the impact of the inclusion/exclusion of indicators on market share and brand loyalty through a sensitivity analysis. Data on food consumption and the concentration of sweeteners were collected. A food frequency questionnaire aimed at identifying females who were high consumers of sugar-free soft drinks and/or of table top sweeteners was filled in by 3982 teenagers living in the District of Rome. Moreover, 362 subjects participated in a detailed food survey by recording, at brand level, all foods and beverages ingested over 12 days. Producers were asked to provide the intense sweeteners' concentration of sugar-free products. Results showed that consumer behaviour with respect to brands has an impact on exposure assessments. Only probabilistic models that took into account indicators of market share and brand loyalty met the validation criteria.

Environmental exposure modeling and monitoring of human pharmaceutical concentrations in the environment

USGS Publications Warehouse

Versteeg, D.J.; Alder, A. C.; Cunningham, V. L.; Kolpin, D.W.; Murray-Smith, R.; Ternes, T.

2005-01-01

Human pharmaceuticals are receiving increased attention as environmental contaminants. This is due to their biological activity and the number of monitoring programs focusing on analysis of these compounds in various environmental media and compartments. Risk assessments are needed to understand the implications of reported concentrations; a fundamental part of the risk assessment is an assessment of environmental exposures. The purpose of this chapter is to provide guidance on the use of predictive tools (e.g., models) and monitoring data in exposure assessments for pharmaceuticals in the environment. Methods to predict environmental concentrations from equations based on first principles are presented. These equations form the basis of existing GIS (geographic information systems)-based systems for understanding the spatial distribution of pharmaceuticals in the environment. The pharmaceutical assessment and transport (PhATE), georeferenced regional exposure assessment tool for European rivers (GREAT-ER), and geographical information system (GIS)-ROUT models are reviewed and recommendations are provided concerning the design and execution of monitoring studies. Model predictions and monitoring data are compared to evaluate the relative utility of each approach in environmental exposure assessments. In summary, both models and monitoring data can be used to define representative exposure concentrations of pharmaceuticals in the environment in support of environmental risk assessments.

Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset

NASA Astrophysics Data System (ADS)

Smith, A.; Neal, J. C.; Bates, P. D.; Quinn, N.; Wing, O.

2017-12-01

Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

PubMed

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (P<0.01) clusters of fasciolosis. The low-risk clusters were mostly located in the southern regions of Ireland, whereas the high-risk clusters were mainly situated in the western part. Several climatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

Estimation of health effects of prenatal methylmercury exposure using structural equation models.

PubMed

Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe; Weihe, Pal

2002-10-14

Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl-mercury toxicity. Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function. Adjustment for local dependence and item bias was necessary for a satisfactory fit of the model, but had little impact on the estimated mercury effects. The mercury effect on the two latent neurobehavioral functions was similar to the strongest effects seen for individual test scores of motor function and verbal skills. Adjustment for contaminant exposure to poly chlorinated biphenyls (PCBs) changed the estimates only marginally, but the mercury effect could be reduced to non-significance by assuming a large measurement error for the PCB biomarker. The structural equation analysis allows correction for measurement error in exposure variables, incorporation of multiple outcomes and incomplete cases. This approach therefore deserves to be applied more frequently in the analysis of complex epidemiological data sets.

Analysis of Intervention Strategies for Inhalation Exposure to Polycyclic Aromatic Hydrocarbons and Associated Lung Cancer Risk Based on a Monte Carlo Population Exposure Assessment Model

PubMed Central

Zhou, Bin; Zhao, Bin

2014-01-01

It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs), a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF) and potential impact fraction (PIF) of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making. PMID:24416436

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

USDA-ARS?s Scientific Manuscript database

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop+Pesticide model. Simulations are performed of hive population trajectories with and without pesticide exposure to determine the eff...

Arsenic Metabolism by Human Gut Microbiota upon In Vitro Digestion of Contaminated Soils

EPA Science Inventory

Background: Speciation analysis is essential when evaluating risks from arsenic (As) exposure. In an oral exposure scenario, the importance of presystemic metabolism by gut microorganisms has been evidenced with in vivo animal models and in vitro experiments with ...

Socio-economic exposure to natural disasters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marin, Giovanni, E-mail: giovanni.marin@uniurb.it; IRCrES - CNR, Research Institute on Sustainable Economic Growth, Via Corti 12, 20133 - Milano; SEEDS, Ferrara

Even though the correct assessment of risks is a key aspect of the risk management analysis, we argue that limited effort has been devoted in the assessment of comprehensive measures of economic exposure at very low scale. For this reason, we aim at providing a series of suitable methodologies to provide a complete and detailed list of the exposure of economic activities to natural disasters. We use Input-Output models to provide information about several socio-economic variables, such as population density, employment density, firms' turnover and capital stock, that can be seen as direct and indirect socio-economic exposure to natural disasters.more » We then provide an application to the Italian context. These measures can be easily incorporated into risk assessment models to provide a clear picture of the disaster risk for local areas. - Highlights: • Ex ante assessment of economic exposure to disasters at very low geographical scale • Assessment of the cost of natural disasters in ex-post perspective • IO model and spatial autocorrelation to get information on socio-economic variables • Indicators supporting risk assessment and risk management models.« less

CAD-based stand-alone spacecraft radiation exposure analysis system: An application of the early man-tended Space Station

NASA Technical Reports Server (NTRS)

Appleby, M. H.; Golightly, M. J.; Hardy, A. C.

1993-01-01

Major improvements have been completed in the approach to analyses and simulation of spacecraft radiation shielding and exposure. A computer-aided design (CAD)-based system has been developed for determining the amount of shielding provided by a spacecraft and simulating transmission of an incident radiation environment to any point within or external to the vehicle. Shielding analysis is performed using a customized ray-tracing subroutine contained within a standard engineering modeling software package. This improved shielding analysis technique has been used in several vehicle design programs such as a Mars transfer habitat, pressurized lunar rover, and the redesigned international Space Station. Results of analysis performed for the Space Station astronaut exposure assessment are provided to demonastrate the applicability and versatility of the system.

Mortality and long-term exposure to ambient air pollution: ongoing analyses based on the American Cancer Society cohort.

PubMed

Krewski, Daniel; Burnett, Richard; Jerrett, Michael; Pope, C Arden; Rainham, Daniel; Calle, Eugenia; Thurston, George; Thun, Michael

This article provides an overview of previous analysis and reanalysis of the American Cancer Society (ACS) cohort, along with an indication of current ongoing analyses of the cohort with additional follow-up information through to 2000. Results of the first analysis conducted by Pope et al. (1995) showed that higher average sulfate levels were associated with increased mortality, particularly from cardiopulmonary disease. A reanalysis of the ACS cohort, undertaken by Krewski et al. (2000), found the original risk estimates for fine-particle and sulfate air pollution to be highly robust against alternative statistical techniques and spatial modeling approaches. A detailed investigation of covariate effects found a significant modifying effect of education with risk of mortality associated with fine particles declining with increasing educational attainment. Pope et al. (2002) subsequently reported results of a subsequent study using an additional 10 yr of follow-up of the ACS cohort. This updated analysis included gaseous copollutant and new fine-particle measurements, more comprehensive information on occupational exposures, dietary variables, and the most recent developments in statistical modeling integrating random effects and nonparametric spatial smoothing into the Cox proportional hazards model. Robust associations between ambient fine particulate air pollution and elevated risks of cardiopulmonary and lung cancer mortality were clearly evident, providing the strongest evidence to date that long-term exposure to fine particles is an important health risk. Current ongoing analysis using the extended follow-up information will explore the role of ecologic, economic, and, demographic covariates in the particulate air pollution and mortality association. This analysis will also provide insight into the role of spatial autocorrelation at multiple geographic scales, and whether critical instances in time of exposure to fine particles influence the risk of mortality from cardiopulmonary and lung cancer. Information on the influence of covariates at multiple scales and of critical exposure time windows can assist policymakers in establishing timelines for regulatory interventions that maximize population health benefits.

Reducing Periconceptional Methylmercury Exposure: Cost–Utility Analysis for a Proposed Screening Program for Women Planning a Pregnancy in Ontario, Canada

PubMed Central

Rennie, Colin; Coyle, Doug

2015-01-01

Background The assessment of neurodevelopmental effects in children associated with prenatal methylmercury exposure, from contaminated fish and seafood in the maternal diet, has recently been strengthened by adjustment for the negative confounding resulting from co-exposure to beneficial polyunsaturated fatty acids (PUFAs). Objectives We aimed to determine the cost-effectiveness of a periconceptional screening program of blood mercury concentration for women planning to become pregnant in Ontario, Canada. Fish intake recommendations would be provided for those found to have blood mercury levels above the intervention threshold. Methods Analysis was conducted using a combined decision tree/Markov model to compare the proposed screening intervention with standard care from a societal perspective over a lifetime horizon. We used the national blood mercury distributions of women 20–49 years of age reported in the Canadian Health Measures Survey from 2009 through 2011 to determine the cognitive deficits associated with prenatal methylmercury exposure for successful planned pregnancies. Outcomes modeled included the loss in quality of life and the remedial education costs. Value of information analysis was conducted to assess the underlying uncertainty around the model results and to identify which parameters contribute most to this uncertainty. Results The incremental cost per quality-adjusted life year (QALY) gained for the proposed screening intervention was estimated to be Can$18,051, and the expected value for a willingness to pay of Can$50,000/QALY to be Can$0.61. Conclusions Our findings suggest that the proposed periconceptional blood mercury screening program for women planning a pregnancy would be highly cost-effective from a societal perspective. The results of a value of information analysis confirm the robustness of the study’s conclusions. Citation Gaskin J, Rennie C, Coyle D. 2015. Reducing periconceptional methylmercury exposure: cost–utility analysis for a proposed screening program for women planning a pregnancy in Ontario, Canada. Environ Health Perspect 123:1337–1344; http://dx.doi.org/10.1289/ehp.1409034 PMID:26024213

Population Pharmacokinetic and Pharmacodynamic Analysis of Belimumab Administered Subcutaneously in Healthy Volunteers and Patients with Systemic Lupus Erythematosus.

PubMed

Struemper, Herbert; Thapar, Mita; Roth, David

2017-09-08

Intravenous belimumab 10 mg/kg every 4 weeks is indicated in patients with active, autoantibody-positive systemic lupus erythematosus receiving standard systemic lupus erythematosus care. Subcutaneous 200-mg weekly administration, which may prove more convenient for patients and improve adherence, is currently under investigation. The objective of this study was to characterize the population pharmacokinetics and exposure-efficacy response of subcutaneous belimumab in a pooled analysis of pharmacokinetic data [phase I: BEL114448 (NCT01583530) and BEL116119 (NCT01516450) in healthy subjects (n = 134); phase III: BEL112341 (NCT01484496) in adults with systemic lupus erythematosus (n = 554)] and pharmacodynamic data [BEL112341 in adults with systemic lupus erythematosus (n = 833)]. Non-linear mixed-effects modeling (NONMEM®) was used to develop a population pharmacokinetic model and perform a covariate analysis. Subsequently, exploratory exposure-response analysis and logistic regression modeling was performed based on the individual parameter estimates of the population pharmacokinetic model. Population-pharmacokinetic parameters for subcutaneous belimumab were consistent with those for intravenous belimumab and other immunoglobulin G1 monoclonal antibodies. Pharmacokinetic parameters and subcutaneous belimumab exposure were consistent between healthy subjects and patients with systemic lupus erythematosus, and no evidence for target-mediated disposition of belimumab was found. Subcutaneous belimumab steady-state exposure was achieved after ~11 weeks; subcutaneous belimumab steady-state minimum concentration exceeded that of intravenous belimumab after <4 weeks, and average steady-state concentration was similar to that achieved following intravenous administration. In patients with moderate-to-severe systemic lupus erythematosus, subcutaneous belimumab 200 mg once weekly plus standard of care significantly improved the systemic lupus erythematosus responder index. However, at this dose, the systemic lupus erythematosus responder index response was not significantly associated with belimumab exposure concentrations. The analysis demonstrates that a 200-mg once-weekly dose of belimumab is appropriate for subcutaneous administration in patients with systemic lupus erythematosus and that no dose adjustments are required for adult patients to maintain efficacy and safety.

The Global Food System as a Transport Pathway for Hazardous Chemicals: The Missing Link between Emissions and Exposure.

PubMed

Ng, Carla A; von Goetz, Natalie

2017-01-01

Food is a major pathway for human exposure to hazardous chemicals. The modern food system is becoming increasingly complex and globalized, but models for food-borne exposure typically assume locally derived diets or use concentrations directly measured in foods without accounting for food origin. Such approaches may not reflect actual chemical intakes because concentrations depend on food origin, and representative analysis is seldom available. Processing, packaging, storage, and transportation also impart different chemicals to food and are not yet adequately addressed. Thus, the link between environmental emissions and realistic human exposure is effectively broken. We discuss the need for a fully integrated treatment of the modern industrialized food system, and we propose strategies for using existing models and relevant supporting data sources to track chemicals during production, processing, packaging, storage, and transport. Fate and bioaccumulation models describe how chemicals distribute in the environment and accumulate through local food webs. Human exposure models can use concentrations in food to determine body burdens based on individual or population characteristics. New models now include the impacts of processing and packaging but are far from comprehensive. We propose to close the gap between emissions and exposure by utilizing a wider variety of models and data sources, including global food trade data, processing, and packaging models. A comprehensive approach that takes into account the complexity of the modern global food system is essential to enable better prediction of human exposure to chemicals in food, sound risk assessments, and more focused risk abatement strategies. Citation: Ng CA, von Goetz N. 2017. The global food system as a transport pathway for hazardous chemicals: the missing link between emissions and exposure. Environ Health Perspect 125:1-7; http://dx.doi.org/10.1289/EHP168.

Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies.

PubMed

Valari, Myrto; Menut, Laurent; Chatignoux, Edouard

2011-02-01

Environmental epidemiology and more specifically time-series analysis have traditionally used area-averaged pollutant concentrations measured at central monitors as exposure surrogates to associate health outcomes with air pollution. However, spatial aggregation has been shown to contribute to the overall bias in the estimation of the exposure-response functions. This paper presents the benefit of adding features of the spatial variability of exposure by using concentration fields modeled with a chemistry transport model instead of monitor data and accounting for human activity patterns. On the basis of county-level census data for the city of Paris, France, and a Monte Carlo simulation, a simple activity model was developed accounting for the temporal variability between working and evening hours as well as during transit. By combining activity data with modeled concentrations, the downtown, suburban, and rural spatial patterns in exposure to nitrogen dioxide, ozone, and PM2.5 (particulate matter [PM] < or = 10 microm in aerodynamic diameter) were captured and parametrized. Exposures predicted with this model were used in a time-series study of the short-term effect of air pollution on total nonaccidental mortality for the 4-yr period from 2001 to 2004. It was shown that the time series of the exposure surrogates developed here are less correlated across co-pollutants than in the case of the area-averaged monitor data. This led to less biased exposure-response functions when all three co-pollutants were inserted simultaneously in the same regression model. This finding yields insight into pollutant-specific health effects that are otherwise masked by the high correlation among co-pollutants.

Mapping for prevention: GIS models for directing childhood lead poisoning prevention programs.

PubMed Central

Miranda, Marie Lynn; Dolinoy, Dana C; Overstreet, M Alicia

2002-01-01

Environmental threats to children's health--especially low-level lead exposure--are complex and multifaceted; consequently, mitigation of these threats has proven costly and insufficient and has produced economic and racial disparities in exposure among populations. Policy makers, public health officials, child advocates, and others currently lack the appropriate infrastructure to evaluate children's risk and exposure potential across a broad range of risks. Unable to identify where the highest risk of exposure occurs, children's environmental health programs remain mitigative instead of preventive. In this article we use geographic information system spatial analysis of data from blood lead screening, county tax assessors, and the U.S. Census to predict statistically based lead exposure risk levels mapped at the individual tax parcel unit in six counties in North Carolina. The resulting model uses weighted risk factors to spatially locate modeled exposure zones, thus highlighting critical areas for targeted intervention. The methods presented here hold promise for application and extension to the other 94 North Carolina counties and nationally, as well as to other environmental health risks. PMID:12204831

Comparison of task-based exposure metrics for an epidemiologic study of isocyanate inhalation exposures among autobody shop workers.

PubMed

Woskie, Susan R; Bello, Dhimiter; Gore, Rebecca J; Stowe, Meredith H; Eisen, Ellen A; Liu, Youcheng; Sparer, Judy A; Redlich, Carrie A; Cullen, Mark R

2008-09-01

Because many occupational epidemiologic studies use exposure surrogates rather than quantitative exposure metrics, the UMass Lowell and Yale study of autobody shop workers provided an opportunity to evaluate the relative utility of surrogates and quantitative exposure metrics in an exposure response analysis of cross-week change in respiratory function. A task-based exposure assessment was used to develop several metrics of inhalation exposure to isocyanates. The metrics included the surrogates, job title, counts of spray painting events during the day, counts of spray and bystander exposure events, and a quantitative exposure metric that incorporated exposure determinant models based on task sampling and a personal workplace protection factor for respirator use, combined with a daily task checklist. The result of the quantitative exposure algorithm was an estimate of the daily time-weighted average respirator-corrected total NCO exposure (microg/m(3)). In general, these four metrics were found to be variable in agreement using measures such as weighted kappa and Spearman correlation. A logistic model for 10% drop in FEV(1) from Monday morning to Thursday morning was used to evaluate the utility of each exposure metric. The quantitative exposure metric was the most favorable, producing the best model fit, as well as the greatest strength and magnitude of association. This finding supports the reports of others that reducing exposure misclassification can improve risk estimates that otherwise would be biased toward the null. Although detailed and quantitative exposure assessment can be more time consuming and costly, it can improve exposure-disease evaluations and is more useful for risk assessment purposes. The task-based exposure modeling method successfully produced estimates of daily time-weighted average exposures in the complex and changing autobody shop work environment. The ambient TWA exposures of all of the office workers and technicians and 57% of the painters were found to be below the current U.K. Health and Safety Executive occupational exposure limit (OEL) for total NCO of 20 microg/m(3). When respirator use was incorporated, all personal daily exposures were below the U.K. OEL.

A re-examination of the mere exposure effect: The influence of repeated exposure on recognition, familiarity, and liking.

PubMed

Montoya, R Matthew; Horton, Robert S; Vevea, Jack L; Citkowicz, Martyna; Lauber, Elissa A

2017-05-01

To evaluate the veracity of models of the mere exposure effect and to understand the processes that moderate the effect, we conducted a meta-analysis of the influence of repeated exposure on liking, familiarity, recognition, among other evaluations. We estimated parameters from 268 curve estimates drawn from 81 articles and revealed that the mere exposure effect was characterized by a positive slope and negative quadratic effect consistent with an inverted-U shaped curve. In fact, such curves were associated with (a) all visual, but not auditory stimuli; (b) exposure durations shorter than 10 s and longer than 1 min; (c) both homogeneous and heterogeneous presentation types; and (d) ratings that were taken after all stimuli were presented. We conclude that existing models for the mere exposure effect do not adequately account for the findings, and we provide a framework to help guide future research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Effects of prenatal alcohol exposure (PAE): insights into FASD using mouse models of PAE.

PubMed

Petrelli, Berardino; Weinberg, Joanne; Hicks, Geoffrey G

2018-04-01

The potential impact of prenatal alcohol exposure (PAE) varies considerably among exposed individuals, with some displaying serious alcohol-related effects and many others showing few or no overt signs of fetal alcohol spectrum disorder (FASD). In animal models, variables such as nutrition, genetic background, health, other drugs, and stress, as well as dosage, duration, and gestational timing of exposure to alcohol can all be controlled in a way that is not possible in a clinical situation. In this review we examine mouse models of PAE and focus on those with demonstrated craniofacial malformations, abnormal brain development, or behavioral phenotypes that may be considered FASD-like outcomes. Analysis of these data should provide a valuable tool for researchers wishing to choose the PAE model best suited to their research questions or to investigate established PAE models for FASD comorbidities. It should also allow recognition of patterns linking gestational timing, dosage, and duration of PAE, such as recognizing that binge alcohol exposure(s) during early gestation can lead to severe FASD outcomes. Identified patterns could be particularly insightful and lead to a better understanding of the molecular mechanisms underlying FASD.

Validation and sensitivity of the FINE Bayesian network for forecasting aquatic exposure to nano-silver.

PubMed

Money, Eric S; Barton, Lauren E; Dawson, Joseph; Reckhow, Kenneth H; Wiesner, Mark R

2014-03-01

The adaptive nature of the Forecasting the Impacts of Nanomaterials in the Environment (FINE) Bayesian network is explored. We create an updated FINE model (FINEAgNP-2) for predicting aquatic exposure concentrations of silver nanoparticles (AgNP) by combining the expert-based parameters from the baseline model established in previous work with literature data related to particle behavior, exposure, and nano-ecotoxicology via parameter learning. We validate the AgNP forecast from the updated model using mesocosm-scale field data and determine the sensitivity of several key variables to changes in environmental conditions, particle characteristics, and particle fate. Results show that the prediction accuracy of the FINEAgNP-2 model increased approximately 70% over the baseline model, with an error rate of only 20%, suggesting that FINE is a reliable tool to predict aquatic concentrations of nano-silver. Sensitivity analysis suggests that fractal dimension, particle diameter, conductivity, time, and particle fate have the most influence on aquatic exposure given the current knowledge; however, numerous knowledge gaps can be identified to suggest further research efforts that will reduce the uncertainty in subsequent exposure and risk forecasts. Copyright © 2013 Elsevier B.V. All rights reserved.

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment.

PubMed

Rice, F L; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust. Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death. Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m(3) for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000). There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.

The effect of a low iron diet and early life methylmercury exposure in Daphnia pulex

PubMed Central

Hudson, Sherri L.; Doke, Dzigbodi A.; Gohlke, Julia M.

2016-01-01

Iron (Fe) deficiency increases risk for adverse health outcomes in humans; however little is known about the potential interaction with methylmercury (MeHg) exposure. Studies testing multiple stressor hypotheses are expensive and time consuming in mammalian model systems; therefore, determining relevance of alternative models is important. Daphnia pulex were fed standard or low-Fe diets of freshwater algae, Ankistrodesmus falcatus. MeHgCl (1600 ng/L) or vehicle was added to culture media for 24 h during early life, and the combinatorial effects of a low-Fe diet and MeHg exposure on lifespan, maturation time, and reproduction were evaluated. Lipid storage effects were measured using image analysis of Oil Red O staining and triacylglyceride quantification. Our results show a dose-dependent reduction in lifespan in D. pulex fed low Fe diets. Lipid analysis suggests an interactive effect of diet and MeHg exposure, with MeHg exposure increasing lipid storage in D. pulex fed a low-Fe diet. These findings suggest the effects of dietary iron intake and early life MeHg exposure in D. pulex may be mediated by changes in energetics that result in differential lipid storage. Therefore, lipid storage in D. pulex may be a useful screen for detecting long-term effects of multiple stressors early in life. PMID:26806633

Is there an association between aircraft noise exposure and the incidence of hypertension? A meta-analysis of 16784 participants.

PubMed

Huang, Di; Song, XuPing; Cui, Qi; Tian, Jinhui; Wang, Quan; Yang, Kehu

2015-01-01

To determine if aircraft noise exposure causes an increased incidence of hypertension among residents near airports. We conducted a meta-analysis of observational studies to evaluate the association between aircraft noise exposure and the incidence of hypertension. PubMed, Embase, Web of Science, the Cochrane Library, and the Chinese Biomedical Literature Database were searched without any restrictions. Odds ratios (ORs) with 95% confidence intervals (CIs) were extracted. The pooled ORs were calculated using both the fixed effects model and random effects model. All analyses were performed using STATA version 12.0 software (Stata Corporation, College Station, TX, USA). We examined five studies, comprising a total of 16,784 residents. The overall OR for hypertension in residents with aircraft noise exposure was 1.63 (95% CI, 1.14-2.33), and one of our included studies showed that there was no evidence that aircraft noise is a risk factor for hypertension in women. According to our subgroup analysis, the summary OR for the incidence was 1.31 (95% CI, 0.85-2.02) with I2 of 80.7% in women and 1.36 (95% CI, 1.15-1.60) with moderate heterogeneity in men. The pooled OR for the incidence of hypertension in residents aged over 55 years and under 55 years was 1.66 (95% CI, 1.21-2.27) with no heterogeneity and 1.78 (95% CI, 1.33-2.39) with I2 of 29.4%, respectively. The present meta-analysis suggests that aircraft noise could contribute to the prevalence of hypertension, but the evidence for a relationship between aircraft noise exposure and hypertension is still inconclusive because of limitations in study populations, exposure characterization, and adjustment for important confounders.

Is there an association between aircraft noise exposure and the incidence of hypertension? A meta-analysis of 16784 participants

PubMed Central

Huang, Di; Song, XuPing; Cui, Qi; Tian, Jinhui; Wang, Quan; Yang, Kehu

2015-01-01

To determine if aircraft noise exposure causes an increased incidence of hypertension among residents near airports. We conducted a meta-analysis of observational studies to evaluate the association between aircraft noise exposure and the incidence of hypertension. PubMed, Embase, Web of Science, the Cochrane Library, and the Chinese Biomedical Literature Database were searched without any restrictions. Odds ratios (ORs) with 95% confidence intervals (CIs) were extracted. The pooled ORs were calculated using both the fixed effects model and random effects model. All analyses were performed using STATA version 12.0 software (Stata Corporation, College Station, TX, USA). We examined five studies, comprising a total of 16,784 residents. The overall OR for hypertension in residents with aircraft noise exposure was 1.63 (95% CI, 1.14-2.33), and one of our included studies showed that there was no evidence that aircraft noise is a risk factor for hypertension in women. According to our subgroup analysis, the summary OR for the incidence was 1.31 (95% CI, 0.85-2.02) with I2 of 80.7% in women and 1.36 (95% CI, 1.15-1.60) with moderate heterogeneity in men. The pooled OR for the incidence of hypertension in residents aged over 55 years and under 55 years was 1.66 (95% CI, 1.21-2.27) with no heterogeneity and 1.78 (95% CI, 1.33-2.39) with I2 of 29.4%, respectively. The present meta-analysis suggests that aircraft noise could contribute to the prevalence of hypertension, but the evidence for a relationship between aircraft noise exposure and hypertension is still inconclusive because of limitations in study populations, exposure characterization, and adjustment for important confounders. PMID:25774612

Prenatal and Postnatal Exposure to Persistent Organic Pollutants and Infant Growth: A Pooled Analysis of Seven European Birth Cohorts.

PubMed

Iszatt, Nina; Stigum, Hein; Verner, Marc-André; White, Richard A; Govarts, Eva; Murinova, Lubica Palkovicova; Schoeters, Greet; Trnovec, Tomas; Legler, Juliette; Pelé, Fabienne; Botton, Jérémie; Chevrier, Cécile; Wittsiepe, Jürgen; Ranft, Ulrich; Vandentorren, Stéphanie; Kasper-Sonnenberg, Monika; Klümper, Claudia; Weisglas-Kuperus, Nynke; Polder, Anuschka; Eggesbø, Merete

2015-07-01

Infant exposure to persistent organic pollutants (POPs) may contribute to obesity. However, many studies so far have been small, focused on transplacental exposure, used an inappropriate measure to assess postnatal exposure through breastfeeding if any, or did not discern between prenatal and postnatal effects. We investigated prenatal and postnatal exposure to POPs and infant growth (a predictor of obesity). We pooled data from seven European birth cohorts with biomarker concentrations of polychlorinated biphenyl 153 (PCB-153) (n = 2,487), and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) (n = 1,864), estimating prenatal and postnatal POPs exposure using a validated pharmacokinetic model. Growth was change in weight-for-age z-score between birth and 24 months. Per compound, multilevel models were fitted with either POPs total exposure from conception to 24 months or prenatal or postnatal exposure. We found a significant increase in growth associated with p,p'-DDE, seemingly due to prenatal exposure (per interquartile increase in exposure, adjusted β = 0.12; 95% CI: 0.03, 0.22). Due to heterogeneity across cohorts, this estimate cannot be considered precise, but does indicate that an association with infant growth is present on average. In contrast, a significant decrease in growth was associated with postnatal PCB-153 exposure (β = -0.10; 95% CI: -0.19, -0.01). To our knowledge, this is the largest study to date of POPs exposure and infant growth, and it contains state-of-the-art exposure modeling. Prenatal p,p'-DDE was associated with increased infant growth, and postnatal PCB-153 with decreased growth at European exposure levels.

Providing a Theoretical Basis for Nanotoxicity Risk Analysis Departing from Traditional Physiologically-Based Pharmacokinetic (PBPK) Modeling

DTIC Science & Technology

2010-09-01

estimation of total exposure at any toxicological endpoint in the body. This effort is a significant contribution as it highlights future research needs...rigorous modeling of the nanoparticle transport by including physico-chemical properties of engineered particles. Similarly, toxicological dose-response...exposure risks as compared to larger sized particles of the same material. Although the toxicology of a base material may be thoroughly defined, the

Modeling Thermal Effects for Simulation of Post Exposure Baking (PEB) Process in Positive Photoresist

NASA Astrophysics Data System (ADS)

Asai, Satoru; Hanyu, Isamu; Nunokawa, Mitsuji; Abe, Masayuki

1991-03-01

We studied the thermal effects in a positive photoresist during post exposure baking (PEB). Infrared analysis and the reduced dissolution rate in the exposed resist suggest that the carboxylic acid is decreased and/or that ECA solvent evaporates. In order to simulate the effects, we assume that the concentration of the alkali-soluble material (carboxylic acid) decreases equivalently. Our model explains PEB and enables its effects to be simulated.

SPATIAL ANALYSIS OF AIR POLLUTION AND DEVELOPMENT OF A LAND-USE REGRESSION ( LUR ) MODEL IN AN URBAN AIRSHED

EPA Science Inventory

The Detroit Children's Health Study is an epidemiologic study examining associations between chronic ambient environmental exposures to gaseous air pollutants and respiratory health outcomes among elementary school-age children in an urban airshed. The exposure component of this...

Analysis of a potential trigger of an acute illness.

PubMed

Becker, Niels G; Salim, Agus; Kelman, Christopher W

2006-01-01

Sometimes certain short-term risk exposures are postulated to act as a trigger for the onset of a specific acute illness. When the incidence of the illness is low it is desirable to investigate this possible association using only data on cases detected during a specific observation period. Here we propose an analysis for such a study based on a model expressed in terms of the probability that the exposure triggers the illness and a random delay from a triggered illness until its diagnosis. Both the natural hazard rate for the illness and the probability that the exposure triggers the illness are assumed to be small and possibly dependent on age and covariates such as sex and duration or severity of the exposure. The method of analysis is illustrated with a study of the association between long flights and hospitalization for venous thromboembolism.

Prescription-drug-related risk in driving: comparing conventional and lasso shrinkage logistic regressions.

PubMed

Avalos, Marta; Adroher, Nuria Duran; Lagarde, Emmanuel; Thiessard, Frantz; Grandvalet, Yves; Contrand, Benjamin; Orriols, Ludivine

2012-09-01

Large data sets with many variables provide particular challenges when constructing analytic models. Lasso-related methods provide a useful tool, although one that remains unfamiliar to most epidemiologists. We illustrate the application of lasso methods in an analysis of the impact of prescribed drugs on the risk of a road traffic crash, using a large French nationwide database (PLoS Med 2010;7:e1000366). In the original case-control study, the authors analyzed each exposure separately. We use the lasso method, which can simultaneously perform estimation and variable selection in a single model. We compare point estimates and confidence intervals using (1) a separate logistic regression model for each drug with a Bonferroni correction and (2) lasso shrinkage logistic regression analysis. Shrinkage regression had little effect on (bias corrected) point estimates, but led to less conservative results, noticeably for drugs with moderate levels of exposure. Carbamates, carboxamide derivative and fatty acid derivative antiepileptics, drugs used in opioid dependence, and mineral supplements of potassium showed stronger associations. Lasso is a relevant method in the analysis of databases with large number of exposures and can be recommended as an alternative to conventional strategies.

Modeling exposure–lag–response associations with distributed lag non-linear models

PubMed Central

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

Immortal time bias in observational studies of time-to-event outcomes.

PubMed

Jones, Mark; Fowler, Robert

2016-12-01

The purpose of the study is to show, through simulation and example, the magnitude and direction of immortal time bias when an inappropriate analysis is used. We compare 4 methods of analysis for observational studies of time-to-event outcomes: logistic regression, standard Cox model, landmark analysis, and time-dependent Cox model using an example data set of patients critically ill with influenza and a simulation study. For the example data set, logistic regression, standard Cox model, and landmark analysis all showed some evidence that treatment with oseltamivir provides protection from mortality in patients critically ill with influenza. However, when the time-dependent nature of treatment exposure is taken account of using a time-dependent Cox model, there is no longer evidence of a protective effect of treatment. The simulation study showed that, under various scenarios, the time-dependent Cox model consistently provides unbiased treatment effect estimates, whereas standard Cox model leads to bias in favor of treatment. Logistic regression and landmark analysis may also lead to bias. To minimize the risk of immortal time bias in observational studies of survival outcomes, we strongly suggest time-dependent exposures be included as time-dependent variables in hazard-based analyses. Copyright © 2016 Elsevier Inc. All rights reserved.

Leaching of plastic additives to marine organisms.

PubMed

Koelmans, Albert A; Besseling, Ellen; Foekema, Edwin M

2014-04-01

It is often assumed that ingestion of microplastics by aquatic species leads to increased exposure to plastic additives. However, experimental data or model based evidence is lacking. Here we assess the potential of leaching of nonylphenol (NP) and bisphenol A (BPA) in the intestinal tracts of Arenicola marina (lugworm) and Gadus morhua (North Sea cod). We use a biodynamic model that allows calculations of the relative contribution of plastic ingestion to total exposure of aquatic species to chemicals residing in the ingested plastic. Uncertainty in the most crucial parameters is accounted for by probabilistic modeling. Our conservative analysis shows that plastic ingestion by the lugworm yields NP and BPA concentrations that stay below the lower ends of global NP and BPA concentration ranges, and therefore are not likely to constitute a relevant exposure pathway. For cod, plastic ingestion appears to be a negligible pathway for exposure to NP and BPA. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparative pharmacokinetic study of the role of gender and developmental differences in occupational and environmental exposure to benzene. Master's thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, E.A.

The purpose of this study is two-fold. First, it shows that physiological differences between men and women result in gender-specific exposures with respect to benzene. Second, it assesses the potential for a lactating woman's occupational and personal benzene exposure to impact a nursing infant's exposure, highlighting the possibility of subjecting an infant to the effects of industrial chemicals via breast feeding. This study employs physiologically based pharmacokinetic (PBPK) modeling to investigate the influence of physiological parameters and to evaluate the ability of inhaled benzene to transfer from mother to infant through breastmilk. The models are run through scenarios that simulatemore » occupational, smoking, and background exposures. The gender comparison is facilitated by a sensitivity analysis. The blood/air partition coefficient and maximum velocity of metabolism were found to substantially impact model output. These values were both higher in women and caused an increase in the percentage of benzene metabolized in all of the exposure scenarios. The study of lactating women and infants is essentially theoretical. There is evidence that over 65% of an infant's benzene exposure can be attributed to contaminated breastmilk. A large portion of the ingested exposure can be eliminated by adjusting the mother's working or nursing schedule. Benzene, Physiologically based pharmacokinetics, PBPK.« less

An Integrated Approach to Assess Exposure and Health-Risk from Polycyclic Aromatic Hydrocarbons (PAHs) in a Fastener Manufacturing Industry

PubMed Central

Hsu, Hsin-I; Lin, Ming-Yeng; Chen, Yu-Cheng; Chen, Wang-Yi; Yoon, Chungsik; Chen, Mei-Ru; Tsai, Perng-Jy

2014-01-01

An integrated approach was developed to assess exposure and health-risk from polycyclic aromatic hydrocarbons (PAHs) contained in oil mists in a fastener manufacturing industry. One previously developed model and one new model were adopted for predicting oil mist exposure concentrations emitted from metal work fluid (MWF) and PAHs contained in MWF by using the fastener production rate (Pr) and cumulative fastener production rate (CPr) as predictors, respectively. By applying the annual Pr and CPr records to the above two models, long-term workplace PAH exposure concentrations were predicted. In addition, true exposure data was also collected from the field. The predicted and measured concentrations respectively served as the prior and likelihood distributions in the Bayesian decision analysis (BDA), and the resultant posterior distributions were used to determine the long-term exposure and health-risks posed on workers. Results show that long term exposures to PAHs would result in a 3.1%, 96.7%, and 73.4% chance of exceeding the PEL-TWA (0.2 mg/m3), action level (0.1 mg/m3), and acceptable health risk (10−3), respectively. In conclusion, preventive measures should be taken immediately to reduce workers’ PAH exposures. PMID:25226413

Using exposure windows to explore an elusive biomarker: blood manganese.

PubMed

Baker, Marissa G; Stover, Bert; Simpson, Christopher D; Sheppard, Lianne; Seixas, Noah S

2016-05-01

We sought to understand the time course between exposure to manganese (Mn) and uptake into the blood, to allow a more meaningful interpretation of exposure biomarker data, and to determine the utility of blood as a biomarker of Mn exposure. Welder trainees were monitored over the course of a five-quarter training program. Each quarter, trainees gave eight blood samples and had personal air monitoring four times. A mixed model was fit to obtain estimates of airborne exposure by welding type (fixed effect), adjusted for subject (random effect). Considering weekends and days absent as zero exposure, estimated exposures were summed over various exposure windows and related to measured blood manganese (MnB) using a mixed model. A relationship consistent with zero was found between MnB and modeled 1 or 7 days of exposure. After 30 days of preceding exposure, a 1 mg-days/m(3) increase in air Mn is associated with a 0.57 ng/mL increase in MnB (95% CI -0.04, 1.19). Considering a 90-day exposure window and a cumulative exposure window, a 1 mg-days/m(3) increase in air Mn is associated with a 0.26 (95% CI 0.005, 0.51) and 0.09 (95% CI 0.006, 0.17) ng/mL increase in MnB, respectively. From this analysis, MnB may begin to act as a biomarker of Mn exposure over longer time periods, or at higher levels of exposure. This novel study design allowed investigation of how MnB relates to different time windows of exposure, representing the most robust Mn exposure assessment in the biomarker literature.

Environmental hazards and stress: evidence from the Texas City Stress and Health Study

PubMed Central

Peek, MK; Cutchin, MP; Freeman, D; Stowe, RP; Goodwin, JS

2013-01-01

Background Substantial research has suggested that exposure to environmental health hazards, such as polluting industrial activity, has deleterious effects on psychological and physiological well-being. However, one gap in the existing literature is comparative analysis of objective and subjective exposure's relative association with various measurable outcomes of exposure. Methods These relationships were explored within a community sample of 2604 respondents living near a large petrochemical complex in Texas City, Texas, USA. Objective exposure was investigated using distance of residence from a cluster of petrochemical plants and subjective exposure using residents' concern about potential health effects from those plants. Regression models were then used to examine how each type of exposure predicts perceived stress, physiological markers of stress and perceived health. Results Results suggest that objective exposure was associated primarily with markers of physiological stress (interleukin-6 and viral reactivation), and subjective exposure (concern about petrochemical health risk) was associated with variables assessing perceived health. Conclusions From the analysis, it can be inferred that, in the context of an environmental hazard of this type, subjective exposure may be at least as important a predictor of poor health outcomes as objective exposure. PMID:19282316

Summary of ionizing radiation analysis on the Long Duration Exposure Facility

NASA Technical Reports Server (NTRS)

Parnell, T. A.

1991-01-01

The Ionizing Radiation Special Investigation Group (IRSIG) for the Long Duration Exposure Facility (LDEF) was established to perform radiation measurements and analysis not planned in the original experiments, and to assure availability of LDEF analysis results in a form useful to future missions. The IRSIG has organized extensive induced radioactivity measurements throughout LDEF, and a comprehensive program to compare the LDEF radiation measurements to values calculated using environment models. The activities and present status of the Group is described. The ionizing radiation results presented is summarized.

A quantitative visual dashboard to explore exposures to ...

EPA Pesticide Factsheets

The Exposure Prioritization (Ex Priori) model features a simplified, quantitative visual dashboard to explore exposures across chemical space. Diverse data streams are integrated within the interface such that different exposure scenarios for “individual,” “population,” or “professional” time-use profiles can be interchanged to tailor exposure and quantitatively explore multi-chemical signatures of exposure, internalized dose (uptake), body burden, and elimination. Ex Priori will quantitatively extrapolate single-point estimates of both exposure and internal dose for multiple exposure scenarios, factors, products, and pathways. Currently, EPA is investigating its usefulness in life cycle analysis, insofar as its ability to enhance exposure factors used in calculating characterization factors for human health. Presented at 2016 Annual ISES Meeting held in Utrecht, The Netherlands, from 9-13 October 2016.

Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

PubMed

Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

2017-05-01

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

New regression model for predicting hand-arm vibration (HAV) of Malaysian Army (MA) three-tonne truck steering wheels.

PubMed

Aziz, Shamsul Akmar Ab; Nuawi, Mohd Zaki; Nor, Mohd Jailani Mohd

2015-01-01

The objective of this study was to present a new method for determination of hand-arm vibration (HAV) in Malaysian Army (MA) three-tonne truck steering wheels based on changes in vehicle speed using regression model and the statistical analysis method known as Integrated Kurtosis-Based Algorithm for Z-Notch Filter Technique Vibro (I-kaz Vibro). The test was conducted for two different road conditions, tarmac and dirt roads. HAV exposure was measured using a Brüel & Kjær Type 3649 vibration analyzer, which is capable of recording HAV exposures from steering wheels. The data was analyzed using I-kaz Vibro to determine the HAV values in relation to varying speeds of a truck and to determine the degree of data scattering for HAV data signals. Based on the results obtained, HAV experienced by drivers can be determined using the daily vibration exposure A(8), I-kaz Vibro coefficient (Ƶ(v)(∞)), and the I-kaz Vibro display. The I-kaz Vibro displays also showed greater scatterings, indicating that the values of Ƶ(v)(∞) and A(8) were increasing. Prediction of HAV exposure was done using the developed regression model and graphical representations of Ƶ(v)(∞). The results of the regression model showed that Ƶ(v)(∞) increased when the vehicle speed and HAV exposure increased. For model validation, predicted and measured noise exposures were compared, and high coefficient of correlation (R(2)) values were obtained, indicating that good agreement was obtained between them. By using the developed regression model, we can easily predict HAV exposure from steering wheels for HAV exposure monitoring.

Noninvasive Biomonitoring Approaches to Determine Dosimetry and Risk Following Acute Chemical Exposure: Analysis of Lead or Organophosphate Insecticide in Saliva

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timchalk, Chuck; Poet, Torka S.; Kousba, Ahmed A.

2004-04-01

There is a need to develop approaches for assessing risk associated with acute exposures to a broad-range of chemical agents and to rapidly determine the potential implications to human health. Non-invasive biomonitoring approaches are being developed using reliable portable analytical systems to quantitate dosimetry utilizing readily obtainable body fluids, such as saliva. Saliva has been used to evaluate a broad range of biomarkers, drugs, and environmental contaminants including heavy metals and pesticides. To advance the application of non-invasive biomonitoring a microfluidic/ electrochemical device has also been developed for the analysis of lead (Pb), using square wave anodic stripping voltammetry. Themore » system demonstrates a linear response over a broad concentration range (1 2000 ppb) and is capable of quantitating saliva Pb in rats orally administered acute doses of Pb-acetate. Appropriate pharmacokinetic analyses have been used to quantitate systemic dosimetry based on determination of saliva Pb concentrations. In addition, saliva has recently been used to quantitate dosimetry following exposure to the organophosphate insecticide chlorpyrifos in a rodent model system by measuring the major metabolite, trichloropyridinol, and saliva cholinesterase inhibition following acute exposures. These results suggest that technology developed for non-invasive biomonitoring can provide a sensitive, and portable analytical tool capable of assessing exposure and risk in real-time. By coupling these non-invasive technologies with pharmacokinetic modeling it is feasible to rapidly quantitate acute exposure to a broad range of chemical agents. In summary, it is envisioned that once fully developed, these monitoring and modeling approaches will be useful for accessing acute exposure and health risk.« less

Causal mediation analysis for longitudinal data with exogenous exposure.

PubMed

Bind, M-A C; Vanderweele, T J; Coull, B A; Schwartz, J D

2016-01-01

Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The role of the location of personal exposimeters on the human body in their use for assessing exposure to the electromagnetic field in the radiofrequency range 98-2450 MHz and compliance analysis: evaluation by virtual measurements.

PubMed

Gryz, Krzysztof; Zradziński, Patryk; Karpowicz, Jolanta

2015-01-01

The use of radiofrequency (98-2450 MHz range) personal exposimeters to measure the electric field (E-field) in far-field exposure conditions was modelled numerically using human body model Gustav and finite integration technique software. Calculations with 256 models of exposure scenarios show that the human body has a significant influence on the results of measurements using a single body-worn exposimeter in various locations near the body ((from -96 to +133)%, measurement errors with respect to the unperturbed E-field value). When an exposure assessment involves the exposure limitations provided for the strength of an unperturbed E-field. To improve the application of exposimeters in compliance tests, such discrepancies in the results of measurements by a body-worn exposimeter may be compensated by using of a correction factor applied to the measurement results or alternatively to the exposure limit values. The location of a single exposimeter on the waist to the back side of the human body or on the front of the chest reduces the range of exposure assessments uncertainty (covering various exposure conditions). However, still the uncertainty of exposure assessments using a single exposimeter remains significantly higher than the assessment of the unperturbed E-field using spot measurements.

The Role of the Location of Personal Exposimeters on the Human Body in Their Use for Assessing Exposure to the Electromagnetic Field in the Radiofrequency Range 98–2450 MHz and Compliance Analysis: Evaluation by Virtual Measurements

PubMed Central

Zradziński, Patryk

2015-01-01

The use of radiofrequency (98–2450 MHz range) personal exposimeters to measure the electric field (E-field) in far-field exposure conditions was modelled numerically using human body model Gustav and finite integration technique software. Calculations with 256 models of exposure scenarios show that the human body has a significant influence on the results of measurements using a single body-worn exposimeter in various locations near the body ((from −96 to +133)%, measurement errors with respect to the unperturbed E-field value). When an exposure assessment involves the exposure limitations provided for the strength of an unperturbed E-field. To improve the application of exposimeters in compliance tests, such discrepancies in the results of measurements by a body-worn exposimeter may be compensated by using of a correction factor applied to the measurement results or alternatively to the exposure limit values. The location of a single exposimeter on the waist to the back side of the human body or on the front of the chest reduces the range of exposure assessments uncertainty (covering various exposure conditions). However, still the uncertainty of exposure assessments using a single exposimeter remains significantly higher than the assessment of the unperturbed E-field using spot measurements. PMID:25879021

[Bibliometrics and visualization analysis of land use regression models in ambient air pollution research].

PubMed

Zhang, Y J; Zhou, D H; Bai, Z P; Xue, F X

2018-02-10

Objective: To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies. Methods: Relevant literature from the PubMed database before June 30, 2017 was analyzed, using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0). Keywords co-occurrence networks, cluster mapping and timeline mapping were generated, using the CiteSpace 5.1.R5 software. Relevant literature identified in three Chinese databases was also reviewed. Results: Four hundred sixty four relevant papers were retrieved from the PubMed database. The number of papers published showed an annual increase, in line with the growing trend of the index. Most papers were published in the journal of Environmental Health Perspectives . Results from the Co-word cluster analysis identified five clusters: cluster#0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution; cluster#1 referred to land use regression modeling and exposure assessment; cluster#2 was related to the epidemiology on traffic exposure; cluster#3 dealt with the exposure to ultrafine particles and related health effects; cluster#4 described the exposure to black carbon and related health effects. Data from Timeline mapping indicated that cluster#0 and#1 were the main research areas while cluster#3 and#4 were the up-coming hot areas of research. Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling. Conclusion: In order to better assess the health-related risks of ambient air pollution, and to best inform preventative public health intervention policies, application of LUR models to environmental epidemiology studies in China should be encouraged.

Assessing model uncertainty using hexavalent chromium and ...

EPA Pesticide Factsheets

Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective of this analysis is to characterize model uncertainty by evaluating the variance in estimates across several epidemiologic analyses.Methods: This analysis compared 7 publications analyzing two different chromate production sites in Ohio and Maryland. The Ohio cohort consisted of 482 workers employed from 1940-72, while the Maryland site employed 2,357 workers from 1950-74. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability in estimates across and within model forms. A total of 7 similarly parameterized analyses were considered across model forms, and 23 analyses with alternative parameterizations were considered within model form (14 Cox; 9 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients for 7 similar analyses ranged from 2.47

Exploration of the molecular basis of blast injury in a biofidelic model of traumatic brain injury

NASA Astrophysics Data System (ADS)

Thielen, P.; Mehoke, T.; Gleason, J.; Iwaskiw, A.; Paulson, J.; Merkle, A.; Wester, B.; Dymond, J.

2018-01-01

Biological response to blast overpressure is complex and results in various and potentially non-concomitant acute and long-term deficits to exposed individuals. Clinical links between blast severity and injury outcomes remain elusive and have yet to be fully described, resulting in a critical inability to develop associated protection and mitigation strategies. Further, experimental models frequently fail to reproduce observed physiological phenomena and/or introduce artifacts that confound analysis and reproducibility. New models are required that employ consistent mechanical inputs, scale with biological analogs and known clinical data, and permit high-throughput examination of biological responses for a range of environmental and battlefield- relevant exposures. Here we describe a novel, biofidelic headform capable of integrating complex biological samples for blast exposure studies. We additionally demonstrate its utility in detecting acute transcriptional responses in the model organism Caenorhabditis elegans after exposure to blast overpressure. This approach enables correlation between mechanical exposure and biological outcome, permitting both the enhancement of existing surrogate and computational models and the high-throughput biofidelic testing of current and future protection systems.

Residential magnetic fields predicted from wiring configurations: I. Exposure model.

PubMed

Bowman, J D; Thomas, D C; Jiang, L; Jiang, F; Peters, J M

1999-10-01

A physically based model for residential magnetic fields from electric transmission and distribution wiring was developed to reanalyze the Los Angeles study of childhood leukemia by London et al. For this exposure model, magnetic field measurements were fitted to a function of wire configuration attributes that was derived from a multipole expansion of the Law of Biot and Savart. The model parameters were determined by nonlinear regression techniques, using wiring data, distances, and the geometric mean of the ELF magnetic field magnitude from 24-h bedroom measurements taken at 288 homes during the epidemiologic study. The best fit to the measurement data was obtained with separate models for the two major utilities serving Los Angeles County. This model's predictions produced a correlation of 0.40 with the measured fields, an improvement on the 0.27 correlation obtained with the Wertheimer-Leeper (WL) wire code. For the leukemia risk analysis in a companion paper, the regression model predicts exposures to the 24-h geometric mean of the ELF magnetic fields in Los Angeles homes where only wiring data and distances have been obtained. Since these input parameters for the exposure model usually do not change for many years, the predicted magnetic fields will be stable over long time periods, just like the WL code. If the geometric mean is not the exposure metric associated with cancer, this regression technique could be used to estimate long-term exposures to temporal variability metrics and other characteristics of the ELF magnetic field which may be cancer risk factors.

Is the perception of clean, humid air indeed affected by cooling the respiratory tract?

NASA Astrophysics Data System (ADS)

Burek, Rudolf; Polednik, Bernard; Guz, Łukasz

2017-07-01

The study aims at determining exposure-response relationships after short exposure to clean air and long exposure to air polluted by people. The impact of water vapor content in the indoor air on its acceptability (ACC) was assessed by the occupants after a short exposure to clean air and an hour-long exposure to increasingly polluted air. The study presents a critical analysis pertaining to the stimulation of olfactory sensations by the air enthalpy suggested in previous models and proposes a new model based on the Weber-Fechner law. Our assumption was that water vapor is the stimulus of olfactory sensations. The model was calibrated and verified in field conditions, in a mechanically ventilated and air conditioned auditorium. Measurements of the air temperature, relative humidity, velocity and CO2 content were carried out; the acceptability of air quality was assessed by 162 untrained students. The subjective assessments and the measurements of the environmental qualities allowed for determining the Weber coefficients and the threshold concentrations of water vapor, as well as for establishing the limitations of the model at short and long exposure to polluted indoor air. The results are in agreement with previous studies. The standard error equals 0.07 for immediate assessments and 0.17 for assessments after adaptation. Based on the model one can predict the ACC assessments of trained and untrained participants.

Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

PubMed Central

Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

2013-01-01

Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

User's Manual for RESRAD-OFFSITE Version 2.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, C.; Gnanapragasam, E.; Biwer, B. M.

2007-09-05

The RESRAD-OFFSITE code is an extension of the RESRAD (onsite) code, which has been widely used for calculating doses and risks from exposure to radioactively contaminated soils. The development of RESRAD-OFFSITE started more than 10 years ago, but new models and methodologies have been developed, tested, and incorporated since then. Some of the new models have been benchmarked against other independently developed (international) models. The databases used have also expanded to include all the radionuclides (more than 830) contained in the International Commission on Radiological Protection (ICRP) 38 database. This manual provides detailed information on the design and application ofmore » the RESRAD-OFFSITE code. It describes in detail the new models used in the code, such as the three-dimensional dispersion groundwater flow and radionuclide transport model, the Gaussian plume model for atmospheric dispersion, and the deposition model used to estimate the accumulation of radionuclides in offsite locations and in foods. Potential exposure pathways and exposure scenarios that can be modeled by the RESRAD-OFFSITE code are also discussed. A user's guide is included in Appendix A of this manual. The default parameter values and parameter distributions are presented in Appendix B, along with a discussion on the statistical distributions for probabilistic analysis. A detailed discussion on how to reduce run time, especially when conducting probabilistic (uncertainty) analysis, is presented in Appendix C of this manual.« less

Using full-cohort data in nested case-control and case-cohort studies by multiple imputation.

PubMed

Keogh, Ruth H; White, Ian R

2013-10-15

In many large prospective cohorts, expensive exposure measurements cannot be obtained for all individuals. Exposure-disease association studies are therefore often based on nested case-control or case-cohort studies in which complete information is obtained only for sampled individuals. However, in the full cohort, there may be a large amount of information on cheaply available covariates and possibly a surrogate of the main exposure(s), which typically goes unused. We view the nested case-control or case-cohort study plus the remainder of the cohort as a full-cohort study with missing data. Hence, we propose using multiple imputation (MI) to utilise information in the full cohort when data from the sub-studies are analysed. We use the fully observed data to fit the imputation models. We consider using approximate imputation models and also using rejection sampling to draw imputed values from the true distribution of the missing values given the observed data. Simulation studies show that using MI to utilise full-cohort information in the analysis of nested case-control and case-cohort studies can result in important gains in efficiency, particularly when a surrogate of the main exposure is available in the full cohort. In simulations, this method outperforms counter-matching in nested case-control studies and a weighted analysis for case-cohort studies, both of which use some full-cohort information. Approximate imputation models perform well except when there are interactions or non-linear terms in the outcome model, where imputation using rejection sampling works well. Copyright © 2013 John Wiley & Sons, Ltd.

Children exposure to PM levels in a typical school morning

NASA Astrophysics Data System (ADS)

Valente, J.; Amorim, J. H.; Cascão, P.; Rodrigues, V.; Borrego, C.

2012-10-01

One of the major challenges to urban sustainability is the threat posed by air pollution, being exposure to ambient air pollutants associated with a high rate of premature deaths. Therefore, the study of the exposure of people, and in particular of vulnerable population groups such as children, to air pollution is a subject of paramount importance. In this paper a CFD model is used to simulate the particulate matter personal exposure of students in their school routine (both daily walk to and permanence in school). Under the concept of COST TU0801, the usability of a 3D city model is evaluated. The analysis was carried out for 4 children, with 4 alternative walking routes to school and using 4 different classrooms. Results indicate that the individual exposure of children is extremely spatially dependent, as a consequence of the wind flow and air pollutant dispersion patterns.

FACTORS INFLUENCING TOTAL DIETARY EXPOSURES OF YOUNG CHILDREN

EPA Science Inventory

A deterministic model was developed to identify the critical input parameters needed to assess dietary intakes of young children. The model was used as a framework for understanding the important factors in data collection and data analysis. Factors incorporated into the model i...

Identifiability of PBPK Models with Applications to Dimethylarsinic Acid Exposure

EPA Science Inventory

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss diff...

A metabolomic, geographic, and seasonal analysis of the contribution of pollen-derived adenosine to allergic sensitization.

PubMed

Mueller, Geoffrey A; Thompson, Peter M; DeRose, Eugene F; O'Connell, Thomas M; London, Robert E

2016-12-01

Studies on ragweed and birch pollen extracts suggested that the adenosine content is an important factor in allergic sensitization. However, exposure levels from other pollens and considerations of geographic and seasonal factors have not been evaluated. This study compared the metabolite profile of pollen species important for allergic disease, specifically measured the adenosine content, and evaluated exposure to pollen-derived adenosine. An NMR metabolomics approach was used to measure metabolite concentrations in twenty-six pollen extracts. Pollen count data was analyzed from five cities to model exposure. A principal component analysis of the various metabolites identified by NMR showed that pollen extracts could be differentiated primarily by sugar content: glucose, fructose, sucrose, and myo-inositol. In extracts of 10 mg of pollen/ml, the adenosine was highest for grasses (45 μM) followed by trees (23 μM) and weeds (19 μM). Pollen count data showed that tree pollen was typically 5-10 times the amount of other pollens. At the daily peaks of tree, grass, and weed season the pollen-derived adenosine exposure per day is likely to only be 1.1, 0.11, and 0.12 μg, respectively. Seasonal models of pollen exposure and respiration suggest that it would be a rare event limited to tree pollen season for concentrations of pollen-derived adenosine to approach physiological levels. Sugar content and other metabolites may be useful in classifying pollens. Unless other factors create localized exposures that are very different from these models, pollen-derived adenosine is unlikely to be a major factor in allergic sensitization.

Modeling U-shaped dose-response curves for manganese using categorical regression.

PubMed

Milton, Brittany; Krewski, Daniel; Mattison, Donald R; Karyakina, Nataliya A; Ramoju, Siva; Shilnikova, Natalia; Birkett, Nicholas; Farrell, Patrick J; McGough, Doreen

2017-01-01

Manganese is an essential nutrient which can cause adverse effects if ingested to excess or in insufficient amounts, leading to a U-shaped exposure-response relationship. Methods have recently been developed to describe such relationships by simultaneously modeling the exposure-response curves for excess and deficiency. These methods incorporate information from studies with diverse adverse health outcomes within the same analysis by assigning severity scores to achieve a common response metric for exposure-response modeling. We aimed to provide an estimate of the optimal dietary intake of manganese to balance adverse effects from deficient or excess intake. We undertook a systematic review of the literature from 1930 to 2013 and extracted information on adverse effects from manganese deficiency and excess to create a database on manganese toxicity following oral exposure. Although data were available for seven different species, only the data from rats was sufficiently comprehensive to support analytical modelling. The toxicological outcomes were standardized on an 18-point severity scale, allowing for a common analysis of all available toxicological data. Logistic regression modelling was used to simultaneously estimate the exposure-response profile for dietary deficiency and excess for manganese and generate a U-shaped exposure-response curve for all outcomes. Data were available on the adverse effects of 6113 rats. The nadir of the U-shaped joint response curve occurred at a manganese intake of 2.70mg/kgbw/day with a 95% confidence interval of 2.51-3.02. The extremes of both deficient and excess intake were associated with a 90% probability of some measurable adverse event. The manganese database supports estimation of optimal intake based on combining information on adverse effects from systematic review of published experiments. There is a need for more studies on humans. Translation of our results from rats to humans will require adjustment for interspecies differences in sensitivity to manganese. Copyright © 2016 Elsevier B.V. All rights reserved.

The Effect of Ongoing Exposure Dynamics in Dose Response Relationships

PubMed Central

Pujol, Josep M.; Eisenberg, Joseph E.; Haas, Charles N.; Koopman, James S.

2009-01-01

Characterizing infectivity as a function of pathogen dose is integral to microbial risk assessment. Dose-response experiments usually administer doses to subjects at one time. Phenomenological models of the resulting data, such as the exponential and the Beta-Poisson models, ignore dose timing and assume independent risks from each pathogen. Real world exposure to pathogens, however, is a sequence of discrete events where concurrent or prior pathogen arrival affects the capacity of immune effectors to engage and kill newly arriving pathogens. We model immune effector and pathogen interactions during the period before infection becomes established in order to capture the dynamics generating dose timing effects. Model analysis reveals an inverse relationship between the time over which exposures accumulate and the risk of infection. Data from one time dose experiments will thus overestimate per pathogen infection risks of real world exposures. For instance, fitting our model to one time dosing data reveals a risk of 0.66 from 313 Cryptosporidium parvum pathogens. When the temporal exposure window is increased 100-fold using the same parameters fitted by our model to the one time dose data, the risk of infection is reduced to 0.09. Confirmation of this risk prediction requires data from experiments administering doses with different timings. Our model demonstrates that dose timing could markedly alter the risks generated by airborne versus fomite transmitted pathogens. PMID:19503605

Expected number of asbestos-related lung cancers in the Netherlands in the next two decades: a comparison of methods.

PubMed

Van der Bij, Sjoukje; Vermeulen, Roel C H; Portengen, Lützen; Moons, Karel G M; Koffijberg, Hendrik

2016-05-01

Exposure to asbestos fibres increases the risk of mesothelioma and lung cancer. Although the vast majority of mesothelioma cases are caused by asbestos exposure, the number of asbestos-related lung cancers is less clear. This number cannot be determined directly as lung cancer causes are not clinically distinguishable but may be estimated using varying modelling methods. We applied three different modelling methods to the Dutch population supplemented with uncertainty ranges (UR) due to uncertainty in model input values. The first method estimated asbestos-related lung cancer cases directly from observed and predicted mesothelioma cases in an age-period-cohort analysis. The second method used evidence on the fraction of lung cancer cases attributable (population attributable risk (PAR)) to asbestos exposure. The third method incorporated risk estimates and population exposure estimates to perform a life table analysis. The three methods varied substantially in incorporated evidence. Moreover, the estimated number of asbestos-related lung cancer cases in the Netherlands between 2011 and 2030 depended crucially on the actual method applied, as the mesothelioma method predicts 17 500 expected cases (UR 7000-57 000), the PAR method predicts 12 150 cases (UR 6700-19 000), and the life table analysis predicts 6800 cases (UR 6800-33 850). The three different methods described resulted in absolute estimates varying by a factor of ∼2.5. These results show that accurate estimation of the impact of asbestos exposure on the lung cancer burden remains a challenge. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy

Treesearch

Michele Salis; Alan A. Ager; Fermin J. Alcasena; Bachisio Arca; Mark A. Finney; Grazia Pellizzaro; Donatella Spano

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn...

Proteomic profiling of halloysite clay nanotube exposure in intestinal cell co-culture.

PubMed

Lai, Xianyin; Agarwal, Mangilal; Lvov, Yuri M; Pachpande, Chetan; Varahramyan, Kody; Witzmann, Frank A

2013-11-01

Halloysite is aluminosilicate clay with a hollow tubular structure with nanoscale internal and external diameters. Assessment of halloysite biocompatibility has gained importance in view of its potential application in oral drug delivery. To investigate the effect of halloysite nanotubes on an in vitro model of the large intestine, Caco-2/HT29-MTX cells in monolayer co-culture were exposed to nanotubes for toxicity tests and proteomic analysis. Results indicate that halloysite exhibits a high degree of biocompatibility characterized by an absence of cytotoxicity, in spite of elevated pro-inflammatory cytokine release. Exposure-specific changes in expression were observed among 4081 proteins analyzed. Bioinformatic analysis of differentially expressed protein profiles suggest that halloysite stimulates processes related to cell growth and proliferation, subtle responses to cell infection, irritation and injury, enhanced antioxidant capability, and an overall adaptive response to exposure. These potentially relevant functional effects warrant further investigation in in vivo models and suggest that chronic or bolus occupational exposure to halloysite nanotubes may have unintended outcomes. Copyright © 2013 John Wiley & Sons, Ltd.

Naphthalene and Naphthoquinone: Distributions and Human Exposure in the Los Angeles Basin

NASA Astrophysics Data System (ADS)

Lu, R.; Wu, J.; Turco, R.; Winer, A. M.; Atkinson, R.; Paulson, S.; Arey, J.; Lurmann, F.

2003-12-01

Naphthalene is the simplest and most abundant of the polycyclic aromatic hydrocarbons (PAHs). Naphthalene is found primarily in the gas-phase and has been detected in both outdoor and indoor samples. Evaporation from naphthalene-containing products (including gasoline), and during refining operations, are important sources of naphthalene in air. Naphthalene is also emitted during the combustion of fossil fuels and wood, and is a component of vehicle exhaust. Exposure to high concentrations of naphthalene can damage or destroy red blood cells, causing hemolytic anemia. If inhaled over a long period of time, naphthalene may cause kidney and liver damage, skin allergy and dermatitis, cataracts and retinal damage, as well as attack the central nervous system. Naphthalene has been found to cause cancer as a result of inhalation in animal tests. Naphthoquinones are photooxidation products of naphthalene and the potential health effects of exposure to these quinones are a current focus of research. We are developing and applying models that can be used to assess human exposure to naphthalene and its photooxidation products in major air basins such as California South Coast Air Basin (SoCAB). The work utilizes the Surface Meteorology and Ozone Generation (SMOG) airshed model, and the REgional Human EXposure (REHEX) model, including an analysis of individual exposure. We will present and discuss simulations of basin-wide distributions of, and human exposures to, naphthalene and naphthoquinone, with emphasis on the uncertainties in these estimates of atmospheric concentrations and human exposure. Regional modeling of pollutant sources and exposures can lead to cost-effective and optimally health-protective emission control strategies.

A MODEL TO EVALUATE PAST EXPOSURE TO 2,3,7,8 ...

EPA Pesticide Factsheets

Data from several studies suggest that concentrations of dioxins rose in the environment from the 1930s to about the 1960s/70s and have been declining over the last decade or two. The most direct evidence of this trend comes from lake core sediments, which can be used to estimate past atmospheric depositions of dioxins. The primary source of human exposure to dioxins is through the food supply. The pathway relating atmospheric depositions to concentrations in food is quite complex, and accordingly, it is not known to what extent the trend in human exposure mirrors the trend in atmospheric depositions. This paper describes an attempt to statistically reconstruct the pattern of past human exposure to the most toxic dioxin congener, 2,3,7,8-TCDD (abbreviated TCDD), through use of a simple pharmacokinetic (PK) model which included a time-varying TCDD exposure dose. This PK model was fit to TCDD body burden data (i.e., TCDD concentrations in lipid) from five U.S. studies dating from 1972 to 1987 and covering a wide age range. A Bayesian statistical approach was used to fit TCDD exposure; model parameters other than exposure were all previously known or estimated from other data sources. The primary results of the analysis are as follows: 1.) use of a time-varying exposure dose provided a far better fit to the TCDD body burden data than did using a dose that was constant over time; this is strong evidence that exposure to TCDD has, in fact, varied during the

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

The role of perceived air pollution and health risk perception in health symptoms and disease: a population-based study combined with modelled levels of PM10.

PubMed

Orru, Kati; Nordin, Steven; Harzia, Hedi; Orru, Hans

2018-07-01

Adverse health impact of air pollution on health may not only be associated with the level of exposure, but rather mediated by perception of the pollution and by top-down processing (e.g. beliefs of the exposure being hazardous), especially in areas with relatively low levels of pollutants. The aim of this study was to test a model that describes interrelations between air pollution (particles < 10 [Formula: see text]m, PM 10 ), perceived pollution, health risk perception, health symptoms and diseases. A population-based questionnaire study was conducted among 1000 Estonian residents (sample was stratified by age, sex, and geographical location) about health risk perception and coping. The PM 10 levels were modelled in 1 × 1 km grids using a Eulerian air quality dispersion model. Respondents were ascribed their annual mean PM 10 exposure according to their home address. Path analysis was performed to test the validity of the model. The data refute the model proposing that exposure level significantly influences symptoms and disease. Instead, the perceived exposure influences symptoms and the effect of perceived exposure on disease is mediated by health risk perception. This relationship is more pronounced in large cities compared to smaller towns or rural areas. Perceived pollution and health risk perception, in particular in large cities, play important roles in understanding and predicting environmentally induced symptoms and diseases at relatively low levels of air pollution.

Difficulties in applying numerical simulations to an evaluation of occupational hazards caused by electromagnetic fields

PubMed Central

Zradziński, Patryk

2015-01-01

Due to the various physical mechanisms of interaction between a worker's body and the electromagnetic field at various frequencies, the principles of numerical simulations have been discussed for three areas of worker exposure: to low frequency magnetic field, to low and intermediate frequency electric field and to radiofrequency electromagnetic field. This paper presents the identified difficulties in applying numerical simulations to evaluate physical estimators of direct and indirect effects of exposure to electromagnetic fields at various frequencies. Exposure of workers operating a plastic sealer have been taken as an example scenario of electromagnetic field exposure at the workplace for discussion of those difficulties in applying numerical simulations. The following difficulties in reliable numerical simulations of workers’ exposure to the electromagnetic field have been considered: workers’ body models (posture, dimensions, shape and grounding conditions), working environment models (objects most influencing electromagnetic field distribution) and an analysis of parameters for which exposure limitations are specified in international guidelines and standards. PMID:26323781

A new surrogate modeling technique combining Kriging and polynomial chaos expansions – Application to uncertainty analysis in computational dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kersaudy, Pierric, E-mail: pierric.kersaudy@orange.com; Whist Lab, 38 avenue du Général Leclerc, 92130 Issy-les-Moulineaux; ESYCOM, Université Paris-Est Marne-la-Vallée, 5 boulevard Descartes, 77700 Marne-la-Vallée

2015-04-01

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input parameters on the SAR cannot be analyzed using crude Monte Carlo simulation. The solution presented here to perform such an analysis is surrogate modeling. This paper proposes a novel approach to build such a surrogate model from a design of experiments. Considering a sparse representationmore » of the polynomial chaos expansions using least-angle regression as a selection algorithm to retain the most influential polynomials, this paper proposes to use the selected polynomials as regression functions for the universal Kriging model. The leave-one-out cross validation is used to select the optimal number of polynomials in the deterministic part of the Kriging model. The proposed approach, called LARS-Kriging-PC modeling, is applied to three benchmark examples and then to a full-scale metamodeling problem involving the exposure of a numerical fetus model to a femtocell device. The performances of the LARS-Kriging-PC are compared to an ordinary Kriging model and to a classical sparse polynomial chaos expansion. The LARS-Kriging-PC appears to have better performances than the two other approaches. A significant accuracy improvement is observed compared to the ordinary Kriging or to the sparse polynomial chaos depending on the studied case. This approach seems to be an optimal solution between the two other classical approaches. A global sensitivity analysis is finally performed on the LARS-Kriging-PC model of the fetus exposure problem.« less

Systems Toxicology: From Basic Research to Risk Assessment

PubMed Central

2014-01-01

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment. PMID:24446777

Systems toxicology: from basic research to risk assessment.

PubMed

Sturla, Shana J; Boobis, Alan R; FitzGerald, Rex E; Hoeng, Julia; Kavlock, Robert J; Schirmer, Kristin; Whelan, Maurice; Wilks, Martin F; Peitsch, Manuel C

2014-03-17

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Alcohol, sex, and screens: Modeling media influence on adolescent alcohol and sex co-occurrence

PubMed Central

Bleakley, Amy; Ellithorpe, Morgan E.; Hennessy, Michael; Khurana, Atika; Jamieson, Patrick; Weitz, Ilana

2017-01-01

Alcohol use and sexual behavior are important risk behaviors in adolescent development, and combining the two is common. The reasoned action approach is used to predict adolescents’ intention to combine alcohol use and sexual behavior based on exposure to alcohol and sex combinations in popular entertainment media. We conducted a content analysis of mainstream (n=29) and Black-oriented movies (n= 34) from 2014 and 2013–2014, respectively, and 56 television shows (2014–15 season). Content analysis ratings featuring character portrayals of both alcohol and sex within the same 5-minute segment were used to create exposure measures that were linked to online survey data collected from 1,990 14–17 year-old adolescents (50.3% Black, 49.7% White, 48.1% female). Structural equation modeling and group analysis by race were used to test whether attitudes, norms, and perceived behavioral control mediated the effects of media exposure on intention to combine alcohol and sex. Results suggest that for both White and Black adolescents, exposure to media portrayals of alcohol and sex combinations is positively associated with adolescents’ attitudes and norms. These relationships were stronger among White adolescents. Intention was predicted by attitude, norms, and control, but only the attitude-intention relationship was different by race group (stronger for Whites). PMID:28276932

The Diesel Exhaust in Miners Study: V. Evaluation of the Exposure Assessment Methods

PubMed Central

Stewart, Patricia A.; Vermeulen, Roel; Coble, Joseph B.; Blair, Aaron; Schleiff, Patricia; Lubin, Jay H.; Attfield, Mike; Silverman, Debra T.

2012-01-01

Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947–1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998–2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976–1977, derived from models developed to predict estimated historical exposures, were compared to 1976–1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 μg m−3 as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976–1977 CO measurement means and the 1976–1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses. PMID:22383674

Assessing and reporting uncertainties in dietary exposure analysis - Part II: Application of the uncertainty template to a practical example of exposure assessment.

PubMed

Tennant, David; Bánáti, Diána; Kennedy, Marc; König, Jürgen; O'Mahony, Cian; Kettler, Susanne

2017-11-01

A previous publication described methods for assessing and reporting uncertainty in dietary exposure assessments. This follow-up publication uses a case study to develop proposals for representing and communicating uncertainty to risk managers. The food ingredient aspartame is used as the case study in a simple deterministic model (the EFSA FAIM template) and with more sophisticated probabilistic exposure assessment software (FACET). Parameter and model uncertainties are identified for each modelling approach and tabulated. The relative importance of each source of uncertainty is then evaluated using a semi-quantitative scale and the results expressed using two different forms of graphical summary. The value of this approach in expressing uncertainties in a manner that is relevant to the exposure assessment and useful to risk managers is then discussed. It was observed that the majority of uncertainties are often associated with data sources rather than the model itself. However, differences in modelling methods can have the greatest impact on uncertainties overall, particularly when the underlying data are the same. It was concluded that improved methods for communicating uncertainties for risk management is the research area where the greatest amount of effort is suggested to be placed in future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A cross-fostering analysis of bromine ion concentration in rats that inhaled 1-bromopropane vapor.

PubMed

Ishidao, Toru; Fueta, Yukiko; Ueno, Susumu; Yoshida, Yasuhiro; Hori, Hajime

2016-06-16

Inhaled 1-bromopropane decomposes easily and releases bromine ion. However, the kinetics and transfer of bromine ion into the next generation have not been clarified. In this work, the kinetics of bromine ion transfer to the next generation was investigated by using cross-fostering analysis and a one-compartment model. Pregnant Wistar rats were exposed to 700 ppm of 1-bromopropane vapor for 6 h per day during gestation days (GDs) 1-20. After birth, cross-fostering was performed between mother exposure groups and mother control groups, and the pups were subdivided into the following four groups: exposure group, postnatal exposure group, gestation exposure group, and control group. Bromine ion concentrations in the brain were measured temporally. Bromine ion concentrations in mother rats were lower than those in virgin rats, and the concentrations in fetuses were higher than those in mothers on GD20. In the postnatal period, the concentrations in the gestation exposure group decreased with time, and the biological half-life was 3.1 days. Conversely, bromine ion concentration in the postnatal exposure group increased until postnatal day 4 and then decreased. This tendency was also observed in the exposure group. A one-compartment model was applied to analyze the behavior of bromine ion concentration in the brain. By taking into account the increase of body weight and change in the bromine ion uptake rate in pups, the bromine ion concentrations in the brains of the rats could be estimated with acceptable precision.

Indoor-to-outdoor particle concentration ratio model for human exposure analysis

NASA Astrophysics Data System (ADS)

Lee, Jae Young; Ryu, Sung Hee; Lee, Gwangjae; Bae, Gwi-Nam

2016-02-01

This study presents an indoor-to-outdoor particle concentration ratio (IOR) model for improved estimates of indoor exposure levels. This model is useful in epidemiological studies with large population, because sampling indoor pollutants in all participants' house is often necessary but impractical. As a part of a study examining the association between air pollutants and atopic dermatitis in children, 16 parents agreed to measure the indoor and outdoor PM10 and PM2.5 concentrations at their homes for 48 h. Correlation analysis and multi-step multivariate linear regression analysis was performed to develop the IOR model. Temperature and floor level were found to be powerful predictors of the IOR. Despite the simplicity of the model, it demonstrated high accuracy in terms of the root mean square error (RMSE). Especially for long-term IOR estimations, the RMSE was as low as 0.064 and 0.063 for PM10 and PM2.5, respectively. When using a prediction model in an epidemiological study, understanding the consequence of the modeling error and justifying the use of the model is very important. In the last section, this paper discussed the impact of the modeling error and developed a novel methodology to justify the use of the model.

The role of models in estimating consequences as part of the risk assessment process.

PubMed

Forde-Folle, K; Mitchell, D; Zepeda, C

2011-08-01

The degree of disease risk represented by the introduction, spread, or establishment of one or several diseases through the importation of animals and animal products is assessed by importing countries through an analysis of risk. The components of a risk analysis include hazard identification, risk assessment, risk management, and risk communication. A risk assessment starts with identification of the hazard(s) and then continues with four interrelated steps: release assessment, exposure assessment, consequence assessment, and risk estimation. Risk assessments may be either qualitative or quantitative. This paper describes how, through the integration of epidemiological and economic models, the potential adverse biological and economic consequences of exposure can be quantified.

Transplacental exposure to environmental carcinogens: Association with childhood cancer risks and the role of modulating factors.

PubMed

Fucic, A; Guszak, V; Mantovani, A

2017-09-01

Biological responses to carcinogens from environmental exposure during adulthood are modulated over years or decades. Conversely, during transplacental exposure, the effects on the human foetus change within weeks, intertwining with developmental mechanisms: even short periods of transplacental exposure may be imprinted in the organism for a lifetime. The pathways leading to childhood and juvenile cancers, such as leukaemias, neuroblastoma/brain tumours, hepatoblastoma, and Willm's tumour involve prenatally-induced genomic, epigenomic and/or non-genomic effects caused by xenobiotics. Pregnant women most often live in complex environmental settings that cause transplacental exposure of the foetus to xenobiotic mixtures. Mother-child biomonitoring should integrate the analysis of chemicals/radiation present in the living and workplace environment with relevant risk modulators related to life style. The interdisciplinary approach for transplacental cancer risk assessment in high-pressure areas should be based on an integrated model for mother-child exposure estimation via profiling the exposure level by water quality analysis, usage of emission grids, and land use maps. Copyright © 2017. Published by Elsevier Inc.

76 FR 50898 - Metconazole; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-17

.../oppefed1/models/water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System... affected. The North American Industrial Classification System (NAICS) codes have been provided to assist... supporting the petition, EPA has modified the levels at which tolerances are being established for the...

Human health risk assessment: models for predicting the effective exposure duration of on-site receptors exposed to contaminated groundwater.

PubMed

Baciocchi, Renato; Berardi, Simona; Verginelli, Iason

2010-09-15

Clean-up of contaminated sites is usually based on a risk-based approach for the definition of the remediation goals, which relies on the well known ASTM-RBCA standard procedure. In this procedure, migration of contaminants is described through simple analytical models and the source contaminants' concentration is supposed to be constant throughout the entire exposure period, i.e. 25-30 years. The latter assumption may often result over-protective of human health, leading to unrealistically low remediation goals. The aim of this work is to propose an alternative model taking in account the source depletion, while keeping the original simplicity and analytical form of the ASTM-RBCA approach. The results obtained by the application of this model are compared with those provided by the traditional ASTM-RBCA approach, by a model based on the source depletion algorithm of the RBCA ToolKit software and by a numerical model, allowing to assess its feasibility for inclusion in risk analysis procedures. The results discussed in this work are limited to on-site exposure to contaminated water by ingestion, but the approach proposed can be extended to other exposure pathways. Copyright 2010 Elsevier B.V. All rights reserved.

Pet exposure and risk of atopic dermatitis at the pediatric age: a meta-analysis of birth cohort studies.

PubMed

Pelucchi, Claudio; Galeone, Carlotta; Bach, Jean-François; La Vecchia, Carlo; Chatenoud, Liliane

2013-09-01

Findings on pet exposure and the risk of atopic dermatitis (AD) in children are inconsistent. With the aim to summarize the results of exposure to different pets on AD, we undertook a meta-analysis of epidemiologic studies on this issue. In August 2012, we conducted a systematic literature search in Medline and Embase. We included analytic studies considering exposure to dogs, cats, other pets, or pets overall during pregnancy, infancy, and/or childhood, with AD assessment performed during infancy or childhood. We calculated summary relative risks and 95% CIs using both fixed- and random-effects models. We computed summary estimates across selected subgroups. Twenty-six publications from 21 birth cohort studies were used in the meta-analyses. The pooled relative risks of AD for exposure versus no exposure were 0.72 (95% CI, 0.61-0.85; I(2) = 46%; results based on 15 studies) for exposure to dogs, 0.94 (95% CI, 0.76-1.16; I(2) = 54%; results based on 13 studies) for exposure to cats, and 0.75 (95% CI, 0.67-0.85; I(2) = 54%; results based on 11 studies) for exposure to pets overall. No heterogeneity emerged across the subgroups examined, except for geographic area. This meta-analysis reported a favorable effect of exposure to dogs and pets on the risk of AD in infants or children, whereas no association emerged with exposure to cats. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Relationship between Telomere Length, Genetic Traits and Environmental/Occupational Exposures in Bladder Cancer Risk by Structural Equation Modelling.

PubMed

Pavanello, Sofia; Carta, Angela; Mastrangelo, Giuseppe; Campisi, Manuela; Arici, Cecilia; Porru, Stefano

2017-12-21

Background : Telomere length (TL) maintenance plays an important role in bladder cancer (BC) and prognosis. However the manifold influence of everyday life exposures and genetic traits on leucocyte TL (LTL), is not fully elucidated. Methods : Within the framework of a hospital-based case ( n = 96)/control ( n = 94) study (all Caucasian males), we investigated the extent to which LTL and BC risk were modulated by genetic polymorphisms and environmental and occupational exposures. Data on lifetime smoking, alcohol and coffee drinking, dietary habits and occupational exposures, pointing to aromatic amines (AAs) and polycyclic aromatic hydrocarbons (PAHs) were collected. Structural equation modelling (SEM) analysis appraised this complex relationships. Results : The SEM analysis indicates negative direct links ( p < 0.05) between LTL with age, DNA adducts, alcohol and NAT2, and positive ones with coffee, MPO and XRCC3; and between BC risk ( p < 0.01) with cigarettes, cumulative exposure to AAs and coffee, while are negative with LTL and age. There was evidence of indirect effects ( p < 0.05) on BC risk, probably via LTL reduction, by age and NAT2 (positive link), MPO and XRCC3 (negative link). Our study supports evidence that LTL attrition is a critical event in BC. The new finding that LTL erosion depends on some preventable everyday life exposures genetically modulated, opens new perspectives in BC prevention.

Relationship between Telomere Length, Genetic Traits and Environmental/Occupational Exposures in Bladder Cancer Risk by Structural Equation Modelling

PubMed Central

Pavanello, Sofia; Carta, Angela; Mastrangelo, Giuseppe; Campisi, Manuela; Porru, Stefano

2017-01-01

Background: Telomere length (TL) maintenance plays an important role in bladder cancer (BC) and prognosis. However the manifold influence of everyday life exposures and genetic traits on leucocyte TL (LTL), is not fully elucidated. Methods: Within the framework of a hospital-based case (n = 96)/control (n = 94) study (all Caucasian males), we investigated the extent to which LTL and BC risk were modulated by genetic polymorphisms and environmental and occupational exposures. Data on lifetime smoking, alcohol and coffee drinking, dietary habits and occupational exposures, pointing to aromatic amines (AAs) and polycyclic aromatic hydrocarbons (PAHs) were collected. Structural equation modelling (SEM) analysis appraised this complex relationships. Results: The SEM analysis indicates negative direct links (p < 0.05) between LTL with age, DNA adducts, alcohol and NAT2, and positive ones with coffee, MPO and XRCC3; and between BC risk (p < 0.01) with cigarettes, cumulative exposure to AAs and coffee, while are negative with LTL and age. There was evidence of indirect effects (p < 0.05) on BC risk, probably via LTL reduction, by age and NAT2 (positive link), MPO and XRCC3 (negative link). Conclusions: Our study supports evidence that LTL attrition is a critical event in BC. The new finding that LTL erosion depends on some preventable everyday life exposures genetically modulated, opens new perspectives in BC prevention. PMID:29267235

Bioavailability of organic solvents in soils: Input into biologically based dose-response models for human risk assessments. 1998 annual progress report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wester, R.C.; Maibach, H.I.

1998-06-01

'The purpose of this study is to determine the bioavailability of organic solvents following dermal exposures to contaminated soil and water. Breath analysis is being used to obtain real-time measurements of volatile organics in expired air following exposure in rats and humans. Rhesus monkeys will be used as surrogates for humans in benzene exposures. The exhaled breath data is being analyzed using physiologically based pharmacokinetic (PBPK) models to determine the dermal bioavailability of organic solvents under realistic exposure conditions. The end product of this research will be a tested framework for the rapid screening of real and potential exposures whilemore » simultaneously developing physiologically based pharmacokinetic (PBPK) models to comprehensively evaluate and compare exposures to organics from either contaminated soil or water. This report summarizes work 7 months into a 3-year project. Method development has produced systems for solvent exposure from soil and water which mimic actual exposure, and for which animals and human volunteers can be safely tested. Soil exposure is generally open to the air (working the soil) while water exposure is generally immersion. For 6--8 hour test exposure, a patch has been developed where soil is contained against the skin by a non-occlusive membrane, while simultaneously allowing volatilization of test solvent to the environment (activated charcoal). The water counterpart is an occlusive glass culture dish, sealed to skin with silicone adhesive. Shorter term exposure is done by one hand immersion in a bucket containing circulating water or soil, the volunteer instructed to move fingers through the water or soil. Human volunteers and animals breathe fresh air via a new breath-inlet system that allows for continuous real-time analysis of undiluted exhaled air. The air supply system is self-contained and separated from the exposure solvent-laden environment. The system uses a Teledyne 3DQ Discovery ion trap mass spectrometer (MS/MS) equipped with an atmospheric sampling glow discharge ionization source (ASGDI). The MS/MS system provides an appraisal of individual chemical components in the breath stream in the single-digit parts-per-billion (ppb) detectable range for each of the compounds proposed for study, while maintaining linearity of response over a wide dynamic range.'« less

Meta-analysis of residential exposure to radon gas and lung cancer.

PubMed Central

Pavia, Maria; Bianco, Aida; Pileggi, Claudia; Angelillo, Italo F.

2003-01-01

OBJECTIVES: To investigate the relation between residential exposure to radon and lung cancer. METHODS: A literature search was performed using Medline and other sources. The quality of studies was assessed. Adjusted odds ratios with 95% confidence intervals (CI) for the risk of lung cancer among categories of levels of exposure to radon were extracted. For each study, a weighted log-linear regression analysis of the adjusted odds ratios was performed according to radon concentration. The random effect model was used to combine values from single studies. Separate meta-analyses were performed on results from studies grouped with similar characteristics or with quality scores above or equal to the median. FINDINGS: Seventeen case-control studies were included in the meta-analysis. Quality scoring for individual studies ranged from 0.45 to 0.77 (median, 0.64). Meta-analysis based on exposure at 150 Bq/m3 gave a pooled odds ratio estimate of 1.24 (95% CI, 1.11-1.38), which indicated a potential effect of residential exposure to radon on the risk of lung cancer. Pooled estimates of fitted odds ratios at several levels of randon exposure were all significantly different from unity--ranging from 1.07 at 50 Bq/m3 to 1.43 at 250 Bq/m3. No remarkable differences from the baseline analysis were found for odds ratios from sensitivity analyses of studies in which > 75% of eligible cases were recruited (1.12, 1.00-1.25) and studies that included only women (1.29, 1.04-1.60). CONCLUSION: Although no definitive conclusions may be drawn, our results suggest a dose-response relation between residential exposure to radon and the risk of lung cancer. They support the need to develop strategies to reduce human exposure to radon. PMID:14758433

Emerging Tools to Estimate and to Predict Exposures to ...

EPA Pesticide Factsheets

The timely assessment of the human and ecological risk posed by thousands of existing and emerging commercial chemicals is a critical challenge facing EPA in its mission to protect public health and the environment The US EPA has been conducting research to enhance methods used to estimate and forecast exposures for tens of thousands of chemicals. This research is aimed at both assessing risks and supporting life cycle analysis, by developing new models and tools for high throughput exposure screening and prioritization, as well as databases that support these and other tools, especially regarding consumer products. The models and data address usage, and take advantage of quantitative structural activity relationships (QSARs) for both inherent chemical properties and function (why the chemical is a product ingredient). To make them more useful and widely available, the new tools, data and models are designed to be: • Flexible • Intraoperative • Modular (useful to more than one, stand-alone application) • Open (publicly available software) Presented at the Society for Risk Analysis Forum: Risk Governance for Key Enabling Technologies, Venice, Italy, March 1-3, 2017

TRIAGE DOSE ASSESSMENT FOR PARTIAL-BODY EXPOSURE: DICENTRIC ANALYSIS

PubMed Central

Moroni, Maria; Pellmar, Terry C.

2009-01-01

Partial-body biodosimetry is likely to be required after a radiological or nuclear exposure. Clinical signs and symptoms, distribution of dicentrics in circulating blood cells, organ-specific biomarkers, physical signals in teeth and nails all can provide indications of non-homogeneous exposures. Organ specific biomarkers may provide early warning regarding physiological systems at risk after radiation injury. Use of a combination of markers and symptoms will be needed for clinical insights for therapeutic approaches. Analysis of dicentrics, a marker specific for radiation injury, is the “Gold standard” of biodosimetry and can reveal partial-body exposures. Automation of sample processing for dicentric analysis can increase throughput with customization of off-the-shelf technologies for cytogenetic sample processing and information management. Automated analysis of the metaphase spreads is currently limited but improvements are in development. Our efforts bridge the technological gaps to allow the use of dicentric chromosome assay (DCA) for risk-based stratification of mass casualties. This article summarizes current knowledge on partial-body cytogenetic dose assessment synthesizing information leading to the proposal of an approach to triage dose prediction in radiation mass casualties, based on equivalent whole-body doses under partial-body exposure conditions and assesses the validity of using this model. An initial screening using only 20 metaphase spreads per subject can confirm irradiation above 2-Gy. A subsequent increase to 50 metaphases improves dose determination to allow risk stratification for clinical triage. Metaphases evaluated for inhomogeneous distribution of dicentrics can reveal partial-body exposures. We tested the validity of this approach in an in vitro model that simulates partial-body irradiation by mixing irradiated and un-irradiated lymphocytes in various proportions. Our preliminary results support the notion that this approach will be effective under a range of conditions including some partial-body exposures, but may have limitations with low doses or small proportions of irradiated body. Our studies address an important problem in the diagnosis of partial-body irradiation and dose assessment in mass casualties and propose a solution. However, additional work is needed to fully develop and validate the application of DCA to partial-body exposures. PMID:20065689

Modelling of aircrew radiation exposure during solar particle events

NASA Astrophysics Data System (ADS)

Al Anid, Hani Khaled

In 1990, the International Commission on Radiological Protection recognized the occupational exposure of aircrew to cosmic radiation. In Canada, a Commercial and Business Aviation Advisory Circular was issued by Transport Canada suggesting that action should be taken to manage such exposure. In anticipation of possible regulations on exposure of Canadian-based aircrew in the near future, an extensive study was carried out at the Royal Military College of Canada to measure the radiation exposure during commercial flights. The radiation exposure to aircrew is a result of a complex mixed-radiation field resulting from Galactic Cosmic Rays (GCRs) and Solar Energetic Particles (SEPs). Supernova explosions and active galactic nuclei are responsible for GCRs which consist of 90% protons, 9% alpha particles, and 1% heavy nuclei. While they have a fairly constant fluence rate, their interaction with the magnetic field of the Earth varies throughout the solar cycles, which has a period of approximately 11 years. SEPs are highly sporadic events that are associated with solar flares and coronal mass ejections. This type of exposure may be of concern to certain aircrew members, such as pregnant flight crew, for which the annual effective dose is limited to 1 mSv over the remainder of the pregnancy. The composition of SEPs is very similar to GCRs, in that they consist of mostly protons, some alpha particles and a few heavy nuclei, but with a softer energy spectrum. An additional factor when analysing SEPs is the effect of flare anisotropy. This refers to the way charged particles are transported through the Earth's magnetosphere in an anisotropic fashion. Solar flares that are fairly isotropic produce a uniform radiation exposure for areas that have similar geomagnetic shielding, while highly anisotropic events produce variable exposures at different locations on the Earth. Studies of neutron monitor count rates from detectors sharing similar geomagnetic shielding properties show a very different response during anisotropic events, leading to variations in aircrew radiation doses that may be significant for dose assessment. To estimate the additional exposure due to solar flares, a model was developed using a Monte-Carlo radiation transport code, MCNPX. The model transports an extrapolated particle spectrum based on satellite measurements through the atmosphere using the MCNPX analysis. This code produces the estimated flux at a specific altitude where radiation dose conversion coefficients are applied to convert the particle flux into effective and ambient dose-equivalent rates. A cut-off rigidity model accounts for the shielding effects of the Earth's magnetic field. Comparisons were made between the model predictions and actual flight measurements taken with various types of instruments used to measure the mixed radiation field during Ground Level Enhancements 60 and 65. An anisotropy analysis that uses neutron monitor responses and the pitch angle distribution of energetic solar particles was used to identify particle anisotropy for a solar event in December 2006. In anticipation of future commercial use, a computer code has been developed to implement the radiation dose assessment model for routine analysis. Keywords: Radiation Dosimetry, Radiation Protection, Space Physics.

Comparative and Predictive Multimedia Assessments Using Monte Carlo Uncertainty Analyses

NASA Astrophysics Data System (ADS)

Whelan, G.

2002-05-01

Multiple-pathway frameworks (sometimes referred to as multimedia models) provide a platform for combining medium-specific environmental models and databases, such that they can be utilized in a more holistic assessment of contaminant fate and transport in the environment. These frameworks provide a relatively seamless transfer of information from one model to the next and from databases to models. Within these frameworks, multiple models are linked, resulting in models that consume information from upstream models and produce information to be consumed by downstream models. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) is an example, which allows users to link their models to other models and databases. FRAMES is an icon-driven, site-layout platform that is an open-architecture, object-oriented system that interacts with environmental databases; helps the user construct a Conceptual Site Model that is real-world based; allows the user to choose the most appropriate models to solve simulation requirements; solves the standard risk paradigm of release transport and fate; and exposure/risk assessments to people and ecology; and presents graphical packages for analyzing results. FRAMES is specifically designed allow users to link their own models into a system, which contains models developed by others. This paper will present the use of FRAMES to evaluate potential human health exposures using real site data and realistic assumptions from sources, through the vadose and saturated zones, to exposure and risk assessment at three real-world sites, using the Multimedia Environmental Pollutant Assessment System (MEPAS), which is a multimedia model contained within FRAMES. These real-world examples use predictive and comparative approaches coupled with a Monte Carlo analysis. A predictive analysis is where models are calibrated to monitored site data, prior to the assessment, and a comparative analysis is where models are not calibrated but based solely on literature or judgement and is usually used to compare alternatives. In many cases, a combination is employed where the model is calibrated to a portion of the data (e.g., to determine hydrodynamics), then used to compare alternatives. Three subsurface-based multimedia examples are presented, increasing in complexity. The first presents the application of a predictive, deterministic assessment; the second presents a predictive and comparative, Monte Carlo analysis; and the third presents a comparative, multi-dimensional Monte Carlo analysis. Endpoints are typically presented in terms of concentration, hazard, risk, and dose, and because the vadose zone model typically represents a connection between a source and the aquifer, it does not generally represent the final medium in a multimedia risk assessment.

PATIENT-SPECIFIC FINITE ELEMENT ANALYSIS OF CHRONIC CONTACT STRESS EXPOSURE AFTER INTRA-ARTICULAR FRACTURE OF THE TIBIAL PLAFOND

PubMed Central

Li, Wendy; Anderson, Donald D.; Goldsworthy, Jane K.; Marsh, J. Lawrence; Brown, Thomas D.

2008-01-01

SUMMARY The role of altered contact mechanics in the pathogenesis of post-traumatic osteoarthritis (PTOA) following intra-articular fracture remains poorly understood. One proposed etiology is that residual incongruities lead to altered joint contact stresses that, over time, predispose to PTOA. Prevailing joint contact stresses following surgical fracture reduction were quantified in this study using patient-specific contact finite element (FE) analysis. FE models were created for 11 ankle pairs from tibial plafond fracture patients. Both (reduced) fractured ankles and their intact contralaterals were modeled. A sequence of 13 loading instances was used to simulate the stance phase of gait. Contact stresses were summed across loadings in the simulation, weighted by resident time in the gait cycle. This chronic exposure measure, a metric of degeneration propensity, was then compared between intact and fractured ankle pairs. Intact ankles had lower peak contact stress exposures that were more uniform, and centrally located. The series-average peak contact stress elevation for fractured ankles was 38% (p=0.0015; peak elevation was 82%). Fractured ankles had less area with low contact stress exposure than intacts, and a greater area with high exposure. Chronic contact stress overexposures (stresses exceeding a damage threshold) ranged from near zero to a high of 18 times the matched intact value. The patient-specific FE models utilized in this study represent substantial progress towards elucidating the relationship between altered contact stresses and the outcome of patients treated for intra-articular fractures. PMID:18404662

Health effects of inhaled gasoline engine emissions.

PubMed

McDonald, Jacob D; Reed, Matthew D; Campen, Matthew J; Barrett, Edward G; Seagrave, JeanClare; Mauderly, Joe L

2007-01-01

Despite their prevalence in the environment, and the myriad studies that have shown associations between morbidity or mortality with proximity to roadways (proxy for motor vehicle exposures), relatively little is known about the toxicity of gasoline engine emissions (GEE). We review the studies conducted on GEE to date, and summarize the findings from each of these studies. While there have been several studies, most of the studies were conducted prior to 1980 and thus were not conducted with contemporary engines, fuels, and driving cycles. In addition, many of the biological assays conducted during those studies did not include many of the assays that are conducted on contemporary inhalation exposures to air pollutants, including cardiovascular responses and others. None of the exposures from these earlier studies were characterized at the level of detail that would be considered adequate today. A recent GEE study was conducted as part of the National Environmental Respiratory Center (www.nercenter.org). In this study several in-use mid-mileage General Motors (Chevrolet S-10) vehicles were purchased and utilized for inhalation exposures. An exposure protocol was developed where engines were operated with a repeating California Unified Driving Cycle with one cold start per day. Two separate engines were used to provide two cold starts over a 6-h inhalation period. The exposure atmospheres were characterized in detail, including detailed chemical and physical analysis of the gas, vapor, and particle phase. Multiple rodent biological models were studied, including general toxicity and inflammation (e.g., serum chemistry, lung lavage cell counts/differentials, cytokine/chemokine analysis, histopathology), asthma (adult and in utero exposures with pulmonary function and biochemical analysis), cardiovascular effects (biochemical and electrocardiograph changes in susceptible rodent models), and susceptibility to infection (Pseudomonas bacteria challenge). GEE resulted in significant biological effects for upregulation of MIP-2, clearance of Pseudomonas bacteria, development of allergic response after in utero exposure, and cardiovascular indicators of vasoconstriction, oxidant stress, and damage.

Evaluation of regional and local atmospheric dispersion models for the analysis of traffic-related air pollution in urban areas

NASA Astrophysics Data System (ADS)

Fallah-Shorshani, Masoud; Shekarrizfard, Maryam; Hatzopoulou, Marianne

2017-10-01

Dispersion of road transport emissions in urban metropolitan areas is typically simulated using Gaussian models that ignore the turbulence and drag induced by buildings, which are especially relevant for areas with dense downtown cores. To consider the effect of buildings, street canyon models are used but often at the level of single urban corridors and small road networks. In this paper, we compare and validate two dispersion models with widely varying algorithms, across a modelling domain consisting of the City of Montreal, Canada accounting for emissions of more 40,000 roads. The first dispersion model is based on flow decomposition into the urban canopy sub-flow as well as overlying airflow. It takes into account the specific height and geometry of buildings along each road. The second model is a Gaussian puff dispersion model, which handles complex terrain and incorporates three-dimensional meteorology, but accounts for buildings only through variations in the initial vertical mixing coefficient. Validation against surface observations indicated that both models under-predicted measured concentrations. Average weekly exposure surfaces derived from both models were found to be reasonably correlated (r = 0.8) although the Gaussian dispersion model tended to underestimate concentrations around the roadways compared to the street canyon model. In addition, both models were used to estimate exposures of a representative sample of the Montreal population composed of 1319 individuals. Large differences were noted whereby exposures derived from the Gaussian puff model were significantly lower than exposures derived from the street canyon model, an expected result considering the concentration of population around roadways. These differences have large implications for the analyses of health effects associated with NO2 exposure.

Biomarker analysis of hemoglobin adducts of acrylamide and glycidamide enantiomers for mid-term internal exposure assessment by isotope dilution ultra-high performance liquid chromatography tandem mass spectrometry.

PubMed

Zhang, Yu; Wang, Qiao; Zhang, Gong; Jia, Wei; Ren, Yiping; Wu, Yongning

2018-02-01

Hemoglobin (Hb) adducts of acrylamide (AA) and its oxidative metabolite glycidamide (GA) are important biomarkers for evaluating the mid-term exposure of acrylamide toxicity in vivo. Taking pentafluoro-2-methylphenyl isothiocyanates of N-(2-carbamoylethyl)valine (AAVal-PFPTH) and N-(2-carbamoyl-2-hydroxyethy)valine (GAVal-PFPTH) as target analytes, we developed an isotope dilution ultra-high performance liquid chromatograph tandem mass spectrometry (UHPLC-MS/MS) method for the simultaneous determination of AA and GA hemoglobin (Hb) adducts under the electroscopy ionization negative (ESI‾) mode in the present work. Among them, the enantiomer pair of GA-Hb adducts was firstly identified and successfully separated at baseline level. The method achieved high sensitivity with the LOD and LOQ ranging 1.43-5.05pmol/g Hb and 4.78-16.82pmol/g Hb, respectively. The recovery rates with low, intermediate and high spiking levels were calculated as 97.0-105.2%, 97.4-106.4% and 100.3-111.2%, respectively. Acceptable within-laboratory reproducibility (RSD < 13.7%) substantially supported the robustness of current UHPLC-MS/MS method, which was successfully applied to measure the hemoglobin adducts of acrylamide and glycidamide enantiomers in blood of both rats and humans. A linear exposure assessment model was developed for estimating the daily exposure to acrylamide in humans via considering acrylamide hemoglobin adducts as variables, indicating a novel connect between biomarker-based internal exposure and dietary-based external exposure. Overall, the present instrumental analysis and related internal exposure assessment model provide a substantially methodological support for profiling the internal biological exposure and estimating the external dietary exposure to acrylamide. Copyright © 2017 Elsevier B.V. All rights reserved.

Incorporation of additional radionuclides and the external exposure pathway into the BECAMP (Basic Environmental Compliance and Monitoring Program) radiological assessment model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, Yook C.; Rodean, H.C.; Anspaugh, L.R.

The Nevada Applied Ecology Group (NAEG) Model of transport and dose for transuranic radionuclides was modified and expanded for the analysis of radionuclides other than pure alpha-emitters. Doses from internal and external exposures were estimated for the inventories and soil distributions of the individual radionuclides quantified in Areas 2 and 4 of the Nevada Test Site (NTS). We found that the dose equivalents via inhalation to liver, lungs, bone marrow, and bone surface from the plutonium isotopes and /sup 241/Am, those via ingestion to bone marrow and bone surfaces from /sup 90/Sr, and those via ingestion to all the targetmore » organs from /sup 137/Cs were the highest from internal exposures. The effective dose equivalents from /sup 137/Cs, /sup 152/Eu, and /sup 154/Eu were the highest from the external exposures. The /sup 60/Co, /sup 152/Eu, /sup 154/Eu, and /sup 155/Eu dose estimates for external exposures greatly exceeded those for internal exposures. The /sup 60/Co, /sup 90/Sr, and /sup 137/Cs dose equivalents from internal exposures were underestimated due to the adoption of some of the foodchain parameter values originally selected for /sup 239/Pu. Nonetheless, the ingestion pathway contributed significantly to the dose estimates for /sup 90/Sr and /sup 137/Cs, but contributed very much less than external exposures to the dose estimates for /sup 60/Co. Therefore, the use of more appropriate values would not alter the identification of important radionuclides, pathways, target organs, and exposure modes in this analysis. 19 refs., 13 figs., 12 tabs.« less

Assessing exposure to violence in urban youth.

PubMed

Selner-O'Hagan, M B; Kindlon, D J; Buka, S L; Raudenbush, S W; Earls, F J

1998-02-01

This study reports on the development of a structured interview, My Exposure to Violence (My ETV), that was designed to assess child and youth exposure to violence. Eighty participants between the ages of 9 and 24 were assessed. Data from My ETV were fit to a Rasch model for rating scales, a technique that generates interval level measures and allows the characterization of both chronic and acute exposure. Results indicated that the fit statistics for six scales, covering both lifetime and past year victimization, witnessing of violence, and total exposure, were all good. These scales were found to have high internal consistency (r = .68 to .93) and test-retest reliability (r = .75 to .94). Evidence of construct validity was provided by the item analysis, which revealed a theoretically sensible ordering of item extremity, and also by analysis of bivariate associations. As expected, younger subjects generally reported less exposure to violence than did older subjects, males reported more exposure than did females, African-American subjects reported higher levels of exposure than did White subjects, violent offenders reported more exposure than did non-offenders, and those living in high crime areas reported more exposure than did those residing in low crime areas. Future areas of investigation and the potential contribution to studies of antisocial behavior and post-traumatic stress disorder are discussed.

The Global Food System as a Transport Pathway for Hazardous Chemicals: The Missing Link between Emissions and Exposure

PubMed Central

Ng, Carla A.; von Goetz, Natalie

2016-01-01

Background: Food is a major pathway for human exposure to hazardous chemicals. The modern food system is becoming increasingly complex and globalized, but models for food-borne exposure typically assume locally derived diets or use concentrations directly measured in foods without accounting for food origin. Such approaches may not reflect actual chemical intakes because concentrations depend on food origin, and representative analysis is seldom available. Processing, packaging, storage, and transportation also impart different chemicals to food and are not yet adequately addressed. Thus, the link between environmental emissions and realistic human exposure is effectively broken. Objectives: We discuss the need for a fully integrated treatment of the modern industrialized food system, and we propose strategies for using existing models and relevant supporting data sources to track chemicals during production, processing, packaging, storage, and transport. Discussion: Fate and bioaccumulation models describe how chemicals distribute in the environment and accumulate through local food webs. Human exposure models can use concentrations in food to determine body burdens based on individual or population characteristics. New models now include the impacts of processing and packaging but are far from comprehensive. We propose to close the gap between emissions and exposure by utilizing a wider variety of models and data sources, including global food trade data, processing, and packaging models. Conclusions: A comprehensive approach that takes into account the complexity of the modern global food system is essential to enable better prediction of human exposure to chemicals in food, sound risk assessments, and more focused risk abatement strategies. Citation: Ng CA, von Goetz N. 2017. The global food system as a transport pathway for hazardous chemicals: the missing link between emissions and exposure. Environ Health Perspect 125:1–7; http://dx.doi.org/10.1289/EHP168 PMID:27384039

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment

PubMed Central

Rice, F; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

OBJECTIVE—To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust.
METHODS—Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death.
RESULTS—Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m3 for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000).
CONCLUSIONS—There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.


Keywords: crystalline silica; cristobalite; lung cancer PMID:11119633

Does the portrayal of tanning in Australian women's magazines relate to real women's tanning beliefs and behavior?

PubMed

Dixon, Helen G; Warne, Charles D; Scully, Maree L; Wakefield, Melanie A; Dobbinson, Suzanne J

2011-04-01

Content analysis data on the tans of 4,422 female Caucasian models sampled from spring and summer magazine issues were combined with readership data to generate indices of potential exposure to social modeling of tanning via popular women's magazines over a 15-year period (1987 to 2002). Associations between these indices and cross-sectional telephone survey data from the same period on 5,675 female teenagers' and adults' tanning attitudes, beliefs, and behavior were examined using logistic regression models. Among young women, greater exposure to tanning in young women's magazines was associated with increased likelihood of endorsing pro-tan attitudes and beliefs. Among women of all ages, greater exposure to tanned models via the most popular women's magazines was associated with increased likelihood of attempting to get a tan but lower likelihood of endorsing pro-tan attitudes. Popular women's magazines may promote and reflect real women's tanning beliefs and behavior.

How Analysis Informs Regulation:Success and Failure of ...

EPA Pesticide Factsheets

How Analysis Informs Regulation:Success and Failure of Evolving Approaches to Polyfluoroalkyl Acid Contamination The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.

Media exposure and smoking intention in adolescents: a moderated mediation analysis from a cultivation perspective.

PubMed

Yang, Fang; Salmon, Charles T; Pang, Joyce S; Cheng, Wendy J Y

2015-02-01

The study tested a moderated mediation model to examine the mechanisms underlying the link between media exposure and adolescent smoking intention by utilizing a modification of cultivation theory. A total of 12,586 non-current smoker adolescents in California were included in the analysis. Results showed that media exposure was positively related to smoking intention via perceived prevalence of peer smoking when friend disapproval of cigarette use was low. This study contributes to a better understanding of the mechanisms regarding the media effects on smoking intention, but the findings should be interpreted with caution due to the small effect size. © The Author(s) 2013.

Multigenerational effects of parental prenatal exposure to famine on adult offspring cognitive function

PubMed Central

Li, Jie; Na, Lixin; Ma, Hao; Zhang, Zhe; Li, Tianjiao; Lin, Liqun; Li, Qiang; Sun, Changhao; Li, Ying

2015-01-01

The effects of prenatal nutrition on adult cognitive function have been reported for one generation. However, human evidence for multigenerational effects is lacking. We examined whether prenatal exposure to the Chinese famine of 1959–61 affects adult cognitive function in two consecutive generations. In this retrospective family cohort study, we investigated 1062 families consisting of 2124 parents and 1215 offspring. We assessed parental and offspring cognitive performance by means of a comprehensive test battery. Generalized linear regression model analysis in the parental generation showed that prenatal exposure to famine was associated with a 8.1 (95% CI 5.8 to 10.4) second increase in trail making test part A, a 7.0 (1.5 to 12.5) second increase in trail making test part B, and a 5.5 (−7.3 to −3.7) score decrease in the Stroop color-word test in adulthood, after adjustment for potential confounders. In the offspring generation, linear mixed model analysis found no significant association between parental prenatal exposure to famine and offspring cognitive function in adulthood after adjustment for potential confounders. In conclusion, prenatal exposure to severe malnutrition is negatively associated with visual- motor skill, mental flexibility, and selective attention in adulthood. However, these associations are limited to only one generation. PMID:26333696

Development of Survey Scales for Measuring Exposure and Behavioral Responses to Disruptive Intraoperative Behavior.

PubMed

Villafranca, Alexander; Hamlin, Colin; Rodebaugh, Thomas L; Robinson, Sandra; Jacobsohn, Eric

2017-09-10

Disruptive intraoperative behavior has detrimental effects to clinicians, institutions, and patients. How clinicians respond to this behavior can either exacerbate or attenuate its effects. Previous investigations of disruptive behavior have used survey scales with significant limitations. The study objective was to develop appropriate scales to measure exposure and responses to disruptive behavior. We obtained ethics approval. The scales were developed in a sequence of steps. They were pretested using expert reviews, computational linguistic analysis, and cognitive interviews. The scales were then piloted on Canadian operating room clinicians. Factor analysis was applied to half of the data set for question reduction and grouping. Item response analysis and theoretical reviews ensured that important questions were not eliminated. Internal consistency was evaluated using Cronbach α. Model fit was examined on the second half of the data set using confirmatory factor analysis. Content validity of the final scales was re-evaluated. Consistency between observed relationships and theoretical predictions was assessed. Temporal stability was evaluated on a subsample of 38 respondents. A total of 1433 and 746 clinicians completed the exposure and response scales, respectively. Content validity indices were excellent (exposure = 0.96, responses = 1.0). Internal consistency was good (exposure = 0.93, responses = 0.87). Correlations between the exposure scale and secondary measures were consistent with expectations based on theory. Temporal stability was acceptable (exposure = 0.77, responses = 0.73). We have developed scales measuring exposure and responses to disruptive behavior. They generate valid and reliable scores when surveying operating room clinicians, and they overcome the limitations of previous tools. These survey scales are freely available.

The potential use of diisononyl phthalate metabolites hair as biomarkers to assess long-term exposure demonstrated by a rat model.

PubMed

Hsu, Jen-Yi; Ho, Hsin-Hui; Liao, Pao-Chi

2015-01-01

Diisononyl phthalate (DINP) is a widely used industrial plasticizer. People come into contact with this chemical by using plastic products made with it. Human health can be adversely affected by long-term DINP exposure. However, because the body rapidly excretes DINP metabolites, the use of single-point urine analysis to assess long-term exposure may produce inconsistent results in epidemiologic studies. Hair analysis has a useful place in biomonitoring, particularly in estimating long-term or historical exposure for some chemicals. Several studies have reported using hair analysis to assess the concentrations of heavy metals, drugs and organic pollutants in humans. As a biomarker, DINP metabolites were measured in rat hair in animal experiments to evaluated long-term exposure to DINP. In addition, we evaluated the correlation between the levels of DINP metabolites in hair and in urine. The levels of DINP metabolites in rat hair were significantly higher in the exposure group, relative to the control group (p<0.05). DINP metabolites had a positive correlation with increasing administered dose. Significant positive correlations for MINP, MOINP and MHINP were found between hair and urine (r=0.86, r=0.79 and r=0.74, respectively, p<0.05). Several metabolites in urine showed earlier saturation than in hair. In this report, we detected eight metabolites in hair and demonstrate that hair analysis has potential applications in the assessment of long-term exposure to DINP. Copyright © 2014 Elsevier Ltd. All rights reserved.

ANALYSIS OF THE MOTOR NEUROTOXICITY INDUCED BY ACUTE ORAL EXPOSURE TO MULTIPLE PYRETHROID COMPOUNDS IN THE RAT USING AN ADDITIVITY MODEL.

EPA Science Inventory

Use of pyrethroids has increased in the last decade, and co-exposure to multiple pyrethroids has been reported in humans. Pyrethroids produce neurotoxicity in mammals at dosages far below those producing lethality. The Food Quality Protection Act requires the EPA to consider cumu...

Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study.

PubMed

Chang, Howard H; Warren, Joshua L; Darrow, Lnydsey A; Reich, Brian J; Waller, Lance A

2015-07-01

In reproductive epidemiology, there is a growing interest to examine associations between air pollution exposure during pregnancy and the risk of preterm birth (PTB). One important research objective is to identify critical periods of exposure and estimate the associated effects at different stages of pregnancy. However, population studies have reported inconsistent findings. This may be due to limitations from the standard analytic approach of treating PTB as a binary outcome without considering time-varying exposures together over the course of pregnancy. To address this research gap, we present a Bayesian hierarchical model for conducting a comprehensive examination of gestational air pollution exposure by estimating the joint effects of weekly exposures during different vulnerable periods. Our model also treats PTB as a time-to-event outcome to address the challenge of different exposure lengths among ongoing pregnancies. The proposed model is applied to a dataset of geocoded birth records in the Atlanta metropolitan area between 1999-2005 to examine the risk of PTB associated with gestational exposure to ambient fine particulate matter [Formula: see text]m in aerodynamic diameter (PM[Formula: see text]). We find positive associations between PM[Formula: see text] exposure during early and mid-pregnancy, and evidence that associations are stronger for PTBs occurring around week 30. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake.

PubMed

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Kimʼs, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children.

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake

PubMed Central

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

Abstract No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children. PMID:26825887

Controlling for selection effects in the relationship between child behavior problems and exposure to intimate partner violence.

PubMed

Emery, Clifton R

2011-05-01

This article used the Project on Human Development in Chicago Neighborhoods (PHDCN) data to examine the relationship between exposure to intimate partner violence (IPV) and child behavior problems (externalizing and internalizing), truancy, grade repetition, smoking, drinking, and use of marijuana. Longitudinal data analysis was conducted on 1,816 primary caregivers and their children. Fixed-effects regression models were employed to address concerns with selection bias. IPV was associated with significantly greater internalizing behavior, externalizing behavior, and truancy. Findings from age interaction models suggested that the relationship between IPV and child behavior problems may attenuate as the age of the child at time of exposure increases.

Effect of occupational exposures on lung cancer susceptibility: a study of gene-environment interaction analysis.

PubMed

Malhotra, Jyoti; Sartori, Samantha; Brennan, Paul; Zaridze, David; Szeszenia-Dabrowska, Neonila; Świątkowska, Beata; Rudnai, Peter; Lissowska, Jolanta; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Gaborieau, Valerie; Stücker, Isabelle; Foretova, Lenka; Janout, Vladimir; Boffetta, Paolo

2015-03-01

Occupational exposures are known risk factors for lung cancer. Role of genetically determined host factors in occupational exposure-related lung cancer is unclear. We used genome-wide association (GWA) data from a case-control study conducted in 6 European countries from 1998 to 2002 to identify gene-occupation interactions and related pathways for lung cancer risk. GWA analysis was performed for each exposure using logistic regression and interaction term for genotypes, and exposure was included in this model. Both SNP-based and gene-based interaction P values were calculated. Pathway analysis was performed using three complementary methods, and analyses were adjusted for multiple comparisons. We analyzed 312,605 SNPs and occupational exposure to 70 agents from 1,802 lung cancer cases and 1,725 cancer-free controls. Mean age of study participants was 60.1 ± 9.1 years and 75% were male. Largest number of significant associations (P ≤ 1 × 10(-5)) at SNP level was demonstrated for nickel, brick dust, concrete dust, and cement dust, and for brick dust and cement dust at the gene-level (P ≤ 1 × 10(-4)). Approximately 14 occupational exposures showed significant gene-occupation interactions with pathways related to response to environmental information processing via signal transduction (P < 0.001 and FDR < 0.05). Other pathways that showed significant enrichment were related to immune processes and xenobiotic metabolism. Our findings suggest that pathways related to signal transduction, immune process, and xenobiotic metabolism may be involved in occupational exposure-related lung carcinogenesis. Our study exemplifies an integrative approach using pathway-based analysis to demonstrate the role of genetic variants in occupational exposure-related lung cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 24(3); 570-9. ©2015 AACR. ©2015 American Association for Cancer Research.

Toxicological analysis of limonene reaction products using an in vitro exposure system

PubMed Central

Anderson, Stacey E.; Khurshid, Shahana S.; Meade, B. Jean; Lukomska, Ewa; Wells, J.R.

2015-01-01

Epidemiological investigations suggest a link between exposure to indoor air chemicals and adverse health effects. Consumer products contain reactive chemicals which can form secondary pollutants which may contribute to these effects. The reaction of limonene and ozone is a well characterized example of this type of indoor air chemistry. The studies described here characterize an in vitro model using an epithelial cell line (A549) or differentiated epithelial tissue (MucilAir™). The model is used to investigate adverse effects following exposure to combinations of limonene and ozone. In A549 cells, exposure to both the parent compounds and reaction products resulted in alterations in inflammatory cytokine production. A one hour exposure to limonene + ozone resulted in decreased proliferation when compared to cells exposed to limonene alone. Repeated dose exposures of limonene or limonene + ozone were conducted on MucilAir™ tissue. No change in proliferation was observed but increases in cytokine production were observed for both the parent compounds and reaction products. Factors such as exposure duration, chemical concentration, and sampling time point were identified to influence result outcome. These findings suggest that exposure to reaction products may produce more severe effects compared to the parent compound. PMID:23220291

Biomarker Exposure-Response Analysis in Mild-To-Moderate Alzheimer's Disease Trials of Bapineuzumab.

PubMed

Russu, Alberto; Samtani, Mahesh N; Xu, Steven; Adedokun, Omoniyi J; Lu, Ming; Ito, Kaori; Corrigan, Brian; Raje, Sangeeta; Liu, Enchi; Brashear, H Robert; Styren, Scot; Hu, Chuanpu

2016-05-03

Bapineuzumab, an anti-amyloid monoclonal antibody, was evaluated as a candidate for immunotherapy in mild-to-moderate Alzheimer's disease (AD) patients. To assess the treatment effect of bapineuzumab therapy on disease-relevant biomarkers in patients with mild-to-moderate AD, using exposure-response modeling. Biomarker data from two Phase III studies were combined to model the impact of bapineuzumab exposure on week-71 change from baseline in brain amyloid burden by 11C-labeled Pittsburgh compound B (PiB) PET imaging (global cortical average of the Standardized Uptake Value ratio values), cerebrospinal fluid (CSF) phosphorylated (p)-tau concentrations, and brain volumetrics (brain boundary shift integral) by magnetic resonance imaging. Bapineuzumab or placebo was administered as a 1-hour intravenous infusion every 13 weeks for 78 weeks. Pharmacokinetic/pharmacodynamic modeling helped determine the most appropriate exposure-response model and estimate the impact of disease-relevant covariates (baseline biomarker value, APOE*E4 allele copy number, and baseline disease status as measured by Mini-Mental State Examination score) on the three biomarkers. Linear exposure-response relationships with negative and significant slope terms were observed for PiB PET and CSF p-tau concentration. Baseline biomarker value and APOE*E4 carrier status were significant covariates for both biomarkers. No exposure-response relationship on brain boundary shift integral was detected. Bapineuzumab treatment induced exposure-dependent reductions in brain amyloid burden. Effects on CSF p-tau concentrations were significant only in APOE*E4 carriers. No apparent influence of bapineuzumab exposure on brain volume could be demonstrated.

The need for non- or minimally-invasive biomonitoring strategies and the development of pharmacokinetic/pharmacodynamic models for quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timchalk, Charles; Weber, Thomas J.; Smith, Jordan N.

Advancements in Exposure Science involving the development and deployment of biomarkers of exposure and biological response are anticipated to significantly (and positively) influence health outcomes associated with occupational, environmental and clinical exposure to chemicals/drugs. To achieve this vision, innovative strategies are needed to develop multiplex sensor platforms capable of quantifying individual and mixed exposures (i.e. systemic dose) by measuring biomarkers of dose and biological response in readily obtainable (non-invasive) biofluids. Secondly, the use of saliva (alternative to blood) for biomonitoring coupled with the ability to rapidly analyze multiple samples in real-time offers an innovative opportunity to revolutionize biomonitoring assessments. Inmore » this regard, the timing and number of samples taken for biomonitoring will not be limited as is currently the case. In addition, real-time analysis will facilitate identification of work practices or conditions that are contributing to increased exposures and will make possible a more rapid and successful intervention strategy. The initial development and application of computational models for evaluation of saliva/blood analyte concentration at anticipated exposure levels represents an important opportunity to establish the limits of quantification and robustness of multiplex sensor systems by exploiting a unique computational modeling framework. The use of these pharmacokinetic models will also enable prediction of an exposure dose based on the saliva/blood measurement. This novel strategy will result in a more accurate prediction of exposures and, once validated, can be employed to assess dosimetry to a broad range of chemicals in support of biomonitoring and epidemiology studies.« less

Mapping information exposure on social media to explain differences in HPV vaccine coverage in the United States.

PubMed

Dunn, Adam G; Surian, Didi; Leask, Julie; Dey, Aditi; Mandl, Kenneth D; Coiera, Enrico

2017-05-25

Together with access, acceptance of vaccines affects human papillomavirus (HPV) vaccine coverage, yet little is known about media's role. Our aim was to determine whether measures of information exposure derived from Twitter could be used to explain differences in coverage in the United States. We conducted an analysis of exposure to information about HPV vaccines on Twitter, derived from 273.8 million exposures to 258,418 tweets posted between 1 October 2013 and 30 October 2015. Tweets were classified by topic using machine learning methods. Proportional exposure to each topic was used to construct multivariable models for predicting state-level HPV vaccine coverage, and compared to multivariable models constructed using socioeconomic factors: poverty, education, and insurance. Outcome measures included correlations between coverage and the individual topics and socioeconomic factors; and differences in the predictive performance of the multivariable models. Topics corresponding to media controversies were most closely correlated with coverage (both positively and negatively); education and insurance were highest among socioeconomic indicators. Measures of information exposure explained 68% of the variance in one dose 2015 HPV vaccine coverage in females (males: 63%). In comparison, models based on socioeconomic factors explained 42% of the variance in females (males: 40%). Measures of information exposure derived from Twitter explained differences in coverage that were not explained by socioeconomic factors. Vaccine coverage was lower in states where safety concerns, misinformation, and conspiracies made up higher proportions of exposures, suggesting that negative representations of vaccines in the media may reflect or influence vaccine acceptance. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Global, spatial, and temporal sensitivity analysis for a complex pesticide fate and transport model.

EPA Science Inventory

Background/Questions/Methods As one ofthe most heavily used exposure models by U.S. EPA, Pesticide Root Zone Model (PRZM) is a one-dimensional, dynamic, compartment model that predicts the fate and transport of a pesticide in the unsaturated soil system around a plant's root zo...

Benchmarking analysis of three multimedia models: RESRAD, MMSOILS, and MEPAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, J.J.; Faillace, E.R.; Gnanapragasam, E.K.

1995-11-01

Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a comprehensive and quantitative benchmarking analysis of three multimedia models. The three models-RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)-represent analytically based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. A list of physical/chemical/biological processes related to multimedia-based exposure and risk assessment is first presented as a basis for comparing the overall capabilitiesmore » of RESRAD, MMSOILS, and MEPAS. Model design, formulation, and function are then examined by applying the models to a series of hypothetical problems. Major components of the models (e.g., atmospheric, surface water, groundwater) are evaluated separately and then studied as part of an integrated system for the assessment of a multimedia release scenario to determine effects due to linking components of the models. Seven modeling scenarios are used in the conduct of this benchmarking study: (1) direct biosphere exposure, (2) direct release to the air, (3) direct release to the vadose zone, (4) direct release to the saturated zone, (5) direct release to surface water, (6) surface water hydrology, and (7) multimedia release. Study results show that the models differ with respect to (1) environmental processes included (i.e., model features) and (2) the mathematical formulation and assumptions related to the implementation of solutions (i.e., parameterization).« less

Sensitivity analysis for linear structural equation models, longitudinal mediation with latent growth models and blended learning in biostatistics education

NASA Astrophysics Data System (ADS)

Sullivan, Adam John

In chapter 1, we consider the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and sensitivity analysis techniques to correct for such biases. We give an analysis of which effects in an SEM are and are not biased by an unmeasured confounder. It is shown that a single unmeasured confounder will bias not just one but numerous effects in an SEM. We present sensitivity analysis techniques to correct for biases in total, direct, and indirect effects when using SEM analyses, and illustrate these techniques with a study of aging and cognitive function. In chapter 2, we consider longitudinal mediation with latent growth curves. We define the direct and indirect effects using counterfactuals and consider the assumptions needed for identifiability of those effects. We develop models with a binary treatment/exposure followed by a model where treatment/exposure changes with time allowing for treatment/exposure-mediator interaction. We thus formalize mediation analysis with latent growth curve models using counterfactuals, makes clear the assumptions and extends these methods to allow for exposure mediator interactions. We present and illustrate the techniques with a study on Multiple Sclerosis(MS) and depression. In chapter 3, we report on a pilot study in blended learning that took place during the Fall 2013 and Summer 2014 semesters here at Harvard. We blended the traditional BIO 200: Principles of Biostatistics and created ID 200: Principles of Biostatistics and epidemiology. We used materials from the edX course PH207x: Health in Numbers: Quantitative Methods in Clinical & Public Health Research and used. These materials were used as a video textbook in which students would watch a given number of these videos prior to class. Using surveys as well as exam data we informally assess these blended classes from the student's perspective as well as a comparison of these students with students in another course, BIO 201: Introduction to Statistical Methods in Fall 2013 as well as students from BIO 200 in Fall semesters of 1992 and 1993. We then suggest improvements upon our original course designs and follow up with an informal look at how these implemented changes affected the second offering of the newly blended ID 200 in Summer 2014.

The Use Of Computational Human Performance Modeling As Task Analysis Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacuqes Hugo; David Gertman

2012-07-01

During a review of the Advanced Test Reactor safety basis at the Idaho National Laboratory, human factors engineers identified ergonomic and human reliability risks involving the inadvertent exposure of a fuel element to the air during manual fuel movement and inspection in the canal. There were clear indications that these risks increased the probability of human error and possible severe physical outcomes to the operator. In response to this concern, a detailed study was conducted to determine the probability of the inadvertent exposure of a fuel element. Due to practical and safety constraints, the task network analysis technique was employedmore » to study the work procedures at the canal. Discrete-event simulation software was used to model the entire procedure as well as the salient physical attributes of the task environment, such as distances walked, the effect of dropped tools, the effect of hazardous body postures, and physical exertion due to strenuous tool handling. The model also allowed analysis of the effect of cognitive processes such as visual perception demands, auditory information and verbal communication. The model made it possible to obtain reliable predictions of operator performance and workload estimates. It was also found that operator workload as well as the probability of human error in the fuel inspection and transfer task were influenced by the concurrent nature of certain phases of the task and the associated demand on cognitive and physical resources. More importantly, it was possible to determine with reasonable accuracy the stages as well as physical locations in the fuel handling task where operators would be most at risk of losing their balance and falling into the canal. The model also provided sufficient information for a human reliability analysis that indicated that the postulated fuel exposure accident was less than credible.« less

Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer.

PubMed

Brown, Kathryn; Comisar, Craig; Witjes, Han; Maringwa, John; de Greef, Rik; Vishwanathan, Karthick; Cantarini, Mireille; Cox, Eugène

2017-06-01

To develop a population (pop) pharmacokinetic (PK) model for osimertinib (AZD9291) and its metabolite (AZ5104) and investigate the exposure-response relationships for selected efficacy and safety parameters. PK, safety and efficacy data were collected from two non-small cell lung cancer (NSCLC) patient studies (n = 748) and one healthy volunteer study (n = 32), after single or multiple once-daily dosing of 20-240 mg osimertinib. Nonlinear mixed effects modelling was used to characterise the popPK. Individual exposure values were used to investigate the relationship with response evaluation criteria in solid tumours (RECIST 1.1) efficacy parameters and key safety parameters (rash, diarrhoea, QTcF). A popPK model that adequately described osimertinib and its metabolite AZ5104 in a joint manner was developed. Body weight, serum albumin and ethnicity were identified as significant covariates on PK in the analysis, but were not found to have a clinically relevant impact on osimertinib exposure. No relationship was identified between exposure and efficacy over the dose range studied. A linear relationship was observed between exposure and the occurrence of rash or diarrhoea, and between concentration and QTcF, with a predicted mean (upper 90% confidence interval) increase of 14.2 (15.8) ms at the maximum concentration for an 80 mg once-daily dose at steady state. PopPK and exposure-response models were developed for osimertinib and AZ5104. There was no relationship between exposure and efficacy but a linear relationship between exposure and safety endpoints (rash, diarrhoea and QTcF) was observed. © 2016 The British Pharmacological Society.

A risk assessment of direct and indirect exposure to emissions from a proposed hazardous waste incinerator in Puerto Rico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hallinger, K.; Huggins, A.; Warner, L.

1995-12-31

An Indirect Exposure Assessment (IEA) was conducted, under USEPA`s RCRA Combustion Strategy, as part of the Part B permitting process for a proposed hazardous waste incinerator. The IEA involved identification of constituents of concern, emissions estimations, air dispersion and deposition modeling, evaluation of site-specific exposure pathways/scenarios, and food chain modeling in order to evaluate potential human health and environmental risks. The COMPDEP model was used to determine ambient ground level concentrations and dry and wet deposition rates of constituents of concern. The air modeling results were input into 50th percentile (Central) and 95th percentile (High-End) exposure scenarios which evaluated directmore » exposure via inhalation, dermal contact, and soil ingestion pathways, and indirect exposure through the food chain. The indirect pathway analysis considered the accumulation of constituents in plants and animals used as food sources by local inhabitants. Local food consumption data obtained from the Puerto Rico USDA were combined with realistic present-day and future-use exposure scenarios such as residential use, pineapple farming, and subsistence farming to obtain a comprehensive evaluation of risk, Overall risk was calculated using constituent doses and toxicity factors associated with the various routes of exposure. Risk values for each exposure pathway were summed to determine total carcinogenic and non-carcinogenic hazard to exposed individuals. A population risk assessment was also conducted in order to assess potential risks to the population surrounding the facility. Results of the assessment indicated no acute effects from constituents of concern, and a high-end excess lifetime cancer risk of approximately 6 in a million with dioxins (as 2,3,7,8-TCDD) and arsenic dominating the risk estimate.« less

Statistical modelling of formaldehyde occupational exposure levels in French industries, 1986-2003.

PubMed

Lavoué, Jérôme; Vincent, Raymond; Gérin, Michel

2006-04-01

Occupational exposure databanks (OEDBs) have been cited as sources of exposure data for exposure surveillance and exposure assessment in epidemiology. In 2003, an extract was made from COLCHIC, the French national OEDB, of all concentrations of formaldehyde. The data were analysed with extended linear mixed-effects models in order to identify influent variables and elaborate a multi-sector picture of formaldehyde exposures. Respectively, 1401 and 1448 personal and area concentrations were available for the analysis. The fixed effects of the personal and area models explained, respectively, 57 and 53% of the total variance. Personal concentrations were related to the sampling duration (short-term higher than TWA levels), decreased with the year of sampling (-9% per year) and were higher when local exhaust ventilation was present. Personal levels taken during planned visits and for occupational illness notification purpose were consistently lower than those taken during ventilation modification programmes or because the hygienist suspected the presence of significant risk or exposure. Area concentrations were related to the sampling duration (short-term higher than TWA levels), and decreased with the year of sampling (-7% per year) and when the measurement sampling flow increased. Significant within-facility (correlation coefficient 0.4-0.5) and within-sampling campaign correlation (correlation coefficient 0.8) was found for both area and personal data. The industry/task classification appeared to have the greatest influence on exposure variability while the sample duration and the sampling flow were significant in some cases. Estimates made from the models for year 2002 showed elevated formaldehyde exposure in the fields of anatomopathological and biological analyses, operation of gluing machinery in the wood industry, operation and monitoring of mixers in the pharmaceutical industry, and garages and warehouses in urban transit authorities.

Signals for a promoting action of radiation in cancer incidence data.

PubMed

Heidenreich, W F

2002-09-01

The two-stage clonal expansion model allows us in principle to separate the initiating and promoting action of radiation. Features of the relative risk functions which indicate the action of promotion most clearly are identified for acute and for protracted exposures. They are compared with data: for acute exposure, some results of a preliminary analysis of the atomic-bomb survivor data are given; for protracted exposure, patterns in the fatal lung tumours of radon-exposed rats are discussed.

Associations of welding and manganese exposure with Parkinson disease

PubMed Central

Borenstein, Amy R.; Nelson, Lorene M.

2012-01-01

Objective: To examine associations of welding and manganese exposure with Parkinson disease (PD) using meta-analyses of data from cohort, case-control, and mortality studies. Methods: Epidemiologic studies related to welding or manganese exposure and PD were identified in a PubMed search, article references, published reviews, and abstracts. Inclusion criteria were 1) cohort, case-control, or mortality study with relative risk (RR), odds ratio (OR), or mortality OR (MOR) and 95 confidence intervals (95% CI); 2) RR, OR, and MOR matched or adjusted for age and sex; 3) valid study design and analysis. When participants of a study were a subgroup of those in a larger study, only results of the larger study were included to assure independence of datasets. Pooled RR/OR estimates and 95% CIs were obtained using random effects models; heterogeneity of study effects were evaluated using the Q statistic and I2 index in fixed effect models. Results: Thirteen studies met inclusion criteria for the welding meta-analysis and 3 studies for the manganese exposure meta-analysis. The pooled RR for the association between welding and PD for all study designs was 0.86 (95% CI 0.80–0.92), with absence of between-study heterogeneity (I2 = 0.0). Effect measures for cohort, case-control, and mortality studies were similar (0.91, 0.82, 0.87). For the association between manganese exposure and PD, the pooled OR was 0.76 (95% CI 0.41–1.42). Conclusions: Welding and manganese exposure are not associated with increased PD risk. Possible explanations for the inverse association between welding and PD include confounding by smoking, healthy worker effect, and hormesis. PMID:22965675

Use-Exposure Relationships of Pesticides for Aquatic Risk Assessment

PubMed Central

Luo, Yuzhou; Spurlock, Frank; Deng, Xin; Gill, Sheryl; Goh, Kean

2011-01-01

Field-scale environmental models have been widely used in aquatic exposure assessments of pesticides. Those models usually require a large set of input parameters and separate simulations for each pesticide in evaluation. In this study, a simple use-exposure relationship is developed based on regression analysis of stochastic simulation results generated from the Pesticide Root-Zone Model (PRZM). The developed mathematical relationship estimates edge-of-field peak concentrations of pesticides from aerobic soil metabolism half-life (AERO), organic carbon-normalized soil sorption coefficient (KOC), and application rate (RATE). In a case study of California crop scenarios, the relationships explained 90–95% of the variances in the peak concentrations of dissolved pesticides as predicted by PRZM simulations for a 30-year period. KOC was identified as the governing parameter in determining the relative magnitudes of pesticide exposures in a given crop scenario. The results of model application also indicated that the effects of chemical fate processes such as partitioning and degradation on pesticide exposure were similar among crop scenarios, while the cross-scenario variations were mainly associated with the landscape characteristics, such as organic carbon contents and curve numbers. With a minimum set of input data, the use-exposure relationships proposed in this study could be used in screening procedures for potential water quality impacts from the off-site movement of pesticides. PMID:21483772

Developmental fluoride neurotoxicity: a systematic review and meta-analysis.

PubMed

Choi, Anna L; Sun, Guifan; Zhang, Ying; Grandjean, Philippe

2012-10-01

Although fluoride may cause neurotoxicity in animal models and acute fluoride poisoning causes neurotoxicity in adults, very little is known of its effects on children's neurodevelopment. We performed a systematic review and meta-analysis of published studies to investigate the effects of increased fluoride exposure and delayed neurobehavioral development. We searched the MEDLINE, EMBASE, Water Resources Abstracts, and TOXNET databases through 2011 for eligible studies. We also searched the China National Knowledge Infrastructure (CNKI) database, because many studies on fluoride neurotoxicity have been published in Chinese journals only. In total, we identified 27 eligible epidemiological studies with high and reference exposures, end points of IQ scores, or related cognitive function measures with means and variances for the two exposure groups. Using random-effects models, we estimated the standardized mean difference between exposed and reference groups across all studies. We conducted sensitivity analyses restricted to studies using the same outcome assessment and having drinking-water fluoride as the only exposure. We performed the Cochran test for heterogeneity between studies, Begg's funnel plot, and Egger test to assess publication bias, and conducted meta-regressions to explore sources of variation in mean differences among the studies. The standardized weighted mean difference in IQ score between exposed and reference populations was -0.45 (95% confidence interval: -0.56, -0.35) using a random-effects model. Thus, children in high-fluoride areas had significantly lower IQ scores than those who lived in low-fluoride areas. Subgroup and sensitivity analyses also indicated inverse associations, although the substantial heterogeneity did not appear to decrease. The results support the possibility of an adverse effect of high fluoride exposure on children's neurodevelopment. Future research should include detailed individual-level information on prenatal exposure, neurobehavioral performance, and covariates for adjustment.

Supermarket and fast-food outlet exposure in Copenhagen: associations with socio-economic and demographic characteristics.

PubMed

Svastisalee, Chalida M; Nordahl, Helene; Glümer, Charlotte; Holstein, Bjørn E; Powell, Lisa M; Due, Pernille

2011-09-01

To investigate whether exposure to fast-food outlets and supermarkets is socio-economically patterned in the city of Copenhagen. The study was based on a cross-sectional multivariate approach to examine the association between the number of fast-food outlets and supermarkets and neighbourhood-level socio-economic indicators. Food business addresses were obtained from commercial and public business locators and geocoded using a geographic information system for all neighbourhoods in the city of Copenhagen (n 400). The regression of counts of fast-food outlets and supermarkets v. indicators of socio-economic status (percentage of recent immigrants, percentage without a high-school diploma, percentage of the population under 35 years of age and average household income in Euros) was performed using negative binomial analysis. Copenhagen, Denmark. The unit of analysis was neighbourhood (n 400). In the fully adjusted models, income was not a significant predictor for supermarket exposure. However, neighbourhoods with low and mid-low income were associated with significantly fewer fast-food outlets. Using backwise deletion from the fully adjusted models, low income remained significantly associated with fast-food outlet exposure (rate ratio = 0·66-0·80) in the final model. In the city of Copenhagen, there was no evidence of spatial patterning of supermarkets by income. However, we detected a trend in the exposure to fast-food outlets, such that neighbourhoods in the lowest income quartile had fewer fast-food outlets than higher-income neighbourhoods. These findings have similarities with studies conducted in the UK, but not in the USA. The results suggest there may be socio-economic factors other than income associated with food exposure in Europe.

Cross-shift changes in FEV1 in relation to wood dust exposure: the implications of different exposure assessment methods

PubMed Central

Schlunssen, V; Sigsgaard, T; Schaumburg, I; Kromhout, H

2004-01-01

Background: Exposure-response analyses in occupational studies rely on the ability to distinguish workers with regard to exposures of interest. Aims: To evaluate different estimates of current average exposure in an exposure-response analysis on dust exposure and cross-shift decline in FEV1 among woodworkers. Methods: Personal dust samples (n = 2181) as well as data on lung function parameters were available for 1560 woodworkers from 54 furniture industries. The exposure to wood dust for each worker was calculated in eight different ways using individual measurements, group based exposure estimates, a weighted estimate of individual and group based exposure estimates, and predicted values from mixed models. Exposure-response relations on cross-shift changes in FEV1 and exposure estimates were explored. Results: A positive exposure-response relation between average dust exposure and cross-shift FEV1 was shown for non-smokers only and appeared to be most pronounced among pine workers. In general, the highest slope and standard error (SE) was revealed for grouping by a combination of task and factory size, the lowest slope and SE was revealed for estimates based on individual measurements, with the weighted estimate and the predicted values in between. Grouping by quintiles of average exposure for task and factory combinations revealed low slopes and high SE, despite a high contrast. Conclusion: For non-smokers, average dust exposure and cross-shift FEV1 were associated in an exposure dependent manner, especially among pine workers. This study confirms the consequences of using different exposure assessment strategies studying exposure-response relations. It is possible to optimise exposure assessment combining information from individual and group based exposure estimates, for instance by applying predicted values from mixed effects models. PMID:15377768

Assessment of global flood exposures - developing an appropriate approach

NASA Astrophysics Data System (ADS)

Millinship, Ian; Booth, Naomi

2015-04-01

Increasingly complex probabilistic catastrophe models have become the standard for quantitative flood risk assessments by re/insurance companies. On the one hand, probabilistic modelling of this nature is extremely useful; a large range of risk metrics can be output. However, they can be time consuming and computationally expensive to develop and run. Levels of uncertainty are persistently high despite, or perhaps because of, attempts to increase resolution and complexity. A cycle of dependency between modelling companies and re/insurers has developed whereby available models are purchased, models run, and both portfolio and model data 'improved' every year. This can lead to potential exposures in perils and territories that are not currently modelled being largely overlooked by companies, who may then face substantial and unexpected losses when large events occur in these areas. We present here an approach to assessing global flood exposures which reduces the scale and complexity of approach used and begins with the identification of hotspots where there is a significant exposure to flood risk. The method comprises four stages: i) compile consistent exposure information, ii) to apply reinsurance terms and conditions to calculate values exposed, iii) to assess the potential hazard using a global set of flood hazard maps, and iv) to identify potential risk 'hotspots' which include considerations of spatially and/or temporally clustered historical events, and local flood defences. This global exposure assessment is designed as a scoping exercise, and reveals areas or cities where the potential for accumulated loss is of significant interest to a reinsurance company, and for which there is no existing catastrophe model. These regions are then candidates for the development of deterministic scenarios, or probabilistic models. The key advantages of this approach will be discussed. These include simplicity and ability of business leaders to understand results, as well as ease and speed of analysis and the advantages this can offer in terms of monitoring changing exposures over time. Significantly, in many areas of the world, this increase in exposure is likely to have more of an impact on increasing catastrophe losses than potential anthropogenically driven changes in weather extremes.

77 FR 25904 - Acequinocyl; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-02

.../oppefed1/models/water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... comments received in response to the notice of filing. Based upon review of the data supporting the...

75 FR 40741 - Hexythiazox; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-14

.../oppefed1/models/water/index.htm . Based on the Pesticide Root Zone Model /Exposure Analysis Modeling System... affected. The North American Industrial Classification System (NAICS) codes have been provided to assist... review of the data supporting the petition, EPA issued a notice in the Federal Register of March 17, 2010...

Sensitivity Analysis of Dispersion Model Results in the NEXUS Health Study Due to Uncertainties in Traffic-Related Emissions Inputs

EPA Science Inventory

Dispersion modeling tools have traditionally provided critical information for air quality management decisions, but have been used recently to provide exposure estimates to support health studies. However, these models can be challenging to implement, particularly in near-road s...

Mortality and morbidity among people living close to incinerators: a cohort study based on dispersion modeling for exposure assessment

PubMed Central

2011-01-01

Background Several studies have been conducted on the possible health effects for people living close to incinerators and well-conducted reviews are available. Nevertheless, several uncertainties limit the overall interpretation of the findings. We evaluated the health effects of emissions from two incinerators in a pilot cohort study. Methods The study area was defined as the 3.5 km radius around two incinerators located near Forlì (Italy). People who were residents in 1/1/1990, or subsequently became residents up to 31/12/2003, were enrolled in a longitudinal study (31,347 individuals). All the addresses were geocoded. Follow-up continued until 31/12/2003 by linking the mortality register, cancer registry and hospital admissions databases. Atmospheric Dispersion Model System (ADMS) software was used for exposure assessment; modelled concentration maps of heavy metals (annual average) were considered the indicators of exposure to atmospheric pollution from the incinerators, while concentration maps of nitrogen dioxide (NO2) were considered for exposure to other pollution sources. Age and area-based socioeconomic status adjusted rate ratios and 95% Confidence Intervals were estimated with Poisson regression, using the lowest exposure category to heavy metals as reference. Results The mortality and morbidity experience of the whole cohort did not differ from the regional population. In the internal analysis, no association between pollution exposure from the incinerators and all-cause and cause-specific mortality outcomes was observed in men, with the exception of colon cancer. Exposure to the incinerators was associated with cancer mortality among women, in particular for all cancer sites (RR for the highest exposure level = 1.47, 95% CI: 1.09, 1.99), stomach, colon, liver and breast cancer. No clear trend was detected for cancer incidence. No association was found for hospitalizations related to major diseases. NO2 levels, as a proxy from other pollution sources (traffic in particular), did not exert an important confounding role. Conclusions No increased risk of mortality and morbidity was found in the entire area. The internal analysis of the cohort based on dispersion modeling found excesses of mortality for some cancer types in the highest exposure categories, especially in women. The interpretation of the findings is limited given the pilot nature of the study. PMID:21435200

Parameter sensitivity analysis for pesticide impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and linear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed that simulate hive population trajectories, taking into account queen strength, foraging success, weather, colo...

Sobol’ sensitivity analysis for stressor impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather...

Meta-analysis on occupational exposure to pesticides--neurobehavioral impact and dose-response relationships.

PubMed

Meyer-Baron, Monika; Knapp, Guido; Schäper, Michael; van Thriel, Christoph

2015-01-01

While the health impact of high exposures to pesticides is acknowledged, the impact of chronic exposures in the absence of acute poisonings is controversial. A systematic analysis of dose-response relationships is still missing. Its absence may provoke alternative explanations for altered performances. Consequently, opportunities for health prevention in the occupational and environmental field may be missed. Objectives were (1) quantification of the neurotoxic impact of pesticides by an analysis of functional alterations in workers measured by neuropsychological performance tests, (2) estimates of dose-response relationships on the basis of exposure duration, and (3) exploration of susceptible subgroups. The meta-analysis employed a random effects model to obtain overall effects for individual performance tests. Twenty-two studies with a total of 1758 exposed and 1260 reference individuals met the inclusion criteria. At least three independent outcomes were available for twenty-six performance variables. Significant performance effects were shown in adults and referred to both cognitive and motor performances. Effect sizes ranging from dRE=-0.14 to dRE=-0.67 showed consistent outcomes for memory and attention. Relationships between effect sizes and exposure duration were indicated for individual performance variables and the total of measured performances. Studies on adolescents had to be analyzed separately due to numerous outliers. The large variation among outcomes hampered the analysis of the susceptibility in this group, while data on female workers was too scant for the analysis. Relationships exist between the impact of pesticides on performances and exposure duration. A change in test paradigms would help to decipher the impact more specifically. The use of biomarkers appropriate for lower exposures would allow a better prevention of neurotoxic effects due to occupational and environmental exposure. Intervention studies in adolescents seem warranted to specify their risk. Copyright © 2014 Elsevier Inc. All rights reserved.

FACTORS INFLUENCING TOTAL DIETARY EXPOSURE OF YOUNG CHILDREN

EPA Science Inventory

A deterministic model was developed to identify critical input parameters to assess dietary intake of young children. The model was used as a framework for understanding important factors in data collection and analysis. Factors incorporated included transfer efficiencies of pest...

VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine mechanism of the metabolic interactions occurring during simultaneous inhalation exposures to the organic solvents chloroform and trichloroethylene (TCE).

V...

VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine the mechanism of metabolic interactions occurring during simultaneous exposures to the organic solvents chloroform and trichloroethylene (TCE). Visualization-based se...

Estimating the effect of immortal-time bias in urological research: a case example of testosterone-replacement therapy.

PubMed

Wallis, Christopher J D; Saskin, Refik; Narod, Steven A; Law, Calvin; Kulkarni, Girish S; Seth, Arun; Nam, Robert K

2017-10-01

To quantify the effect of immortal-time bias in an observational study examining the effect of cumulative testosterone exposure on mortality. We used a population-based matched cohort study of men aged ≥66 years, newly treated with testosterone-replacement therapy (TRT), and matched-controls from 2007 to 2012 in Ontario, Canada to quantify the effects of immortal-time bias. We used generalised estimating equations to determine the association between cumulative TRT exposure and mortality. Results produced by models using time-fixed and time-varying exposures were compared. Further, we undertook a systematic review of PubMed to identify studies addressing immortal-time bias or time-varying exposures in the urological literature and qualitatively summated these. Among 10 311 TRT-exposed men and 28 029 controls, the use of a time-varying exposure resulted in the attenuation of treatment effects compared with an analysis that did not account for immortal-time bias. While both analyses showed a decreased risk of death for patients in the highest tertile of TRT exposure, the effect was overestimated when using a time-fixed analysis (adjusted hazard ratio [aHR] 0.56, 95% confidence interval [CI]: 0.52-0.61) when compared to a time-varying analysis (aHR 0.67, 95% CI: 0.62-0.73). Of the 1 241 studies employing survival analysis identified in the literature, nine manuscripts met criteria for inclusion. Of these, five used a time-varying analytical method. Each of these was a large, population-based retrospective cohort study assessing potential harms of pharmacological agents. Where exposures vary over time, a time-varying exposure is necessary to draw meaningful conclusions. Failure to use a time-varying analysis will result in overestimation of a beneficial effect. However, time-varying exposures are uncommonly utilised among manuscripts published in prominent urological journals. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Childhood autism spectrum disorders and exposure to nitrogen dioxide, and particulate matter air pollution: A review and meta-analysis.

PubMed

Flores-Pajot, Marie-Claire; Ofner, Marianna; Do, Minh T; Lavigne, Eric; Villeneuve, Paul J

2016-11-01

Genetic and environmental factors have been recognized to play an important role in autism. The possibility that exposure to outdoor air pollution increases the risk of autism spectrum disorder (ASD) has been an emerging area of research. Herein, we present a systematic review, and meta-analysis of published epidemiological studies that have investigated these associations. We undertook a comprehensive search strategy to identify studies that investigated outdoor air pollution and autism in children. Overall, seven cohorts and five case-control studies met our inclusion criteria for the meta-analysis. We summarized the associations between exposure to air pollution and ASD based on the following critical exposure windows: (i) first, second and third trimester of pregnancy, (ii) entire pregnancy, and (iii) postnatal period. Random effects meta-analysis modeling was undertaken to derive pooled risk estimates for these exposures across the studies. The meta-estimates for the change in ASD associated with a 10μg/m 3 increase in exposure in PM 2.5 and 10 ppb increase in NO 2 during pregnancy were 1.34 (95% CI:0.83, 2.17) and 1.05 (95% CI:0.99, 1.11), respectively. Stronger associations were observed for exposures received after birth, but these estimates were unstable as they were based on only two studies. O 3 exposure was weakly associated with ASD during the third trimester of pregnancy and during the entire pregnancy, however, these estimates were also based on only two studies. Our meta-analysis support the hypothesis that exposure to ambient air pollution is associated with an increased risk of autism. Our findings should be interpreted cautiously due to relatively small number of studies, and several studies were unable to control for other key risk factors. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of methods to control for immortal time bias in a pharmacoepidemiologic analysis of renin-angiotensin system inhibitors in type 2 diabetes.

PubMed

Yang, Xilin; Kong, Alice Ps; Luk, Andrea Oy; Ozaki, Risa; Ko, Gary Tc; Ma, Ronald Cw; Chan, Juliana Cn; So, Wing Yee

2014-01-01

Pharmacoepidemiologic analysis can confirm whether drug efficacy in a randomized controlled trial (RCT) translates to effectiveness in real settings. We examined methods used to control for immortal time bias in an analysis of renin-angiotensin system (RAS) inhibitors as the reference cardioprotective drug. We analyzed data from 3928 patients with type 2 diabetes who were recruited into the Hong Kong Diabetes Registry between 1996 and 2005 and followed up to July 30, 2005. Different Cox models were used to obtain hazard ratios (HRs) for cardiovascular disease (CVD) associated with RAS inhibitors. These HRs were then compared to the HR of 0.92 reported in a recent meta-analysis of RCTs. During a median follow-up period of 5.45 years, 7.23% (n = 284) patients developed CVD and 38.7% (n = 1519) were started on RAS inhibitors, with 39.1% of immortal time among the users. In multivariable analysis, time-dependent drug-exposure Cox models and Cox models that moved immortal time from users to nonusers both severely inflated the HR, and time-fixed models that included immortal time deflated the HR. Use of time-fixed Cox models that excluded immortal time resulted in a HR of only 0.89 (95% CI, 0.68-1.17) for CVD associated with RAS inhibitors, which is closer to the values reported in RCTs. In pharmacoepidemiologic analysis, time-dependent drug exposure models and models that move immortal time from users to nonusers may introduce substantial bias in investigations of the effects of RAS inhibitors on CVD in type 2 diabetes.

Molecular Genetic Analysis of Ethanol Intoxication in Drosophila melanogaster.

PubMed

Heberlein, Ulrike; Wolf, Fred W; Rothenfluh, Adrian; Guarnieri, Douglas J

2004-08-01

Recently, the fruit fly Drosophila melanogaster has been introduced as a model system to study the molecular bases of a variety of ethanol-induced behaviors. It became immediately apparent that the behavioral changes elicited by acute ethanol exposure are remarkably similar in flies and mammals. Flies show signs of acute intoxication, which range from locomotor stimulation at low doses to complete sedation at higher doses and they develop tolerance upon intermittent ethanol exposure. Genetic screens for mutants with altered responsiveness to ethanol have been carried out and a few of the disrupted genes have been identified. This analysis, while still in its early stages, has already revealed some surprising molecular parallels with mammals. The availability of powerful tools for genetic manipulation in Drosophila, together with the high degree of conservation at the genomic level, make Drosophila a promising model organism to study the mechanism by which ethanol regulates behavior and the mechanisms underlying the organism's adaptation to long-term ethanol exposure.

Affecting Factors of Secondhand Smoke Exposure in Korea: Focused on Different Exposure Locations.

PubMed

Sun, Li Yuan; Cheong, Hae Kwan; Lee, Eun Whan; Kang, Kyeong Jin; Park, Jae Hyun

2016-09-01

Exposure to secondhand smoke (SHS) not only can cause serious illness, but is also an economic and social burden. Contextual and individual factors of non-smoker exposure to SHS depend on location. However, studies focusing on this subject are lacking. In this study, we described and compared the factors related to SHS exposure according to location in Korea. Regarding individual factors related to SHS exposure, a common individual variable model and location-specific variable model was used to evaluate SHS exposure at home/work/public locations based on sex. In common individual variables, such as age, and smoking status showed different relationships with SHS exposure in different locations. Among home-related variables, housing type and family with a single father and unmarried children showed the strongest positive relationships with SHS exposure in both males and females. In the workplace, service and sales workers, blue-collar workers, and manual laborers showed the strongest positive association with SHS exposure in males and females. For multilevel analysis in public places, only SHS exposure in females was positively related with cancer screening rate. Exposure to SHS in public places showed a positive relationship with drinking rate and single-parent family in males and females. The problem of SHS embodies social policies and interactions between individuals and social contextual factors. Policy makers should consider the contextual factors of specific locations and regional and individual context, along with differences between males and females, to develop effective strategies for reducing SHS exposure.

Modeling the Unites States government's economic cost of noise-induced hearing loss for a military population.

PubMed

Tufts, Jennifer B; Weathersby, Paul K; Rodriguez, Francisco A

2010-05-01

The purpose of this paper is to demonstrate the feasibility and utility of developing economic cost models for noise-induced hearing loss (NIHL). First, we outline an economic model of NIHL for a population of US Navy sailors with an "industrial"-type noise exposure. Next, we describe the effect on NIHL-related cost of varying the two central model inputs--the noise-exposure level and the duration of exposure. Such an analysis can help prioritize promising areas, to which limited resources to reduce NIHL-related costs should be devoted. NIHL-related costs borne by the US government were computed on a yearly basis using a finite element approach that took into account varying levels of susceptibility to NIHL. Predicted hearing thresholds for the population were computed with ANSI S3.44-1996 and then used as the basis for the calculation of NIHL-related costs. Annual and cumulative costs were tracked. Noise-exposure level and duration were systematically varied to determine their effects on the expected lifetime NIHL-related cost of a specific US Navy sailor population. Our nominal noise-exposure case [93 dB(A) for six years] yielded a total expected lifetime cost of US $13,472 per sailor, with plausible lower and upper bounds of US $2,500 and US $26,000. Starting with the nominal case, a decrease of 50% in exposure level or duration would yield cost savings of approximately 23% and 19%, respectively. We concluded that a reduction in noise level would be more somewhat more cost-effective than the same percentage reduction in years of exposure. Our economic cost model can be used to estimate the changes in NIHL-related costs that would result from changes in noise-exposure level and/or duration for a single military population. Although the model is limited at present, suggestions are provided for adapting it to civilian populations.

Cancer Risk Assessment in Welder's Under Different Exposure Scenarios.

PubMed

Barkhordari, Abolfazl; Zare Sakhvidi, Mohammad Javad; Zare Sakhvidi, Fariba; Halvani, Gholamhossein; Firoozichahak, Ali; Shirali, GholamAbbas

2014-05-01

Welders exposure to nickel and hexavalent chromium in welding fumes is associated with increase of cancer risk in welders. In this study we calculated cancer risk due to exposure to these compounds in welders. The role of exposure parameters in welders on derived incremental lifetime cancer risk were determined by stochastic modeling of cancer risk. Input parameters were determined by field investigation in Iranian welders in 2013 and literature review. The 90% upper band cancer risk due to hexavalent chromium and nickel exposure was in the range of 6.03E-03 to 2.12E-02 and 7.18E-03 to 2.61E-02 respectively. Scenario analysis showed that asthmatic and project welders are significantly at higher cancer risk in comparison with other welders (P<0.05). Shift duration was responsible for 37% and 33% of variances for hexavalent chromium and nickel respectively. Welders are at high and unacceptable risk of cancer. Control measures according to scenario analysis findings are advisable.

Assessment of Prenatal Exposure to Arsenic in Tenerife Island

PubMed Central

Vall, Oriol; Gómez-Culebras, Mario; Garcia-Algar, Oscar; Joya, Xavier; Velez, Dinoraz; Rodríguez-Carrasco, Eva; Puig, Carme

2012-01-01

Introduction Increasing awareness of the potential chronic health effects of arsenic (As) at low exposure levels has motivated efforts to better understand impaired child development during pregnancy by biomarkers of exposure. The aims of this study were to evaluate the prenatal exposure to As by analysis of an alternative matrix (meconium), to examine its effects on neonatal outcomes and investigate the association with maternal lifestyle and dietary habits during pregnancy. Methods A transversal descriptive study was conducted in Tenerife (Spain). A total of 96 mother-child pairs participated in the study. A questionnaire on sociodemographic, lifestyle and dietary habits during pregnancy was administered the day after the delivery. Analysis of total As in meconium was performed by inductively coupled plasma-optical emission spectrometer. Results Total As was detected in 37 (38.5%) meconium samples. The univariate logistic regression model indicates that prenatal exposure to As was associated with a low intake of eggs per week (OR 0.56; CI (95%): 0.34–0.94) during pregnancy. Conversely, frequent intake of vegetables was associated with prenatal As exposure (OR: 1.19; CI (95%): 1.01–1.41) and frequent intake of processed meat (as bacon, Frankfurt’s sausage, and hamburger) shows a trend to As prenatal exposure (OR: 8.54; CI (95%): 0.80–90.89). The adjusted multivariate logistic regression model indicates that only frequent intake of vegetables maintains the association (OR: 1.31; CI (95%): 1.02–1.68). Conclusion The studied population presented a low As exposure and was not associated with neonatal effects. Maternal consumption of vegetables during pregnancy was associated with detectable meconium As levels; however the concentration detected in meconium was too low to be considered a major public health concern in this geographical area. PMID:23209747

Comparative Exposure Assessment of ESBL-Producing Escherichia coli through Meat Consumption

PubMed Central

Pielaat, Annemarie; Smid, Joost H.; van Duijkeren, Engeline; Vennemann, Francy B. C.; Wijnands, Lucas M.; Chardon, Jurgen E.

2017-01-01

The presence of extended-spectrum β-lactamase (ESBL) and plasmidic AmpC (pAmpC) producing Escherichia coli (EEC) in food animals, especially broilers, has become a major public health concern. The aim of the present study was to quantify the EEC exposure of humans in The Netherlands through the consumption of meat from different food animals. Calculations were done with a simplified Quantitative Microbiological Risk Assessment (QMRA) model. The model took the effect of pre-retail processing, storage at the consumers home and preparation in the kitchen (cross-contamination and heating) on EEC numbers on/in the raw meat products into account. The contribution of beef products (78%) to the total EEC exposure of the Dutch population through the consumption of meat was much higher than for chicken (18%), pork (4.5%), veal (0.1%) and lamb (0%). After slaughter, chicken meat accounted for 97% of total EEC load on meat, but chicken meat experienced a relatively large effect of heating during food preparation. Exposure via consumption of filet americain (a minced beef product consumed raw) was predicted to be highest (61% of total EEC exposure), followed by chicken fillet (13%). It was estimated that only 18% of EEC exposure occurred via cross-contamination during preparation in the kitchen, which was the only route by which EEC survived for surface-contaminated products. Sensitivity analysis showed that model output is not sensitive for most parameters. However, EEC concentration on meat other than chicken meat was an important data gap. In conclusion, the model assessed that consumption of beef products led to a higher exposure to EEC than chicken products, although the prevalence of EEC on raw chicken meat was much higher than on beef. The (relative) risk of this exposure for public health is yet unknown given the lack of a modelling framework and of exposure studies for other potential transmission routes. PMID:28056081

A PROBABILISTIC ARSENIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CHROMATED COPPER ARSENATE ( CAA )-TREATED PLAYSETS AND DECKS: PART 2 SENSITIVITY AND UNCERTAINTY ANALYSIS

EPA Science Inventory

A probabilistic model (SHEDS-Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two part paper. This Part 2 paper discusses sensitivity and uncertainty analyses conducted to assess the key m...

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

NASA Astrophysics Data System (ADS)

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-06-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening.

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

PubMed Central

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-01-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening. PMID:28621308

Exploring associations between prenatal solvent exposures and teenage drug and alcohol use: a retrospective cohort study.

PubMed

Gallagher, Lisa G; Webster, Thomas F; Aschengrau, Ann

2017-03-11

Investigating the effects of prenatal and childhood exposures on behavioral health outcomes in adolescence is challenging given the lengthy period between the exposure and outcomes. We conducted a retrospective cohort study in Cape Cod, Massachusetts to evaluate the impact of prenatal and early childhood exposure to tetrachloroethylene (PCE)-contaminated drinking water on the occurrence of risk-taking behaviors as a teenager. An increased occurrence of risk-taking behaviors, particularly illicit drug use, was observed in those highly exposed to PCE. We hypothesized that there may be other sources of prenatal solvent exposure such as maternal consumption of alcoholic beverages during pregnancy which might modify the previously observed associations between PCE and risk-taking behaviors and so we conducted an exploratory analysis using available cohort data. The current report presents the results of these analyses and describes the difficulties in conducting research on long-term behavioral effects of early life exposures. The exploratory analysis compared a referent group of subjects with no early life exposure to PCE or alcohol (n = 242) to subjects with only alcohol exposure (n = 201), subjects with only PCE exposure (n = 361), and subjects with exposure to both PCE and alcohol (n = 302). Surveys completed by the subject's mother included questions on prenatal alcoholic beverage consumption and available confounding variables such as cigarette smoking and marijuana use. Surveys completed by the subjects included questions on risk-taking behaviors such as alcoholic beverage consumption and illicit drug use as a teenager and available confounding variables. PCE exposure was modeled using a leaching and transport algorithm embedded in water distribution system modeling software that estimated the amount of PCE delivered to a subject's residence during gestation and early childhood. Subjects with early life exposure to both PCE and alcohol had an increased risk of using two or more major drugs as a teen (RR = 1.9 (95% CI 1.2, 3.0)) compared to unexposed subjects. Increased risks for only PCE exposure (RR = 1.6 (95% CI 1.0, 2.4) and only alcohol exposure (RR = 1.3 (95% CI 0.7, 2.1)) were also evident but were smaller than the increased risk associated with both exposures. While available confounding variables were controlled, many relevant social risk factors were not obtained due to limitations in the retrospective study design. This exploratory analysis found evidence for an additive effect of early life exposure to PCE and alcohol on the risk of use of multiple illicit drugs as a teenager. Because of numerous limitations in this retrospective study, further research is needed to examine longstanding behavioral effects of early life exposures. To be most informative, this research should involve long-term prospective data collection.

Alcohol, Sex, and Screens: Modeling Media Influence on Adolescent Alcohol and Sex Co-Occurrence.

PubMed

Bleakley, Amy; Ellithorpe, Morgan E; Hennessy, Michael; Khurana, Atika; Jamieson, Patrick; Weitz, Ilana

2017-10-01

Alcohol use and sexual behavior are important risk behaviors in adolescent development, and combining the two is common. The reasoned action approach (RAA) is used to predict adolescents' intention to combine alcohol use and sexual behavior based on exposure to alcohol and sex combinations in popular entertainment media. We conducted a content analysis of mainstream (n = 29) and Black-oriented movies (n = 34) from 2014 and 2013-2014, respectively, and 56 television shows (2014-2015 season). Content analysis ratings featuring character portrayals of both alcohol and sex within the same five-minute segment were used to create exposure measures that were linked to online survey data collected from 1,990 adolescents ages 14 to 17 years old (50.3% Black, 49.7% White; 48.1% female). Structural equation modeling (SEM) and group analysis by race were used to test whether attitudes, norms, and perceived behavioral control mediated the effects of media exposure on intention to combine alcohol and sex. Results suggest that for both White and Black adolescents, exposure to media portrayals of alcohol and sex combinations is positively associated with adolescents' attitudes and norms. These relationships were stronger among White adolescents. Intention was predicted by attitude, norms, and control, but only the attitude-intention relationship was different by race group (stronger for Whites).

Occupational exposures and non-Hodgkin's lymphoma: Canadian case-control study.

PubMed

Karunanayake, Chandima P; McDuffie, Helen H; Dosman, James A; Spinelli, John J; Pahwa, Punam

2008-08-07

The objective was to study the association between Non-Hodgkin's Lymphoma (NHL) and occupational exposures related to long held occupations among males in six provinces of Canada. A population based case-control study was conducted from 1991 to 1994. Males with newly diagnosed NHL (ICD-10) were stratified by province of residence and age group. A total of 513 incident cases and 1506 population based controls were included in the analysis. Conditional logistic regression was conducted to fit statistical models. Based on conditional logistic regression modeling, the following factors independently increased the risk of NHL: farmer and machinist as long held occupations; constant exposure to diesel exhaust fumes; constant exposure to ionizing radiation (radium); and personal history of another cancer. Men who had worked for 20 years or more as farmer and machinist were the most likely to develop NHL. An increased risk of developing NHL is associated with the following: long held occupations of faer and machinist; exposure to diesel fumes; and exposure to ionizing radiation (radium). The risk of NHL increased with the duration of employment as a farmer or machinist.

AQMEII3: the EU and NA regional scale program of the ...

EPA Pesticide Factsheets

The presentation builds on the work presented last year at the 14th CMAS meeting and it is applied to the work performed in the context of the AQMEII-HTAP collaboration. The analysis is conducted within the framework of the third phase of AQMEII (Air Quality Model Evaluation International Initiative) and encompasses the gauging of model performance through measurement-to-model comparison, error decomposition and time series analysis of the models biases. Through the comparison of several regional-scale chemistry transport modelling systems applied to simulate meteorology and air quality over two continental areas, this study aims at i) apportioning the error to the responsible processes through time-scale analysis, and ii) help detecting causes of models error, and iii) identify the processes and scales most urgently requiring dedicated investigations. The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while the apportioning of the error into its constituent parts (bias, variance and covariance) can help assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the previous phases of AQMEII. The National Exposure Research Laboratory (NERL) Computational Exposur

Complementary proteomic approaches reveal mitochondrial dysfunction, immune and inflammatory dysregulation in a mouse model of Gulf War Illness.

PubMed

Zakirova, Zuchra; Reed, Jon; Crynen, Gogce; Horne, Lauren; Hassan, Samira; Mathura, Venkatarajan; Mullan, Michael; Crawford, Fiona; Ait-Ghezala, Ghania

2017-09-01

Long-term consequences of combined pyridostigmine bromide (PB) and permethrin (PER) exposure in C57BL6/J mice using a well-characterized mouse model of exposure to these Gulf War (GW) agents were explored at the protein level. We used orthogonal proteomic approaches to identify pathways that are chronically impacted in the mouse CNS due to semiacute GW agent exposure early in life. These analyses were performed on soluble and membrane-bound protein fractions from brain samples using two orthogonal isotopic labeling LC-MS/MS proteomic approaches-stable isotope dimethyl labeling and iTRAQ. The use of these approaches allowed for greater coverage of proteins than was possible by either one alone and revealed both distinct and overlapping datasets. This combined analysis identified changes in several mitochondrial, as well as immune and inflammatory pathways after GW agent exposure. The work discussed here provides insight into GW agent exposure dependent mechanisms that adversely affect mitochondrial function and immune and inflammatory regulation. Collectively, our work identified key pathways which were chronically impacted in the mouse CNS following acute GW agent exposure, this may lead to the identification of potential targets for therapeutic intervention in the future. Long-term consequences of combined PB and PER exposure in C57BL6/J mice using a well-characterized mouse model of exposure to these GW agents were explored at the protein level. Expanding on earlier work, we used orthogonal proteomic approaches to identify pathways that are chronically impacted in the mouse CNS due to semiacute GW agent exposure early in life. These analyses were performed on soluble and membrane-bound protein fractions from brain samples using two orthogonal isotopic labeling LC-MS/MS proteomic approaches-stable isotope dimethyl labeling and iTRAQ. The use of these approaches allowed for greater coverage of proteins than was possible by either one alone and revealed both distinct and overlapping datasets. This combined analysis identified changes in several mitochondrial, as well as immune and inflammatory pathways after GW agent exposure. The work discussed here provides insight into GW agent exposure dependent mechanisms that adversely affect mitochondrial function and immune and inflammatory regulation at 5 months postexposure to PB + PER. © 2017 The Authors. PROTEOMICS - Clinical Applications published by WILEY-VCH Verlag GmbH & Co. KGaA.

Complementary proteomic approaches reveal mitochondrial dysfunction, immune and inflammatory dysregulation in a mouse model of Gulf War Illness

PubMed Central

Zakirova, Zuchra; Reed, Jon; Crynen, Gogce; Horne, Lauren; Hassan, Samira; Mathura, Venkatarajan; Mullan, Michael; Crawford, Fiona

2017-01-01

Purpose Long‐term consequences of combined pyridostigmine bromide (PB) and permethrin (PER) exposure in C57BL6/J mice using a well‐characterized mouse model of exposure to these Gulf War (GW) agents were explored at the protein level. Experimental design We used orthogonal proteomic approaches to identify pathways that are chronically impacted in the mouse CNS due to semiacute GW agent exposure early in life. These analyses were performed on soluble and membrane‐bound protein fractions from brain samples using two orthogonal isotopic labeling LC‐MS/MS proteomic approaches—stable isotope dimethyl labeling and iTRAQ. Results The use of these approaches allowed for greater coverage of proteins than was possible by either one alone and revealed both distinct and overlapping datasets. This combined analysis identified changes in several mitochondrial, as well as immune and inflammatory pathways after GW agent exposure. Conclusions and clinical relevance The work discussed here provides insight into GW agent exposure dependent mechanisms that adversely affect mitochondrial function and immune and inflammatory regulation. Collectively, our work identified key pathways which were chronically impacted in the mouse CNS following acute GW agent exposure, this may lead to the identification of potential targets for therapeutic intervention in the future. Long‐term consequences of combined PB and PER exposure in C57BL6/J mice using a well‐characterized mouse model of exposure to these GW agents were explored at the protein level. Expanding on earlier work, we used orthogonal proteomic approaches to identify pathways that are chronically impacted in the mouse CNS due to semiacute GW agent exposure early in life. These analyses were performed on soluble and membrane‐bound protein fractions from brain samples using two orthogonal isotopic labeling LC‐MS/MS proteomic approaches—stable isotope dimethyl labeling and iTRAQ. The use of these approaches allowed for greater coverage of proteins than was possible by either one alone and revealed both distinct and overlapping datasets. This combined analysis identified changes in several mitochondrial, as well as immune and inflammatory pathways after GW agent exposure. The work discussed here provides insight into GW agent exposure dependent mechanisms that adversely affect mitochondrial function and immune and inflammatory regulation at 5 months postexposure to PB + PER. PMID:28371386

Identification and estimation of survivor average causal effects.

PubMed

Tchetgen Tchetgen, Eric J

2014-09-20

In longitudinal studies, outcomes ascertained at follow-up are typically undefined for individuals who die prior to the follow-up visit. In such settings, outcomes are said to be truncated by death and inference about the effects of a point treatment or exposure, restricted to individuals alive at the follow-up visit, could be biased even if as in experimental studies, treatment assignment were randomized. To account for truncation by death, the survivor average causal effect (SACE) defines the effect of treatment on the outcome for the subset of individuals who would have survived regardless of exposure status. In this paper, the author nonparametrically identifies SACE by leveraging post-exposure longitudinal correlates of survival and outcome that may also mediate the exposure effects on survival and outcome. Nonparametric identification is achieved by supposing that the longitudinal data arise from a certain nonparametric structural equations model and by making the monotonicity assumption that the effect of exposure on survival agrees in its direction across individuals. A novel weighted analysis involving a consistent estimate of the survival process is shown to produce consistent estimates of SACE. A data illustration is given, and the methods are extended to the context of time-varying exposures. We discuss a sensitivity analysis framework that relaxes assumptions about independent errors in the nonparametric structural equations model and may be used to assess the extent to which inference may be altered by a violation of key identifying assumptions. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Identification and estimation of survivor average causal effects

PubMed Central

Tchetgen, Eric J Tchetgen

2014-01-01

In longitudinal studies, outcomes ascertained at follow-up are typically undefined for individuals who die prior to the follow-up visit. In such settings, outcomes are said to be truncated by death and inference about the effects of a point treatment or exposure, restricted to individuals alive at the follow-up visit, could be biased even if as in experimental studies, treatment assignment were randomized. To account for truncation by death, the survivor average causal effect (SACE) defines the effect of treatment on the outcome for the subset of individuals who would have survived regardless of exposure status. In this paper, the author nonparametrically identifies SACE by leveraging post-exposure longitudinal correlates of survival and outcome that may also mediate the exposure effects on survival and outcome. Nonparametric identification is achieved by supposing that the longitudinal data arise from a certain nonparametric structural equations model and by making the monotonicity assumption that the effect of exposure on survival agrees in its direction across individuals. A novel weighted analysis involving a consistent estimate of the survival process is shown to produce consistent estimates of SACE. A data illustration is given, and the methods are extended to the context of time-varying exposures. We discuss a sensitivity analysis framework that relaxes assumptions about independent errors in the nonparametric structural equations model and may be used to assess the extent to which inference may be altered by a violation of key identifying assumptions. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24889022

Diesel engine exhaust and lung cancer risks - evaluation of the meta-analysis by Vermeulen et al. 2014.

PubMed

Morfeld, Peter; Spallek, Michael

2015-01-01

Vermeulen et al. 2014 published a meta-regression analysis of three relevant epidemiological US studies (Steenland et al. 1998, Garshick et al. 2012, Silverman et al. 2012) that estimated the association between occupational diesel engine exhaust (DEE) exposure and lung cancer mortality. The DEE exposure was measured as cumulative exposure to estimated respirable elemental carbon in μg/m(3)-years. Vermeulen et al. 2014 found a statistically significant dose-response association and described elevated lung cancer risks even at very low exposures. We performed an extended re-analysis using different modelling approaches (fixed and random effects regression analyses, Greenland/Longnecker method) and explored the impact of varying input data (modified coefficients of Garshick et al. 2012, results from Crump et al. 2015 replacing Silverman et al. 2012, modified analysis of Moehner et al. 2013). We reproduced the individual and main meta-analytical results of Vermeulen et al. 2014. However, our analysis demonstrated a heterogeneity of the baseline relative risk levels between the three studies. This heterogeneity was reduced after the coefficients of Garshick et al. 2012 were modified while the dose coefficient dropped by an order of magnitude for this study and was far from being significant (P = 0.6). A (non-significant) threshold estimate for the cumulative DEE exposure was found at 150 μg/m(3)-years when extending the meta-analyses of the three studies by hockey-stick regression modelling (including the modified coefficients for Garshick et al. 2012). The data used by Vermeulen and colleagues led to the highest relative risk estimate across all sensitivity analyses performed. The lowest relative risk estimate was found after exclusion of the explorative study by Steenland et al. 1998 in a meta-regression analysis of Garshick et al. 2012 (modified), Silverman et al. 2012 (modified according to Crump et al. 2015) and Möhner et al. 2013. The meta-coefficient was estimated to be about 10-20 % of the main effect estimate in Vermeulen et al. 2014 in this analysis. The findings of Vermeulen et al. 2014 should not be used without reservations in any risk assessments. This is particularly true for the low end of the exposure scale.

Use of Nuclepore filters for ambient and workplace nanoparticle exposure assessment-Spherical particles

NASA Astrophysics Data System (ADS)

Chen, Sheng-Chieh; Wang, Jing; Fissan, Heinz; Pui, David Y. H.

2013-10-01

Nuclepore filter collection with subsequent electron microscopy analysis for nanoparticles was carried out to examine the feasibility of the method to assess the nanoparticle exposure. The number distribution of nanoparticles collected on the filter surface was counted visually and converted to the distribution in the air using existing filtration models for Nuclepore filters. To search for a proper model, this paper studied the overall penetrations of three different nanoparticles (PSL, Ag and NaCl), covering a wide range of particle sizes (20-800 nm) and densities (1.05-10.5 g cm-3), through Nuclepore filters with two different pore diameters (1 and 3 μm) and different face velocities (2-15 cm s-1). The data were compared with existing particle deposition models and modified models proposed by this study, which delivered different results because of different deposition processes considered. It was found that a parameter associated with flow condition and filter geometry (density of fluid medium, particle density, filtration face velocity, filter porosity and pore diameter) should be taken into account to verify the applicability of the models. The data of the overall penetration were in very good agreement with the properly applied models. A good agreement of filter surface collection between the validated model and the SEM analysis was obtained, indicating a correct nanoparticle number distribution in the air can be converted from the Nuclepore filter surface collection and this method can be applied for nanoparticle exposure assessment.

Effects of prenatal cocaine exposure on special education in school-aged children.

PubMed

Levine, Todd P; Liu, Jing; Das, Abhik; Lester, Barry; Lagasse, Linda; Shankaran, Seetha; Bada, Henrietta S; Bauer, Charles R; Higgins, Rosemary

2008-07-01

The objective of this study was to evaluate the effects of prenatal cocaine exposure on special education at age 7 with adjustment for covariates. As part of the prospective, longitudinal, multisite study of children with prenatal cocaine exposure (Maternal Lifestyle Study), school records were reviewed for 943 children at 7 years to determine involvement in special education outcomes: (1) individualized education plan; (2) special education conditions; (3) support services; (4) special education classes; and (5) speech and language services. Logistic regression was used to examine the effect of prenatal cocaine exposure on these outcomes with environmental, maternal, and infant medical variables as covariates, as well as with and without low child IQ. Complete data for each analysis model were available for 737 to 916 children. When controlling for covariates including low child IQ, prenatal cocaine exposure had a significant effect on individualized education plan. When low child IQ was not included in the model, prenatal cocaine exposure had a significant effect on support services. Male gender, low birth weight, white race, and low child IQ also predicted individualized education plan. Low birth weight and low child IQ were significant in all models. White race was also significant in speech and language services. Other covariate effects were model specific. When included in the models, low child IQ accounted for more of the variance and changed the significance of other covariates. Prenatal cocaine exposure increased the likelihood of receiving an individualized education plan and support services, with adjustment for covariates. Low birth weight and low child IQ increased the likelihood of all outcomes. The finding that white children were more likely to get an individualized education plan and speech and language services could indicate a greater advantage in getting educational resources for this population.

Comparing Dimensional Accuracy Between a Polyvinyl Chloride Skull and Its Virtually Constructed Counterpart

DTIC Science & Technology

2015-06-01

exposure settings…………………...26 Table 4. Kodak 9500 Cone Beam 3D System exposure settings…………..….27 Table 5. Average and statistical analysis results...42 Figure 6 Image of Mounted PVC Skull Model on the Kodak 9500……….…......43 Figure 7 Screen image of Reconstructed CBCT Digital...replica was taken with the Kodak 9500 Cone Beam 3D System. To create the digital dental models fifteen type IV maxillary dental casts were made on the

Exposure to Domestic Violence and Abuse: Evidence of Distinct Physical and Psychological Dimensions.

PubMed

Naughton, Catherine M; O'Donnell, Aisling T; Muldoon, Orla T

2017-05-01

Recent literature on exposure to domestic violence (DV) highlights the need for increased understanding of the dynamics of domestic violence and abuse (DVA). The current aims were to explore whether two separate dimensions, physical and psychological DVA, were evident in adult children's reports of their exposure to DVA in their family of origin, and whether these dimensions affected psychological well-being and perceived satisfaction with emotional support (hereafter referred to as social support satisfaction). Young adults ( N = 465, aged 17-25, 70% female) reported their experiences of DVA as perpetrated by their parents/caregivers, as well as psychological well-being and social support satisfaction, in an online survey. Using confirmatory factor analysis (CFA), we verified the presence of a two-factor model (physical and psychological DVA). Hierarchical linear regression analysis demonstrated the differing impact of these two factors: Specifically, although exposure to psychological DVA (domestic abuse [DA]) was related to reduced psychological well-being, there was no significant effect of exposure to physical DVA (DV). However, mediation analysis suggested the presence of a suppression effect; there was a magnification of the negative relationship between exposure to psychological DA and social support satisfaction when exposure to physical DV was accounted for. Although findings are preliminary, they provide strong evidence to support theoretical arguments regarding the need for future research to conceptualize exposure to DVA in terms of both physical and psychological dimensions. Our findings also highlight that to improve service response and provide effective interventions, it is essential to include exposure to psychological DA in risk assessments of such young adults.

Relationship between mediation analysis and the structured life course approach

PubMed Central

Howe, Laura D; Smith, Andrew D; Macdonald-Wallis, Corrie; Anderson, Emma L; Galobardes, Bruna; Lawlor, Debbie A; Ben-Shlomo, Yoav; Hardy, Rebecca; Cooper, Rachel; Tilling, Kate; Fraser, Abigail

2016-01-01

Abstract Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome). PMID:27681097

New developments in exposure assessment: the impact on the practice of health risk assessment and epidemiological studies.

PubMed

Nieuwenhuijsen, Mark; Paustenbach, Dennis; Duarte-Davidson, Raquel

2006-12-01

The field of exposure assessment has matured significantly over the past 10-15 years. Dozens of studies have measured the concentrations of numerous chemicals in many media to which humans are exposed. Others have catalogued the various exposure pathways and identified typical values which can be used in the exposure calculations for the general population such as amount of water or soil ingested per day or the percent of a chemical than can pass through the skin. In addition, studies of the duration of exposure for many tasks (e.g. showering, jogging, working in the office) have been conducted which allow for more general descriptions of the likely range of exposures. All of this information, as well as the development of new and better models (e.g. air dispersion or groundwater models), allow for better estimates of exposure. In addition to identifying better exposure factors, and better mathematical models for predicting the aerial distribution of chemicals, the conduct of simulation studies and dose-reconstruction studies can offer extraordinary opportunities for filling in data gaps regarding historical exposures which are critical to improving the power of epidemiology studies. The use of probabilistic techniques such as Monte Carlo analysis and Bayesian statistics have revolutionized the practice of exposure assessment and has greatly enhanced the quality of the risk characterization. Lastly, the field of epidemiology is about to undergo a sea change with respect to the exposure component because each year better environmental and exposure models, statistical techniques and new biological monitoring techniques are being introduced. This paper reviews these techniques and discusses where additional research is likely to pay a significant dividend. Exposure assessment techniques are now available which can significantly improve the quality of epidemiology and health risk assessment studies and vastly improve their usefulness. As more quantitative exposure components can now be incorporated into these studies, they can be better used to identify safe levels of exposure using customary risk assessment methodologies. Examples are drawn from both environmental and occupational studies illustrating how these techniques have been used to better understand exposure to specific chemicals. Some thoughts are also presented on what lessons have been learned about conducting exposure assessment for health risk assessments and epidemiological studies.

Traffic-Related Air Pollution and Childhood Asthma: Recent Advances and Remaining Gaps in the Exposure Assessment Methods.

PubMed

Khreis, Haneen; Nieuwenhuijsen, Mark J

2017-03-17

Background : Current levels of traffic-related air pollution (TRAP) are associated with the development of childhood asthma, although some inconsistencies and heterogeneity remain. An important part of the uncertainty in studies of TRAP-associated asthma originates from uncertainties in the TRAP exposure assessment and assignment methods. In this work, we aim to systematically review the exposure assessment methods used in the epidemiology of TRAP and childhood asthma, highlight recent advances, remaining research gaps and make suggestions for further research. Methods : We systematically reviewed epidemiological studies published up until 8 September 2016 and available in Embase, Ovid MEDLINE (R), and "Transport database". We included studies which examined the association between children's exposure to TRAP metrics and their risk of "asthma" incidence or lifetime prevalence, from birth to the age of 18 years old. Results : We found 42 studies which examined the associations between TRAP and subsequent childhood asthma incidence or lifetime prevalence, published since 1999. Land-use regression modelling was the most commonly used method and nitrogen dioxide (NO₂) was the most commonly used pollutant in the exposure assessments. Most studies estimated TRAP exposure at the residential address and only a few considered the participants' mobility. TRAP exposure was mostly assessed at the birth year and only a few studies considered different and/or multiple exposure time windows. We recommend that further work is needed including e.g., the use of new exposure metrics such as the composition of particulate matter, oxidative potential and ultra-fine particles, improved modelling e.g., by combining different exposure assessment models, including mobility of the participants, and systematically investigating different exposure time windows. Conclusions : Although our previous meta-analysis found statistically significant associations for various TRAP exposures and subsequent childhood asthma, further refinement of the exposure assessment may improve the risk estimates, and shed light on critical exposure time windows, putative agents, underlying mechanisms and drivers of heterogeneity.

Traffic-Related Air Pollution and Childhood Asthma: Recent Advances and Remaining Gaps in the Exposure Assessment Methods

PubMed Central

Khreis, Haneen; Nieuwenhuijsen, Mark J.

2017-01-01

Background: Current levels of traffic-related air pollution (TRAP) are associated with the development of childhood asthma, although some inconsistencies and heterogeneity remain. An important part of the uncertainty in studies of TRAP-associated asthma originates from uncertainties in the TRAP exposure assessment and assignment methods. In this work, we aim to systematically review the exposure assessment methods used in the epidemiology of TRAP and childhood asthma, highlight recent advances, remaining research gaps and make suggestions for further research. Methods: We systematically reviewed epidemiological studies published up until 8 September 2016 and available in Embase, Ovid MEDLINE (R), and “Transport database”. We included studies which examined the association between children’s exposure to TRAP metrics and their risk of “asthma” incidence or lifetime prevalence, from birth to the age of 18 years old. Results: We found 42 studies which examined the associations between TRAP and subsequent childhood asthma incidence or lifetime prevalence, published since 1999. Land-use regression modelling was the most commonly used method and nitrogen dioxide (NO2) was the most commonly used pollutant in the exposure assessments. Most studies estimated TRAP exposure at the residential address and only a few considered the participants’ mobility. TRAP exposure was mostly assessed at the birth year and only a few studies considered different and/or multiple exposure time windows. We recommend that further work is needed including e.g., the use of new exposure metrics such as the composition of particulate matter, oxidative potential and ultra-fine particles, improved modelling e.g., by combining different exposure assessment models, including mobility of the participants, and systematically investigating different exposure time windows. Conclusions: Although our previous meta-analysis found statistically significant associations for various TRAP exposures and subsequent childhood asthma, further refinement of the exposure assessment may improve the risk estimates, and shed light on critical exposure time windows, putative agents, underlying mechanisms and drivers of heterogeneity. PMID:28304360

Whole-Body Lifetime Occupational Lead Exposure and Risk of Parkinson’s Disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coon , Steven; Stark, Azadeh; Peterson, Edward

2006-12-01

We enrolled 121 PD patients and 414 age-, sex-, and race-, frequency-matched controls in a case–control study. As an indicator of chronic Pb exposure, we measured concentrations of tibial and calcaneal bone Pb stores using 109Cadmium excited K-series X-ray fluorescence. As an indicator of recent exposure, we measured blood Pb concentration. We collected occupational data on participants from 18 years of age until the age at enrollment, and an industrial hygienist determined the duration and intensity of environmental Pb exposure. We employed physiologically based pharmacokinetic modeling to combine these data, and we estimated whole-body lifetime Pb exposures for each individual.more » Logistic regression analysis produced estimates of PD risk by quartile of lifetime Pb exposure.« less

Determining Historical Pesticide Deposition on Cape Cod through Sediment Core Analysis:A Validation of GIS as An Exposure Assessment Tool

NASA Astrophysics Data System (ADS)

Feingold, B. J.; Benoit, G.; Rudel, R.

2006-12-01

Geographic Information Systems (GIS) has emerged as a powerful tool to assess current and historical exposure to environmental pollutants. GIS aids in the visualization and understanding of associations between exposure to contaminants and disease. This study is an example of the bridge between environmental science and public health and of how new technology such as GIS can be incorporated into these fields to strengthen both the research and the communication of scientific results. It attempts to validate a GIS-based aerial drift model which predicts the residential exposure to and boundaries of historical organochlorine pesticide (OCP) drift from applications on cranberry bogs, tree pest sprayings and others by analytically quantifying the historical pesticide deposition in a transect of lakes radiating from a distinct spray source. This model was previously used to assess historical residential exposure to OCPs in an environmental epidemiological case-control study of breast cancer incidence on Cape Cod, MA, where the incidence rate of the disease is significantly higher than in the rest of the state. The model's validation in this current study is essential to establishing its predictive ability and thus, its further use. Ground truthing of the model was done through the collection and analysis of sediment cores along a transect of five hydrologically independent kettle ponds radiating from a distinct OCP tree-pest spray area. Measurements of OCP concentrations, total carbon and total organic carbon were determined, and dating of the sediments was completed using 210Pb and verified using 137Cs. Each 50-cm core was sliced into 25 2- cm sections for the analyses, creating a fine-scale depositional history in each pond. Information gathered from each core allows for the determination of the extent and degree of dissipation of individual spray events of a known source area and determine how well the model fits the actual data.

Exposure of differentiated airway epithelial cells to volatile smoke in vitro.

PubMed

Beisswenger, Christoph; Platz, Juliane; Seifart, Carola; Vogelmeier, Claus; Bals, Robert

2004-01-01

Cigarette smoke (CS) is the predominant pathogenetic factor in the development of chronic bronchitis and chronic obstructive pulmonary disease. The knowledge about the cellular and molecular mechanisms underlying the smoke-induced inflammation in epithelial cells is limited. The aim of this study was to develop an in vitro model to monitor the effects of volatile CS on differentiated airway epithelial cells. The airway epithelial cell line MM-39 and primary human bronchial epithelial cells were cultivated as air-liquid interface cultures and exposed directly to volatile CS. We used two types of exposure models, one using ambient air, the other using humidified and warm air. Cytokine levels were measured by quantitative PCR and ELISA. Phosphorylation of p38 MAP kinase was assessed by Western blot analysis. To reduce the smoke-induced inflammation, antisense oligonucleotides directed against the p65 subunit of NF-kappaB were applied. Exposure of epithelia to cold and dry air resulted in a significant inflammatory response. In contrast, exposure to humidified warm air did not elicit a cellular response. Stimulation with CS resulted in upregulation of mRNA for IL-6 and IL-8 and protein release. Exposure to CS combined with heat-inactivated bacteria synergistically increased levels of the cytokines. Reactions of differentiated epithelial cells to smoke are mediated by the MAP kinase p38 and the transcription factor NF-kappaB. We developed an exposure model to examine the consequences of direct exposure of differentiated airway epithelial cells to volatile CS. The model enables to measure the cellular reactions to smoke exposure and to determine the outcome of therapeutic interventions. Copyright 2004 S. Karger AG, Basel

Association Between Cd Exposure and Risk of Prostate Cancer: A PRISMA-Compliant Systematic Review and Meta-Analysis.

PubMed

Ju-Kun, Song; Yuan, Dong-Bo; Rao, Hao-Fu; Chen, Tian-Fei; Luan, Bo-Shi; Xu, Xiao-Ming; Jiang, Fu-Neng; Zhong, Wei-De; Zhu, Jian-Guo

2016-02-01

Several observational studies on the association between Cd exposure and risk of prostate cancer have yielded inconsistent results. To address this issue, we conducted a meta-analysis to evaluate the correlation between Cd exposure and risk of prostate cancer.Relevant studies in PubMed and Embase databases were retrieved until October 2015. We compared the highest and lowest meta-analyses to quantitatively evaluate the relationship between Cd exposure and risk of prostate cancer. Summary estimates were obtained using a random-effects model.In the general population, high Cd exposure was not associated with increased prostate cancer (OR 1.21; 95% CI 0.91-1.64), whereas the combined standardized mortality ratio of the association between Cd exposure and risk of prostate cancer was 1.66 (95% CI 1.10-2.50) in populations exposed to occupational Cd. In addition, high D-Cd intake (OR 1.07; 95% CI 0.96-1.20) and U-Cd concentration (OR 0.86; 95% CI 0.48-1.55) among the general population was not related to the increased risk of prostate cancer. In the dose analysis, the summary relative risk was 1.07 (95% CI 0.73-1.57) for each 0.5 μg/g creatinine increase in U-Cd and 1.02 (95% CI 0.99-1.06) for each 10 μg/day increase of dietary Cd intake. However, compared with nonoccupational exposure, high occupational Cd exposure may be associated with the increased risk of prostate cancer.This meta-analysis suggests high Cd exposure as a risk factor for prostate cancer in occupational rather than nonoccupational populations. However, these results should be carefully interpreted because of the significant heterogeneity among studies. Additional large-scale and high-quality prospective studies are needed to confirm the association between Cd exposure and risk of prostate cancer.

Comparison of Ordinal and Nominal Classification Trees to Predict Ordinal Expert-Based Occupational Exposure Estimates in a Case–Control Study

PubMed Central

Wheeler, David C.; Archer, Kellie J.; Burstyn, Igor; Yu, Kai; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla; Silverman, Debra T.; Friesen, Melissa C.

2015-01-01

Objectives: To evaluate occupational exposures in case–control studies, exposure assessors typically review each job individually to assign exposure estimates. This process lacks transparency and does not provide a mechanism for recreating the decision rules in other studies. In our previous work, nominal (unordered categorical) classification trees (CTs) generally successfully predicted expert-assessed ordinal exposure estimates (i.e. none, low, medium, high) derived from occupational questionnaire responses, but room for improvement remained. Our objective was to determine if using recently developed ordinal CTs would improve the performance of nominal trees in predicting ordinal occupational diesel exhaust exposure estimates in a case–control study. Methods: We used one nominal and four ordinal CT methods to predict expert-assessed probability, intensity, and frequency estimates of occupational diesel exhaust exposure (each categorized as none, low, medium, or high) derived from questionnaire responses for the 14983 jobs in the New England Bladder Cancer Study. To replicate the common use of a single tree, we applied each method to a single sample of 70% of the jobs, using 15% to test and 15% to validate each method. To characterize variability in performance, we conducted a resampling analysis that repeated the sample draws 100 times. We evaluated agreement between the tree predictions and expert estimates using Somers’ d, which measures differences in terms of ordinal association between predicted and observed scores and can be interpreted similarly to a correlation coefficient. Results: From the resampling analysis, compared with the nominal tree, an ordinal CT method that used a quadratic misclassification function and controlled tree size based on total misclassification cost had a slightly better predictive performance that was statistically significant for the frequency metric (Somers’ d: nominal tree = 0.61; ordinal tree = 0.63) and similar performance for the probability (nominal = 0.65; ordinal = 0.66) and intensity (nominal = 0.65; ordinal = 0.65) metrics. The best ordinal CT predicted fewer cases of large disagreement with the expert assessments (i.e. no exposure predicted for a job with high exposure and vice versa) compared with the nominal tree across all of the exposure metrics. For example, the percent of jobs with expert-assigned high intensity of exposure that the model predicted as no exposure was 29% for the nominal tree and 22% for the best ordinal tree. Conclusions: The overall agreements were similar across CT models; however, the use of ordinal models reduced the magnitude of the discrepancy when disagreements occurred. As the best performing model can vary by situation, researchers should consider evaluating multiple CT methods to maximize the predictive performance within their data. PMID:25433003

Evaluating cardiac risk: exposure response analysis in early clinical drug development.

PubMed

Grenier, Julie; Paglialunga, Sabina; Morimoto, Bruce H; Lester, Robert M

2018-01-01

The assessment of a drug's cardiac liability has undergone considerable metamorphosis by regulators since International Council for Harmonization of Technical Requirement for Pharmaceuticals for Human Use E14 guideline was introduced in 2005. Drug developers now have a choice in how proarrhythmia risk can be evaluated; the options include a dedicated thorough QT (TQT) study or exposure response (ER) modeling of intensive electrocardiogram (ECG) captured in early clinical development. The alternative approach of ER modeling was incorporated into a guidance document in 2015 as a primary analysis tool which could be utilized in early phase dose escalation studies as an option to perform a dedicated TQT trial. This review will describe the current state of ER modeling of intensive ECG data collected during early clinical drug development; the requirements with regard to the use of a positive control; and address the challenges and opportunities of this alternative approach to assessing QT liability.

Long-term air pollution and traffic noise exposures and cognitive function:A cross-sectional analysis of the Heinz Nixdorf Recall study.

PubMed

Tzivian, Lilian; Dlugaj, Martha; Winkler, Angela; Hennig, Frauke; Fuks, Kateryna; Sugiri, Dorothee; Schikowski, Tamara; Jakobs, Hermann; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Hoffmann, Barbara; Weimar, Christian

2016-01-01

Investigations of adverse effects of air pollution (AP) and ambient noise on cognitive functions are apparently scarce, and findings seem to be inconsistent. The aim of this study was to examine the associations of long-term exposure to AP and traffic noise with cognitive performance. At the second examination of the population-based Heinz Nixdorf Recall study (2006-2008), cognitive performance was evaluated in 4086 participants. Long-term residential exposure to size-specific particulate matter (PM) and nitrogen oxides (NOx) with land use regression, to and traffic noise (weighted 24-h (L DEN ) and nighttime (L NIGHT ) means), was assessed according to the European Union (EU) Directive 2002/49/EC. Multiple regression models were calculated for the relationship of environmental exposures with a global cognitive score (GCS) and in five cognitive subtests, using single- and two-exposure models. In fully adjusted models, several AP metrics were negatively associated with four of five subtests and with GCS. For example, an interquartile range increase in PM 2.5 was correlated with verbal fluency, labyrinth test, and immediate and delayed verbal recall. A 10 dB(A) elevation in L DEN and L NIGHT was associated with GCS. Similar but not significant associations were found for the cognitive subtests. In two-exposure models including noise and air pollution simultaneously, the associations did not change markedly for air pollution, but attenuated numerically for noise. Long-term exposures to AP and traffic noise are negatively correlated with subtests related to memory and executive functions. There appears to be little evidence for mutual confounding.

Neurobehavioral deficits, diseases, and associated costs of exposure to endocrine-disrupting chemicals in the European Union.

PubMed

Bellanger, Martine; Demeneix, Barbara; Grandjean, Philippe; Zoeller, R Thomas; Trasande, Leonardo

2015-04-01

Epidemiological studies and animal models demonstrate that endocrine-disrupting chemicals (EDCs) contribute to cognitive deficits and neurodevelopmental disabilities. The objective was to estimate neurodevelopmental disability and associated costs that can be reasonably attributed to EDC exposure in the European Union. An expert panel applied a weight-of-evidence characterization adapted from the Intergovernmental Panel on Climate Change. Exposure-response relationships and reference levels were evaluated for relevant EDCs, and biomarker data were organized from peer-reviewed studies to represent European exposure and approximate burden of disease. Cost estimation as of 2010 utilized lifetime economic productivity estimates, lifetime cost estimates for autism spectrum disorder, and annual costs for attention-deficit hyperactivity disorder. Setting, Patients and Participants, and Intervention: Cost estimation was carried out from a societal perspective, ie, including direct costs (eg, treatment costs) and indirect costs such as productivity loss. The panel identified a 70-100% probability that polybrominated diphenyl ether and organophosphate exposures contribute to IQ loss in the European population. Polybrominated diphenyl ether exposures were associated with 873,000 (sensitivity analysis, 148,000 to 2.02 million) lost IQ points and 3290 (sensitivity analysis, 3290 to 8080) cases of intellectual disability, at costs of €9.59 billion (sensitivity analysis, €1.58 billion to €22.4 billion). Organophosphate exposures were associated with 13.0 million (sensitivity analysis, 4.24 million to 17.1 million) lost IQ points and 59 300 (sensitivity analysis, 16,500 to 84,400) cases of intellectual disability, at costs of €146 billion (sensitivity analysis, €46.8 billion to €194 billion). Autism spectrum disorder causation by multiple EDCs was assigned a 20-39% probability, with 316 (sensitivity analysis, 126-631) attributable cases at a cost of €199 million (sensitivity analysis, €79.7 million to €399 million). Attention-deficit hyperactivity disorder causation by multiple EDCs was assigned a 20-69% probability, with 19 300 to 31 200 attributable cases at a cost of €1.21 billion to €2.86 billion. EDC exposures in Europe contribute substantially to neurobehavioral deficits and disease, with a high probability of >€150 billion costs/year. These results emphasize the advantages of controlling EDC exposure.

Diffusion Tensor Imaging Reveals White Matter Injury in a Rat Model of Repetitive Blast-Induced Traumatic Brain Injury

PubMed Central

Calabrese, Evan; Du, Fu; Garman, Robert H.; Johnson, G. Allan; Riccio, Cory; Tong, Lawrence C.

2014-01-01

Abstract Blast-induced traumatic brain injury (bTBI) is one of the most common combat-related injuries seen in U.S. military personnel, yet relatively little is known about the underlying mechanisms of injury. In particular, the effects of the primary blast pressure wave are poorly understood. Animal models have proven invaluable for the study of primary bTBI, because it rarely occurs in isolation in human subjects. Even less is known about the effects of repeated primary blast wave exposure, but existing data suggest cumulative increases in brain damage with a second blast. MRI and, in particular, diffusion tensor imaging (DTI), have become important tools for assessing bTBI in both clinical and preclinical settings. Computational statistical methods such as voxelwise analysis have shown promise in localizing and quantifying bTBI throughout the brain. In this study, we use voxelwise analysis of DTI to quantify white matter injury in a rat model of repetitive primary blast exposure. Our results show a significant increase in microstructural damage with a second blast exposure, suggesting that primary bTBI may sensitize the brain to subsequent injury. PMID:24392843

Exposure to UV radiation and risk of Hodgkin lymphoma: a pooled analysis

PubMed Central

Glaser, Sally L.; Schupp, Clayton W.; Ekström Smedby, Karin; de Sanjosé, Silvia; Kane, Eleanor; Melbye, Mads; Forétova, Lenka; Maynadié, Marc; Staines, Anthony; Becker, Nikolaus; Nieters, Alexandra; Brennan, Paul; Boffetta, Paolo; Cocco, Pierluigi; Glimelius, Ingrid; Clavel, Jacqueline; Hjalgrim, Henrik; Chang, Ellen T.

2013-01-01

Ultraviolet radiation (UVR) exposure has been inversely associated with Hodgkin lymphoma (HL) risk, but only inconsistently, only in a few studies, and without attention to HL heterogeneity. We conducted a pooled analysis of HL risk focusing on type and timing of UVR exposure and on disease subtypes by age, histology, and tumor-cell Epstein-Barr virus (EBV) status. Four case-control studies contributed 1320 HL cases and 6381 controls. We estimated lifetime, adulthood, and childhood UVR exposure and history of sunburn and sunlamp use. We used 2-stage estimation with mixed-effects models and weighted pooled effect estimates by inverse marginal variances. We observed statistically significant inverse associations with HL risk for UVR exposures during childhood and adulthood, sunburn history, and sunlamp use, but we found no significant dose-response relationships. Risks were significant only for EBV-positive HL (pooled odds ratio, 0.56; 95% confidence interval, 0.35 to 0.91 for the highest overall UVR exposure category), with a significant linear trend for overall exposure (P = .03). Pooled relative risk estimates were not heterogeneous across studies. Increased UVR exposure may protect against HL, particularly EBV-positive HL. Plausible mechanisms involving UVR induction of regulatory T cells or the cellular DNA damage response suggest opportunities for new prevention targets. PMID:24016459

Sunlight exposure and cardiovascular risk factors in the REGARDS study: a cross-sectional split-sample analysis

PubMed Central

2014-01-01

Background Previous research has suggested that vitamin D and sunlight are related to cardiovascular outcomes, but associations between sunlight and risk factors have not been investigated. We examined whether increased sunlight exposure was related to improved cardiovascular risk factor status. Methods Residential histories merged with satellite, ground monitor, and model reanalysis data were used to determine previous-year sunlight radiation exposure for 17,773 black and white participants aged 45+ from the US. Exploratory and confirmatory analyses were performed by randomly dividing the sample into halves. Logistic regression models were used to examine relationships with cardiovascular risk factors. Results The lowest, compared to the highest quartile of insolation exposure was associated with lower high-density lipoprotein levels in adjusted exploratory (−2.7 mg/dL [95% confidence interval: −4.2, −1.2]) and confirmatory (−1.5 mg/dL [95% confidence interval: −3.0, −0.1]) models. The lowest, compared to the highest quartile of insolation exposure was associated with higher systolic blood pressure levels in unadjusted exploratory and confirmatory, as well as the adjusted exploratory model (2.3 mmHg [95% confidence interval: 0.8, 3.8]), but not the adjusted confirmatory model (1.6 mg/dL [95% confidence interval: −0.5, 3.7]). Conclusions The results of this study suggest that lower long-term sunlight exposure has an association with lower high-density lipoprotein levels. However, all associations were weak, thus it is not known if insolation may affect cardiovascular outcomes through these risk factors. PMID:24946776

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS*

PubMed Central

Keller, Joshua P.; Drton, Mathias; Larson, Timothy; Kaufman, Joel D.; Sandler, Dale P.; Szpiro, Adam A.

2017-01-01

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP. PMID:28572869

A meta-analysis of bladder cancer and diesel exhaust exposure.

PubMed

Boffetta, P; Silverman, D T

2001-01-01

The aim of this study is to review and summarize the available epidemiologic studies of bladder cancer and occupational exposure to diesel exhaust. We retrieved relevant studies and abstracted their characteristics and results. We assessed the heterogeneity of the results to decide whether to perform a fixed-effects model meta-analysis. We identified 35 relevant studies. No overall meta-analysis was performed because of heterogeneity in results. Results of railroad workers (N = 14) suggested an increased occurrence of bladder cancer, but we did not conduct a meta-analysis. The summary relative risk (RR) among truck drivers was 1.17 (95% confidence interval [CI] = 1.06-1.29, 15 studies) and that among bus drivers was 1.33 (95% CI = 1.22-1.45, 10 studies). Ten studies considered diesel exhaust exposure based on a job exposure matrix or a similar approach; the summary RR for these studies was 1.13 (95% CI = 1.00-1.27). A positive dose-response relation was suggested by 10 of the 12 studies that provided relevant information. The summary RR for high diesel exposure was 1.44 (95% CI = 1.18-1.76). There was some evidence of publication bias, however, with a lack of small studies with null or negative results. Our review suggests that exposure to diesel exhaust may increase the occurrence of bladder cancer, but the effects of misclassification, publication bias, and confounding cannot be fully taken into account.

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and themore » volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. In conclusion, given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted.« less

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

DOE PAGES

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

2016-12-08

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and themore » volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. In conclusion, given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted.« less

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

PubMed Central

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

2016-01-01

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and the volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. Given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted. PMID:27930709

Meta-Analysis of Lead (Pb) in Multiple Environmental Media in the United States

EPA Science Inventory

Introduction: The U.S. Environmental Protection Agency, Office of Research and Development, conducts probabilistic multimedia lead (Pb) exposure modeling to inform the development of health-based benchmarks for Pb in the environment. For this modeling, robust Pb concentration dat...

76 FR 18895 - Hexythiazox; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-06

... Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS), the estimated drinking water concentration... Classification System (NAICS) codes have been provided to assist you and others in determining whether this.... Based upon review of the data supporting the petition, EPA has revised the proposed tolerance levels for...

78 FR 25396 - Glyphosate; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-01

.../water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS.... The following list of North American Industrial Classification System (NAICS) codes is not intended to... the data supporting the petition, EPA has modified the levels at which tolerances are being...

DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

EPA Science Inventory

The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

Passive smoking and cooking oil fumes (COF) may modify the association between tea consumption and oral cancer in Chinese women.

PubMed

Chen, Fa; He, Baochang; Hu, Zhijian; Huang, Jiangfeng; Liu, Fangping; Yan, Lingjun; Lin, Zheng; Zheng, Xiaoyan; Lin, Lisong; Zhang, Zuofeng; Cai, Lin

2016-05-01

To evaluate the confounding effects of passive smoking and COF exposure on association between tea and oral cancer in Chinese women. A case-control study including 207 female oral cancer cases and 480 age-matched controls was performed in Fujian, China. Data were collected with a structured questionnaire by face-to-face interviews. The effects of tea consumption on oral cancer were, respectively, adjusted for Model-1 and Model-2 using logistic regression analysis. Model-1 did not adjusted for passive smoking and COF; Model-2 included the variables in Model-1, passive smoking and COF. Tea consumption was associated with a decreased risk of oral cancer in females: The OR was 0.498 (95 % CI 0.312-0.795) for Model-1 and 0.565 (95 % CI 0.352-0.907) for Model-2. The ORs for all the categories of tea consumption estimated by Model-2 were slightly higher than Model-1. When stratified by passive smoking, the statistically significant association between tea drinking and oral cancer was only emerged in non-passive smoking women. Stratification by COF found tea drinking was still associated with a decreased risk of oral cancer for women who have light-COF exposure, but an increased risk for those who subjected to heavy exposure. A negative, multiplicative interaction was found between tea consumption and COF exposure for oral cancer, but not found between tea consumption and passive smoking. Tea consumption reduces the risk of oral cancer in Chinese women, but this effect is modified by the carcinogenic effects of passive smoking and COF exposure.

Estimating trajectories of energy intake through childhood and adolescence using linear-spline multilevel models.

PubMed

Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D

2013-07-01

Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.

Oxidative Damage Induced by Arsenic in Mice or Rats: A Systematic Review and Meta-Analysis.

PubMed

Xu, Mengchuan; Rui, Dongsheng; Yan, Yizhong; Xu, Shangzhi; Niu, Qiang; Feng, Gangling; Wang, Yan; Li, Shugang; Jing, Mingxia

2017-03-01

In this meta-analysis, studies reporting arsenic-induced oxidative damage in mouse models were systematically evaluated to provide a scientific understanding of oxidative stress mechanisms associated with arsenic poisoning. Fifty-eight relevant peer-reviewed publications were identified through exhaustive database searching. Oxidative stress indexes assessed included superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), glutathione peroxidase (GPx), glutathione-s-transferase (GST), glutathione reductase (GR), oxidized glutathione (GSSG), malondialdehyde (MDA), and reactive oxygen species (ROS). Our meta-analysis showed that arsenic exposure generally suppressed measured levels of the antioxidants, SOD, CAT, GSH, GPx, GST, and GR, but increased levels of the oxidants, GSSG, MDA, and ROS. Arsenic valence was important and GR and MDA levels increased to a significantly (P < 0.05) greater extent upon exposure to As 3+ than to As 5+ . Other factors that contributed to a greater overall oxidative effect from arsenic exposure included intervention time, intervention method, dosage, age of animals, and the sample source from which the indexes were estimated. Our meta-analysis effectively summarized a wide range of studies and detected a positive relationship between arsenic exposure and oxidative damage. These data provide a scientific basis for the prevention and treatment of arsenic poisoning.

Factors associated with secondhand smoke exposure in different settings: Results from the German Health Update (GEDA) 2012.

PubMed

Fischer, Florian; Kraemer, Alexander

2016-04-14

The ubiquity of secondhand smoke (SHS) exposure at home or in private establishments, workplaces and public areas poses several challenges for the reduction of SHS exposure. This study aimed to describe the prevalence of SHS exposure in Germany and key factors associated with exposure. Results were also differentiated by place of exposure. A secondary data analysis based on the public use file of the German Health Update 2012 was conducted (n = 13,933). Only non-smokers were included in the analysis. In a multivariable logistic regression model the factors associated with SHS exposure were calculated. In addition, a further set of multivariable logistic regressions were calculated for factors associated with the place of SHS exposure (workplace, at home, bars/discotheques, restaurants, at the house of a friend). More than a quarter of non-smoking study participants were exposed to SHS. The main area of exposure was the workplace (40.9 %). The multivariable logistic regression indicated young age as the most important factor associated with SHS exposure. The odds for SHS exposure was higher in men than in women. The likelihood of SHS exposure decreased with higher education. SHS exposure and the associated factors varied between different places of exposure. Despite several actions to protect non-smokers which were implemented in Germany during the past years, SHS exposure still remains a relevant risk factor at a population level. According to the results of this study, particularly the workplace and other public places such as bars and discotheques have to be taken into account for the development of strategies to reduce SHS exposure.

National and School Policies on Restrictions of Teacher Smoking: A Multilevel Analysis of Student Exposure to Teacher Smoking in Seven European Countries

ERIC Educational Resources Information Center

Wold, Bente; Torsheim, Torbjorn; Currie, Candace; Roberts, Chris

2004-01-01

The paper examines the association between restrictions on teacher tobacco smoking at school and student exposure to teachers who smoke during school hours. The data are taken from a European Commission-funded study "Control of Adolescent Smoking" (the CAS study) in seven European countries. Multilevel modelling analyses were applied to…

Exposure-response analysis and risk assessment for lung cancer in relationship to silica exposure: a 44-year cohort study of 34,018 workers.

PubMed

Liu, Yuewei; Steenland, Kyle; Rong, Yi; Hnizdo, Eva; Huang, Xiji; Zhang, Hai; Shi, Tingming; Sun, Yi; Wu, Tangchun; Chen, Weihong

2013-11-01

Crystalline silica has been classified as a human carcinogen by the International Agency for Research on Cancer (Lyon, France); however, few previous studies have provided quantitative data on silica exposure, silicosis, and/or smoking. We investigated a cohort in China (in 1960-2003) of 34,018 workers without exposure to carcinogenic confounders. Cumulative silica exposure was estimated by linking a job-exposure matrix to work history. Cox proportional hazards model was used to conduct exposure-response analysis and risk assessment. During a mean 34.5-year follow-up, 546 lung cancer deaths were identified. Categorical analyses by quartiles of cumulative silica exposure (using a 25-year lag) yielded hazard ratios of 1.26, 1.54, 1.68, and 1.70, respectively, compared with the unexposed group. Monotonic exposure-response trends were observed among nonsilicotics (P for trend < 0.001). Analyses using splines showed similar trends. The joint effect of silica and smoking was more than additive and close to multiplicative. For workers exposed from ages 20 to 65 years at 0.1 mg/m(3) of silica exposure, the estimated excess lifetime risk (through age 75 years) was 0.51%. These findings confirm silica as a human carcinogen and suggest that current exposure limits in many countries might be insufficient to protect workers from lung cancer. They also indicate that smoking cessation could help reduce lung cancer risk for silica-exposed individuals.

Modelling Short-Term Maximum Individual Exposure from Airborne Hazardous Releases in Urban Environments. Part ΙI: Validation of a Deterministic Model with Wind Tunnel Experimental Data.

PubMed

Efthimiou, George C; Bartzis, John G; Berbekar, Eva; Hertwig, Denise; Harms, Frank; Leitl, Bernd

2015-06-26

The capability to predict short-term maximum individual exposure is very important for several applications including, for example, deliberate/accidental release of hazardous substances, odour fluctuations or material flammability level exceedance. Recently, authors have proposed a simple approach relating maximum individual exposure to parameters such as the fluctuation intensity and the concentration integral time scale. In the first part of this study (Part I), the methodology was validated against field measurements, which are governed by the natural variability of atmospheric boundary conditions. In Part II of this study, an in-depth validation of the approach is performed using reference data recorded under truly stationary and well documented flow conditions. For this reason, a boundary-layer wind-tunnel experiment was used. The experimental dataset includes 196 time-resolved concentration measurements which detect the dispersion from a continuous point source within an urban model of semi-idealized complexity. The data analysis allowed the improvement of an important model parameter. The model performed very well in predicting the maximum individual exposure, presenting a factor of two of observations equal to 95%. For large time intervals, an exponential correction term has been introduced in the model based on the experimental observations. The new model is capable of predicting all time intervals giving an overall factor of two of observations equal to 100%.

Simulating cholinesterase inhibition in birds caused by dietary insecticide exposure

USGS Publications Warehouse

Corson, M.S.; Mora, M.A.; Grant, W.E.

1998-01-01

We describe a stochastic simulation model that simulates avian foraging in an agricultural landscape to evaluate factors affecting dietary insecticide exposure and to predict post-exposure cholinesterase (ChE) inhibition. To evaluate the model, we simulated published field studies and found that model predictions of insecticide decay and ChE inhibition reasonably approximated most observed results. Sensitivity analysis suggested that foraging location usually influenced ChE inhibition more than diet preferences or daily intake rate. Although organophosphorus insecticides usually caused greater inhibition than carbamate insecticides, insecticide toxicity appeared only moderately important. When we simulated impact of heavy insecticide applications during breeding seasons of 15 wild bird species, mean maximum ChE inhibition in most species exceeded 20% at some point. At this level of inhibition, birds may experience nausea and/or may exhibit minor behavioral changes. Simulated risk peaked in April–May and August–September and was lowest in July. ChE inhibition increased with proportion of vegetation in the diet. This model, and ones like it, may help predict insecticide exposure of and sublethal ChE inhibition in grassland animals, thereby reducing dependence of ecological risk assessments on field studies alone.

Model-Based Dose Selection for Intravaginal Ring Formulations Releasing Anastrozole and Levonorgestrel Intended for the Treatment of Endometriosis Symptoms.

PubMed

Reinecke, Isabel; Schultze-Mosgau, Marcus-Hillert; Nave, Rüdiger; Schmitz, Heinz; Ploeger, Bart A

2017-05-01

Pharmacokinetics (PK) of anastrozole (ATZ) and levonorgestrel (LNG) released from an intravaginal ring (IVR) intended to treat endometriosis symptoms were characterized, and the exposure-response relationship focusing on the development of large ovarian follicle-like structures was investigated by modeling and simulation to support dose selection for further studies. A population PK analysis and simulations were performed for ATZ and LNG based on clinical phase 1 study data from 66 healthy women. A PK/PD model was developed to predict the probability of a maximum follicle size ≥30 mm and the potential contribution of ATZ beside the known LNG effects. Population PK models for ATZ and LNG were established where the interaction of LNG with sex hormone-binding globulin (SHBG) as well as a stimulating effect of estradiol on SHBG were considered. Furthermore, simulations showed that doses of 40 μg/d LNG combined with 300, 600, or 1050 μg/d ATZ reached anticipated exposure levels for both drugs, facilitating selection of ATZ and LNG doses in the phase 2 dose-finding study. The main driver for the effect on maximum follicle size appears to be unbound LNG exposure. A 50% probability of maximum follicle size ≥30 mm was estimated for 40 μg/d LNG based on the exposure-response analysis. ATZ in the dose range investigated does not increase the risk for ovarian cysts as occurs with LNG at a dose that does not inhibit ovulation. © 2016, The American College of Clinical Pharmacology.

Investigating the American Time Use Survey from an exposure modeling perspective.

PubMed

George, Barbara Jane; McCurdy, Thomas

2011-01-01

This paper describes an evaluation of the US Bureau of Labor Statistics' American Time Use Survey (ATUS) for potential use in modeling human exposures to environmental pollutants. The ATUS is a large, on-going, cross-sectional survey of where Americans spend time and what activities they undertake in those locations. The data are reported as a series of sequential activities over a 24-h time period--a "diary day"--starting at 0400 hours. Between 12,000 and 13,000 surveys are obtained each year and the Bureau has plans to continue ATUS for the foreseeable future. The ATUS already has about 73,000 diary days of data, more than twice as many as that which currently exists in the US Environmental Protection Agency's (EPA) "Consolidated Human Activity Database" (CHAD) that the Agency uses for exposure modeling purposes. There are limitations for using ATUS in modeling human exposures to environmental pollutants. The ATUS does not report the location for a number of activities regarded as "personal." For 2006, personal activities with missing location information totaled 572 min/day, on average, for survey participants: about 40% of their day. Another limitation is that ATUS does not distinguish between indoor and outdoor activities at home, two of the traditional locational demarcations used in human exposure modeling. This lack of information affects exposure estimates to both indoor and outdoor air pollutants and potentially affects non-dietary ingestion estimates for children, which can vary widely depending on whether or not a child is indoors. Finally, a detailed analysis of the work travel activity in a subsample from ATUS 2006 indicates that the coding scheme is not fully consistent with a CHAD-based exposure modeling approach. For ATUS respondents in this subsample who reported work as an activity, roughly 48% of their days were missing work travel at one or both ends of the work shift or reported within work-shift travel inconsistently. An extensive effort would be needed to recode work travel data from ATUS for EPA's exposure modeling purposes.

Integrated Population Pharmacokinetic Analysis of Rivaroxaban Across Multiple Patient Populations

PubMed Central

Zhang, Liping; Frede, Matthias; Kubitza, Dagmar; Mueck, Wolfgang; Schmidt, Stephan; Solms, Alexander; Yan, Xiaoyu; Garmann, Dirk

2018-01-01

The population pharmacokinetics (PK) of rivaroxaban have been evaluated in several population‐specific models. We developed an integrated population PK model using pooled data from 4,918 patients in 7 clinical trials across all approved indications. Effects of gender, age, and weight on apparent clearance (CL/F) and apparent volume of distribution (V/F), renal function, and comedication on CL/F, and relative bioavailability as a function of dose (F) were analyzed. Virtual subpopulations for exposure simulations were defined by age, creatinine clearance (CrCL) and body mass index (BMI). Rivaroxaban PK were adequately described by a one‐compartment disposition model with a first‐order absorption rate constant. Significant effects of CrCL, use of comedications, and study population on CL/F, age, weight, and gender on V/F, and dose on F were identified. CrCL had a modest influence on exposure, whereas age and BMI had a minor influence. The model was suitable to predict rivaroxaban exposure in patient subgroups of special interest. PMID:29660785

Preliminary synchrotron analysis of lead in hair from a lead smelter worker

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, R.R.; Kempson, I.M.; Naftel, S.J.

2008-06-09

Synchrotron X-ray fluorescence has been used to study the distribution of lead in a hair sample collected from a lead smelter worker. A mathematical model was used to imitate the transverse scan signal based on the analysis volume and concentration profiles. The results suggest that the Pb originates both from ingestion and environmental exposure, however direct deposition from the environment is the more important source of hair lead. The model could apply equally to any other analysis involving a thin cylindrical sample.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Intention to comply with post-exposure management among nurses exposed to blood and body fluids in Taiwan: application of the theory of planned behaviour.

PubMed

Ko, N-Y; Yeh, S-H; Tsay, S-L; Ma, H-J; Chen, C-H; Pan, S-M; Feng, M-C; Chiang, M-C; Lee, Y-W; Chang, L-H; Jang, J-F

2011-04-01

Nurses are at significant risk from occupationally acquired bloodborne virus infections following a needlestick and sharps injury. This study aimed to apply the theory of planned behaviour (TPB) to predict nurses' intention to comply with occupational post-exposure management. A cross-sectional survey was applied to select registered nurses who worked in human immunodeficiency virus (HIV)-designated hospitals. An anonymous, self-administered questionnaire based on the TPB was distributed to 1630 nurses and 1134 (69.5%) questionnaires were returned. From these, a total of 802 nurses (71%) reported blood and body fluid exposure incidents during 2003-2005 and this group was used for analysis. Only 44.6% of the 121 exposed nurses who were prescribed post-exposure prophylaxis (PEP) by infectious disease doctors returned to the clinic for interim monitoring, and only 56.6% of exposed nurses confirmed their final serology status. Structural equation modelling was used to test the TPB indicating perceived behavioural control (the perception of the difficulty or ease of PEP management, β=0.58), subjective norm (the perception of social pressure to adhere to PEP, β=0.15), and attitudes (β=0.12) were significant direct effects on nurses' intention to comply with post-exposure management. The hypothesised model test indicated that the model fitted with the expected relationships and directions of theoretical constructs [χ(2) (14, N=802)=23.14, P=0.057, GFI=0.987, RMSEA=0.039]. The TPB model constructs accounted for 54% of the variance in nurses' intention to comply with post-exposure management. The TPB is an appropriate model for predicting nurses' intention to comply with post-exposure management. Healthcare facilities should have policies to decrease the inconvenience of follow-up to encourage nurses to comply with post-exposure management. Copyright © 2010 the Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Preclinical Mouse Models of Neurofibromatosis

DTIC Science & Technology

2005-11-01

and NF2-deficient human cells and in cells from Nf1 and Nf2 mutant mice. Genetic analysis of human and murine tumors has provided compelling...lethal myeloproliferative disorder (MPD) characterized by over-production of infiltrative myeloid cells (13). JMML has been modeled in mice by...tumor development for 18 months after exposure. Pathologic analysis was performed on 91% of the Shannon, K.M. 11 study cohort, including 95 of 104

Anthropometry-corrected exposure modeling as a method to improve trunk posture assessment with a single inclinometer.

PubMed

Van Driel, Robin; Trask, Catherine; Johnson, Peter W; Callaghan, Jack P; Koehoorn, Mieke; Teschke, Kay

2013-01-01

Measuring trunk posture in the workplace commonly involves subjective observation or self-report methods or the use of costly and time-consuming motion analysis systems (current gold standard). This work compared trunk inclination measurements using a simple data-logging inclinometer with trunk flexion measurements using a motion analysis system, and evaluated adding measures of subject anthropometry to exposure prediction models to improve the agreement between the two methods. Simulated lifting tasks (n=36) were performed by eight participants, and trunk postures were simultaneously measured with each method. There were significant differences between the two methods, with the inclinometer initially explaining 47% of the variance in the motion analysis measurements. However, adding one key anthropometric parameter (lower arm length) to the inclinometer-based trunk flexion prediction model reduced the differences between the two systems and accounted for 79% of the motion analysis method's variance. Although caution must be applied when generalizing lower-arm length as a correction factor, the overall strategy of anthropometric modeling is a novel contribution. In this lifting-based study, by accounting for subject anthropometry, a single, simple data-logging inclinometer shows promise for trunk posture measurement and may have utility in larger-scale field studies where similar types of tasks are performed.

Validation of Methods to Control for Immortal Time Bias in a Pharmacoepidemiologic Analysis of Renin–Angiotensin System Inhibitors in Type 2 Diabetes

PubMed Central

Yang, Xilin; Kong, Alice PS; Luk, Andrea OY; Ozaki, Risa; Ko, Gary TC; Ma, Ronald CW; Chan, Juliana CN; So, Wing Yee

2014-01-01

Background Pharmacoepidemiologic analysis can confirm whether drug efficacy in a randomized controlled trial (RCT) translates to effectiveness in real settings. We examined methods used to control for immortal time bias in an analysis of renin–angiotensin system (RAS) inhibitors as the reference cardioprotective drug. Methods We analyzed data from 3928 patients with type 2 diabetes who were recruited into the Hong Kong Diabetes Registry between 1996 and 2005 and followed up to July 30, 2005. Different Cox models were used to obtain hazard ratios (HRs) for cardiovascular disease (CVD) associated with RAS inhibitors. These HRs were then compared to the HR of 0.92 reported in a recent meta-analysis of RCTs. Results During a median follow-up period of 5.45 years, 7.23% (n = 284) patients developed CVD and 38.7% (n = 1519) were started on RAS inhibitors, with 39.1% of immortal time among the users. In multivariable analysis, time-dependent drug-exposure Cox models and Cox models that moved immortal time from users to nonusers both severely inflated the HR, and time-fixed models that included immortal time deflated the HR. Use of time-fixed Cox models that excluded immortal time resulted in a HR of only 0.89 (95% CI, 0.68–1.17) for CVD associated with RAS inhibitors, which is closer to the values reported in RCTs. Conclusions In pharmacoepidemiologic analysis, time-dependent drug exposure models and models that move immortal time from users to nonusers may introduce substantial bias in investigations of the effects of RAS inhibitors on CVD in type 2 diabetes. PMID:24747198

Evaluation of workplace exposure to respirable crystalline silica in Italy

PubMed Central

Scarselli, Alberto; Corfiati, Marisa; Marzio, Davide Di; Iavicoli, Sergio

2014-01-01

Background: Crystalline silica is a human carcinogen and its use is widespread among construction, mining, foundries, and other manufacturing industries. Purpose: To evaluate occupational exposure to crystalline silica in Italy. Methods: Data were collected from exposure registries and descriptive statistics were calculated for exposure-related variables. The number of potentially exposed workers was estimated in a subset of industrial sectors. Linear mixed model analysis was performed to determine factors affecting the exposure level. Results: We found 1387 cases of crystalline silica exposure between 1996 and 2012. Exposure was most common in construction work (AM = 0.057 mg/m3, N = 505), and among miners and quarry workers (AM = 0.048 mg/m3, N = 238). We estimated that 41 643 workers were at risk of exposure in the selected industrial sectors during the same period. Conclusions: This study identified high-risk sectors for occupational exposure to crystalline silica, which can help guide targeted dust control interventions and health promotion campaigns in the workplace. PMID:25078346

Evaluation of workplace exposure to respirable crystalline silica in Italy.

PubMed

Scarselli, Alberto; Corfiati, Marisa; Marzio, Davide Di; Iavicoli, Sergio

2014-10-01

Crystalline silica is a human carcinogen and its use is widespread among construction, mining, foundries, and other manufacturing industries. To evaluate occupational exposure to crystalline silica in Italy. Data were collected from exposure registries and descriptive statistics were calculated for exposure-related variables. The number of potentially exposed workers was estimated in a subset of industrial sectors. Linear mixed model analysis was performed to determine factors affecting the exposure level. We found 1387 cases of crystalline silica exposure between 1996 and 2012. Exposure was most common in construction work (AM = 0·057 mg/m(3), N = 505), and among miners and quarry workers (AM = 0·048 mg/m(3), N = 238). We estimated that 41 643 workers were at risk of exposure in the selected industrial sectors during the same period. This study identified high-risk sectors for occupational exposure to crystalline silica, which can help guide targeted dust control interventions and health promotion campaigns in the workplace.

Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis

PubMed Central

Ducrot, Virginie; Péry, Alexandre R. R.; Lagadic, Laurent

2010-01-01

Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment. PMID:20921047

Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis.

PubMed

Ducrot, Virginie; Péry, Alexandre R R; Lagadic, Laurent

2010-11-12

Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment.

Synthesis, characterization and cytotoxic evaluation of chitosan nanoparticles: in vitro liver cancer model

NASA Astrophysics Data System (ADS)

Loutfy, Samah A.; Alam El-Din, Hanaa M.; Elberry, Mostafa H.; Allam, Nanis G.; Hasanin, M. T. M.; Abdellah, Ahmed M.

2016-09-01

To evaluate the cytotoxic effect of chitosan nanoparticles (CS-NPs) on an in vitro human liver cancer cell model (HepG2) and their possible application as a drug delivery system, we synthesized water-soluble CS-NPs, investigated their properties and extensively evaluated their cytotoxic activity on the cellular and molecular levels. A human liver cancer cell line was used as a model of human liver cancer. The CS-NPs were characterized using transmission electron microscopy, Fourier transform infrared spectroscopy, and zeta analysis. The cytotoxic effects of the CS-NPs on HepG2 cells were monitored by sulforhodamine B colorimetric assays for cytotoxicity screening and flow cytometric analysis. Molecular investigations including DNA fragmentation and the expression of some apoptotic genes on the transcriptional RNA level were conducted. Treatment of HepG2 with different concentrations of 150 nm diameter CS-NPs did not show alteration of cell morphology after 24 h of cell exposure. Also, when cells were treated with 100 μg ml-1 of CS-NPs, 12% of them were killed and IC50 reached 239 μg ml-1 after 48 h of cell exposure. Flow cytometry evaluation of the CS-NPs revealed mild accumulation in the G2/M phase followed by cellular DNA fragmentation after 48 h of cell exposure. Extensive evaluation of the cytotoxic effect of the CS-NPs showed messenger RNA (mRNA) apoptotic gene expression (p53, Bak, Caspase3) after 24 h of cell exposure with no expression of the mRNA of the caspase 3 gene after 48 h of cell exposure, suggesting the involvement of an intrinsic apoptotic caspase-independent pathway by increasing the exposure time of 100 μg ml-1 of the CS-NPs. The engineered CS-NPs were controlled to a 150 nm size and charges of 40 mV and a concentration of 100 μg ml-1 revealed a genotoxic effect on HepG2 after 48 h of cell exposure through intrinsic apoptotic caspase-independent mechanisms. Further quantitative analysis on the molecular and protein levels is still required to confirm the impact of chitosan size and time on genotoxic effect before reaching a final conclusion and starting its biomedical application.

Comparison of methods for the analysis of relatively simple mediation models.

PubMed

Rijnhart, Judith J M; Twisk, Jos W R; Chinapaw, Mai J M; de Boer, Michiel R; Heymans, Martijn W

2017-09-01

Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.

Associations of Short-Term and Long-Term Exposure to Ambient Air Pollutants With Hypertension: A Systematic Review and Meta-Analysis.

PubMed

Cai, Yuanyuan; Zhang, Bo; Ke, Weixia; Feng, Baixiang; Lin, Hualiang; Xiao, Jianpeng; Zeng, Weilin; Li, Xing; Tao, Jun; Yang, Zuyao; Ma, Wenjun; Liu, Tao

2016-07-01

Hypertension is a major disease of burden worldwide. Previous studies have indicated that air pollution might be a risk factor for hypertension, but the results were controversial. To fill this gap, we performed a meta-analysis of epidemiological studies to investigate the associations of short-term and long-term exposure to ambient air pollutants with hypertension. We searched all of the studies published before September 1, 2015, on the associations of ozone (O3), carbon monoxide (CO), nitrogen oxide (NO2 and NOX), sulfur dioxide (SO2), and particulate matter (PM10 and PM2.5) with hypertension in the English electronic databases. A pooled odds ratio (OR) for hypertension in association with each 10 μg/m(3) increase in air pollutant was calculated by a random-effects model (for studies with significant heterogeneity) or a fixed-effect model (for studies without significant heterogeneity). A total of 17 studies examining the effects of short-term (n=6) and long-term exposure (n=11) to air pollutants were identified. Short-term exposure to SO2 (OR=1.046, 95% confidence interval [CI]: 1.012-1.081), PM2.5 (OR=1.069, 95% CI: 1.003-1.141), and PM10 (OR=1.024, 95% CI: 1.016-1.032) were significantly associated with hypertension. Long-term exposure (a 10 μg/m(3) increase) to NO2 (OR=1.034, 95% CI: 1.005-1.063) and PM10 (OR=1.054, 95% CI: 1.036-1.072) had significant associations with hypertension. Exposure to other ambient air pollutants (short-term exposure to NO2, O3, and CO and long-term exposure to NOx, PM2.5, and SO2) also had positive relationships with hypertension, but lacked statistical significance. Our results suggest that short-term or long-term exposure to some air pollutants may increase the risk of hypertension. © 2016 American Heart Association, Inc.

Economic costs of childhood lead exposure in low- and middle-income countries.

PubMed

Attina, Teresa M; Trasande, Leonardo

2013-09-01

Children's blood lead levels have declined worldwide, especially after the removal of lead in gasoline. However, significant exposure remains, particularly in low- and middle-income countries. To date, there have been no global estimates of the costs related to lead exposure in children in developing countries. Our main aim was to estimate the economic costs attributable to childhood lead exposure in low- and middle-income countries. We developed a regression model to estimate mean blood lead levels in our population of interest, represented by each 1-year cohort of children < 5 years of age. We used an environmentally attributable fraction model to estimate lead-attributable economic costs and limited our analysis to the neurodevelopmental impacts of lead, assessed as decrements in IQ points. Our main outcome was lost lifetime economic productivity due to early childhood exposure. We estimated a total cost of $977 billions of international dollars in low- and middle-income countries, with economic losses equal to $134.7 billion in Africa [4.03% of gross domestic product (GDP)], $142.3 billion in Latin America and the Caribbean (2.04% of GDP), and $699.9 billion in Asia (1.88% of GDP). Our sensitivity analysis indicates a total economic loss in the range of $728.6-1162.5 billion. We estimated that, in low- and middle-income countries, the burden associated with childhood lead exposure amounts to 1.20% of world GDP in 2011. For comparison, in the United States and Europe lead-attributable economic costs have been estimated at $50.9 and $55 billion, respectively, suggesting that the largest burden of lead exposure is now borne by low- and middle-income countries.

Integration of the predictions of two models with dose measurements in a case study of children exposed to the emissions of a lead smelter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bonnard, R.; McKone, T.E.

2009-03-01

The predictions of two source-to-dose models are systematically evaluated with observed data collected in a village polluted by a currently operating secondary lead smelter. Both models were built up from several sub-models linked together and run using Monte-Carlo simulation, to calculate the distribution children's blood lead levels attributable to the emissions from the facility. The first model system is composed of the CalTOX model linked to a recoded version of the IEUBK model. This system provides the distribution of the media-specific lead concentrations (air, soil, fruit, vegetables and blood) in the whole area investigated. The second model consists of amore » statistical model to estimate the lead deposition on the ground, a modified version of the model HHRAP and the same recoded version of the IEUBK model. This system provides an estimate of the concentration of exposure of specific individuals living in the study area. The predictions of the first model system were improved in terms of accuracy and precision by performing a sensitivity analysis and using field data to correct the default value provided for the leaf wet density. However, in this case study, the first model system tends to overestimate the exposure due to exposed vegetables. The second model was tested for nine children with contrasting exposure conditions. It managed to capture the blood levels for eight of them. In the last case, the exposure of the child by pathways not considered in the model may explain the failure of the model. The interest of this integrated model is to provide outputs with lower variance than the first model system, but at the moment further tests are necessary to conclude about its accuracy.« less

76 FR 18899 - Indaziflam; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-06

... Model/Exposure Analysis Modeling System (PRZM/EXAMS) and Screening Concentration in Ground Water (SCI... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... response to the notice of filing. Based upon review of the data supporting the petitions, EPA has modified...

75 FR 70143 - Acequinocyl; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-17

.../water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS... be affected. The North American Industrial Classification System (NAICS) codes have been provided to... the data supporting the petition, EPA has revised the proposed tolerance for hop dried cones from 3.5...

Impact of cytochrome P450 2C19 polymorphisms on citalopram/escitalopram exposure: a systematic review and meta-analysis.

PubMed

Chang, Ming; Tybring, Gunnel; Dahl, Marja-Liisa; Lindh, Jonatan D

2014-09-01

Citalopram and escitalopram, selective serotonin reuptake inhibitors, are primarily metabolized by cytochrome P450 (CYP) 2C19, which is a highly polymorphic enzyme known to cause inter-individual differences in pharmacokinetics. However, the impact of CYP2C19 polymorphisms on citalopram or escitalopram exposure has yet to be fully clarified, especially with regard to the quantitative impact of the CYP2C19*17 allele. The objective of this study was to quantify the effect of functional CYP2C19 allele variants on citalopram/escitalopram exposure. We performed a systematic review and meta-analysis with a structured search algorithm and eligibility criteria for including related studies, calculating the change of citalopram or escitalopram exposure associated with CYP2C19*2, *3, and *17 as compared with CYP2C19*1 using fixed-effect and random-effects models. Assessment of publication bias was performed by means of funnel plots and sensitivity analysis using meta-regressions. The pre-defined review protocol was registered at the PROSPERO international prospective register of systematic reviews, registration number CRD42013004106. Sixteen studies from 14 publications met the inclusion criteria. Eligible studies included 847 patients from psychiatric patient trials and 140 healthy subjects from pharmacokinetic studies. Compared to subjects with the EM/EM (CYP2C19*1/*1) genotype, the exposure to (es)citalopram increased by 95 % (95 % CI 40-149, p < 0.0001) in the poor metabolizer (PM)/PM (CYP2C19*2 or *3/*2 or *3), 30 % (95 % CI 4-55, p < 0.05) in the extensive metabolizer (EM)/PM (CYP2C19*1/*2 or *3), and 25 % (95 % CI 1-49, p < 0.05) in the ultrarapid metabolizer (UM)/PM (CYP2C19*17/*2 or *3) groups. In contrast, the exposure to (es)citalopram decreased by 36 % (95 % CI 27-46, p < 0.0001) in the UM/UM (CYP2C19*17/*17) and by 14 % (95 % CI 1-27, p < 0.05) in the UM/EM (CYP2C19*17/*1). This is the first meta-analysis based on a systematic review of accumulated information that addresses the relationship between CYP2C19 genotypes and the exposure to citalopram or escitalopram. All functional CYP2C19 genotype groups demonstrated significant effects on (es)citalopram exposure. The findings based on our pooled analysis are likely to help in understanding the inter-individual variability in the exposure to citalopram and escitalopram in psychiatric patients and to facilitate dose selection, particularly for the homozygous carriers of CYP2C19*2 or *3 (loss of function) and CYP2C19*17 (gain of function) alleles. The results could improve individualization of citalopram or escitalopram therapy and could also be used for physiologically based pharmacokinetic modeling as well as pharmacokinetic/pharmacodynamic modeling.

Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts

PubMed Central

Iskandar, Anita R.; Xiang, Yang; Frentzel, Stefan; Talikka, Marja; Leroy, Patrice; Kuehn, Diana; Guedj, Emmanuel; Martin, Florian; Mathis, Carole; Ivanov, Nikolai V.; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

Organotypic 3D cultures of epithelial cells are grown at the air–liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model. PMID:26085348

Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts.

PubMed

Iskandar, Anita R; Xiang, Yang; Frentzel, Stefan; Talikka, Marja; Leroy, Patrice; Kuehn, Diana; Guedj, Emmanuel; Martin, Florian; Mathis, Carole; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2015-09-01

Organotypic 3D cultures of epithelial cells are grown at the air-liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.

Spatiotemporal distributions of ambient oxides of nitrogen, with implications for exposure inequality and urban design.

PubMed

Yu, Haofei; Stuart, Amy L

2013-08-01

Intra-urban differences in concentrations of oxides of nitrogen (NO(x)) and exposure disparities in the Tampa area were investigated across temporal scales through emissions estimation, dispersion modeling, and analysis of residential subpopulation exposures. A hybrid estimation method was applied to provide link-level hourly on-road mobile source emissions. Ambient concentrations in 2002 at 1 km resolution were estimated using the CALPUFF dispersion model. Results were combined with residential demographic data at the block-group level, to investigate exposures and inequality for select racioethnic, age, and income population subgroups. Results indicate that on-road mobile sources contributed disproportionately to ground-level concentrations and dominated the spatial footprint across temporal scales (annual average to maximum hour). The black, lower income (less than $40K annually), and Hispanic subgroups had higher estimated exposures than the county average; the white and higher income (greater than $60K) subgroups had lower than average exposures. As annual average concentration increased, the disparity between groups generally increased. However for the highest 1-hr concentrations, reverse disparities were also found. Current studies of air pollution exposure inequality have not fully considered differences by time scale and are often limited in spatial resolution. The modeling methods and the results presented here can be used to improve understanding of potential impacts of urban growth form on health and to improve urban sustainability. Results suggest focusing urban design interventions on reducing on-road mobile source emissions in areas with high densities of minority and low income groups.

High-Throughput Analysis of Ovarian Cycle Disruption by Mixtures of Aromatase Inhibitors

PubMed Central

Golbamaki-Bakhtyari, Nazanin; Kovarich, Simona; Tebby, Cleo; Gabb, Henry A.; Lemazurier, Emmanuel

2017-01-01

Background: Combining computational toxicology with ExpoCast exposure estimates and ToxCast™ assay data gives us access to predictions of human health risks stemming from exposures to chemical mixtures. Objectives: We explored, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycles. Methods: We simulated random exposures to millions of potential mixtures of 86 aromatase inhibitors. A pharmacokinetic model of intake and disposition of the chemicals predicted their internal concentration as a function of time (up to 2 y). A ToxCast™ aromatase assay provided concentration–inhibition relationships for each chemical. The resulting total aromatase inhibition was input to a mathematical model of the hormonal hypothalamus–pituitary–ovarian control of ovulation in women. Results: Above 10% inhibition of estradiol synthesis by aromatase inhibitors, noticeable (eventually reversible) effects on ovulation were predicted. Exposures to individual chemicals never led to such effects. In our best estimate, ∼10% of the combined exposures simulated had mild to catastrophic impacts on ovulation. A lower bound on that figure, obtained using an optimistic exposure scenario, was 0.3%. Conclusions: These results demonstrate the possibility to predict large-scale mixture effects for endocrine disrupters with a predictive toxicology approach that is suitable for high-throughput ranking and risk assessment. The size of the effects predicted is consistent with an increased risk of infertility in women from everyday exposures to our chemical environment. https://doi.org/10.1289/EHP742 PMID:28886606

Social imagery, tobacco independence, and the truthsm campaign.

PubMed

Evans, W Douglas; Price, Simani; Blahut, Steven; Hersey, James; Niederdeppe, Jeffrey; Ray, Sarah

2004-01-01

This study investigated relationships among exposure to the truthsm campaign, differences in social imagery about not smoking and related measures, and smoking behavior. We asked, "How does truthsm work? Through what psychological mechanisms does it affect smoking behavior?" We developed a framework to explain how receptivity to truthsm ads might influence youth cognitive states and subsequent effects on progression to established smoking. The main hypotheses were that social imagery about not smoking and related beliefs and attitudes about tobacco use mediate the relationship between truthsm exposure and smoking status. The study was based on data from the Legacy Media Tracking Survey (LMTS), waves I-III, which were conducted at three time points from 1999 through 2001. A nationally representative sample of 20,058 respondents aged 12-24 from the three time points was used in the analysis. We developed a structural equation model (SEM) based on constructs drawn from the LMTS. We investigated the model and tested our hypotheses about the psychological and behavioral effects of campaign exposure. We tested our constructs and model using a two-stage structural equation modeling approach. We first conducted a confirmatory factor analysis (CFA) to test the measurement model. Our model achieved satisfactory fit, and we conducted the SEM to test our hypotheses. We found that social imagery and perceived tobacco independence mediate the relationship between truthsm exposure and smoking status. We found meaningful differences between paths for segmented samples based on age, gender, and race/ethnicity subgroups and over time. The truthsm campaign operates through individuals'sense of tobacco independence and social imagery about not smoking. This study indicates that the campaign's strategy has worked as predicted and represents an effective model for social marketing to change youth risk behaviors. Future studies should further investigate subgroup differences in campaign reactions and utilize contextual information about the truthsm campaign's evolution to explain changes in reactions over time.

The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control

PubMed Central

Wyss, Richard; Hansen, Ben B.; Ellis, Alan R.; Gagne, Joshua J.; Desai, Rishi J.; Glynn, Robert J.; Stürmer, Til

2017-01-01

Abstract A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the “dry-run” analysis, which divides the unexposed population into “pseudo-exposed” and “pseudo-unexposed” groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models. PMID:28338910

Galactic and solar radiation exposure to aircrew during a solar cycle.

PubMed

Lewis, B J; Bennett, L G I; Green, A R; McCall, M J; Ellaschuk, B; Butler, A; Pierre, M

2002-01-01

An on-going investigation using a tissue-equivalent proportional counter (TEPC) has been carried out to measure the ambient dose equivalent rate of the cosmic radiation exposure of aircrew during a solar cycle. A semi-empirical model has been derived from these data to allow for the interpolation of the dose rate for any global position. The model has been extended to an altitude of up to 32 km with further measurements made on board aircraft and several balloon flights. The effects of changing solar modulation during the solar cycle are characterised by correlating the dose rate data to different solar potential models. Through integration of the dose-rate function over a great circle flight path or between given waypoints, a Predictive Code for Aircrew Radiation Exposure (PCAIRE) has been further developed for estimation of the route dose from galactic cosmic radiation exposure. This estimate is provided in units of ambient dose equivalent as well as effective dose, based on E/H x (10) scaling functions as determined from transport code calculations with LUIN and FLUKA. This experimentally based treatment has also been compared with the CARI-6 and EPCARD codes that are derived solely from theoretical transport calculations. Using TEPC measurements taken aboard the International Space Station, ground based neutron monitoring, GOES satellite data and transport code analysis, an empirical model has been further proposed for estimation of aircrew exposure during solar particle events. This model has been compared to results obtained during recent solar flare events.

Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (Athene cunicularia hypugaea) as a case study

USGS Publications Warehouse

Engelman, Catherine A.; Grant, William E.; Mora, Miguel A.; Woodin, Marc

2012-01-01

We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls (Athene cunicularia hypugaea) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals.

Pulmonary immune responses to Aspergillus fumigatus in an immunocompetent mouse model of repeated exposures

PubMed Central

Buskirk, Amanda D.; Templeton, Steven P.; Nayak, Ajay P.; Hettick, Justin M.; Law, Brandon F.; Green, Brett J.; Beezhold, Donald H.

2015-01-01

Aspergillus fumigatus is a filamentous fungus that produces abundant pigmented conidia. Several fungal components have been identified as virulence factors, including melanin; however, the impact of these factors in a repeated exposure model resembling natural environmental exposures remains unknown. This study examined the role of fungal melanin in the stimulation of pulmonary immune responses using immunocompetent BALB/c mice in a multiple exposure model. It compared conidia from wild-type A. fumigatus to two melanin mutants of the same strain, Δarp2 (tan) or Δalb1 (white). Mass spectrometry-based analysis of conidial extracts demonstrated that there was little difference in the protein fingerprint profiles between the three strains. Field emission scanning electron microscopy demonstrated that the immunologically inert Rodlet A layer remained intact in melanin-deficient conidia. Thus, the primary difference between the strains was the extent of melanization. Histopathology indicated that each A. fumigatus strain induced lung inflammation, regardless of the extent of melanization. In mice exposed to Δalb1 conidia, an increase in airway eosinophils and a decrease in neutrophils and CD8+ IL-17+ (Tc17) cells were observed. Additionally, it was shown that melanin mutant conidia were more rapidly cleared from the lungs than wild-type conidia. These data suggest that the presence of fungal melanin may modulate the pulmonary immune response in a mouse model of repeated exposures to A. fumigatus conidia. PMID:23919459

Multivariate analysis of longitudinal rates of change.

PubMed

Bryan, Matthew; Heagerty, Patrick J

2016-12-10

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed in the literature. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, 'accelerated time' methods have been developed which assume that covariates rescale time in longitudinal models for disease progression. In this manuscript, we detail an alternative multivariate model formulation that directly structures longitudinal rates of change and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Meta-analysis of gene expression patterns in animal models of prenatal alcohol exposure suggests role for protein synthesis inhibition and chromatin remodeling

PubMed Central

Rogic, Sanja; Wong, Albertina; Pavlidis, Paul

2017-01-01

Background Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioural and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models, however there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. Methods We assembled ten microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and post-natal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. Results For each sub-analysis we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute ethanol treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over-representation of genes involved in protein synthesis, mRNA splicing and chromatin organization. Conclusions Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of FASD. PMID:26996386

Characterizing Class-Specific Exposure-Viral Load Suppression Response of HIV Antiretrovirals Using A Model-Based Meta-Analysis.

PubMed

Xu, Y; Li, Y F; Zhang, D; Dockendorf, M; Tetteh, E; Rizk, M L; Grobler, J A; Lai, M-T; Gobburu, J; Ankrom, W

2016-08-01

We applied model-based meta-analysis of viral suppression as a function of drug exposure and in vitro potency for short-term monotherapy in human immunodeficiency virus type 1 (HIV-1)-infected treatment-naïve patients to set pharmacokinetic targets for development of nonnucleoside reverse transcriptase inhibitors (NNRTIs) and integrase strand transfer inhibitors (InSTIs). We developed class-specific models relating viral load kinetics from monotherapy studies to potency normalized steady-state trough plasma concentrations. These models were integrated with a literature assessment of doses which demonstrated to have long-term efficacy in combination therapy, in order to set steady-state trough concentration targets of 6.17- and 2.15-fold above potency for NNRTIs and InSTIs, respectively. Both the models developed and the pharmacokinetic targets derived can be used to guide compound selection during preclinical development and to predict the dose-response of new antiretrovirals to inform early clinical trial design. © 2016 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

Topography- and nightlight-based national flood risk assessment in Canada

NASA Astrophysics Data System (ADS)

Elshorbagy, Amin; Bharath, Raja; Lakhanpal, Anchit; Ceola, Serena; Montanari, Alberto; Lindenschmidt, Karl-Erich

2017-04-01

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

Bivariate Left-Censored Bayesian Model for Predicting Exposure: Preliminary Analysis of Worker Exposure during the Deepwater Horizon Oil Spill.

PubMed

Groth, Caroline; Banerjee, Sudipto; Ramachandran, Gurumurthy; Stenzel, Mark R; Sandler, Dale P; Blair, Aaron; Engel, Lawrence S; Kwok, Richard K; Stewart, Patricia A

2017-01-01

In April 2010, the Deepwater Horizon oil rig caught fire and exploded, releasing almost 5 million barrels of oil into the Gulf of Mexico over the ensuing 3 months. Thousands of oil spill workers participated in the spill response and clean-up efforts. The GuLF STUDY being conducted by the National Institute of Environmental Health Sciences is an epidemiological study to investigate potential adverse health effects among these oil spill clean-up workers. Many volatile chemicals were released from the oil into the air, including total hydrocarbons (THC), which is a composite of the volatile components of oil including benzene, toluene, ethylbenzene, xylene, and hexane (BTEXH). Our goal is to estimate exposure levels to these toxic chemicals for groups of oil spill workers in the study (hereafter called exposure groups, EGs) with likely comparable exposure distributions. A large number of air measurements were collected, but many EGs are characterized by datasets with a large percentage of censored measurements (below the analytic methods' limits of detection) and/or a limited number of measurements. We use THC for which there was less censoring to develop predictive linear models for specific BTEXH air exposures with higher degrees of censoring. We present a novel Bayesian hierarchical linear model that allows us to predict, for different EGs simultaneously, exposure levels of a second chemical while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposure levels for several EGs on the Development Driller III, a rig vessel charged with drilling one of the relief wells. The model provided credible estimates in this example for geometric means, arithmetic means, variances, correlations, and regression coefficients for each group. This approach should be considered when estimating exposures in situations when multiple chemicals are correlated and have varying degrees of censoring. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study

PubMed Central

Chang, Howard H.; Warren, Joshua L.; Darrow, Lnydsey A.; Reich, Brian J.; Waller, Lance A.

2015-01-01

In reproductive epidemiology, there is a growing interest to examine associations between air pollution exposure during pregnancy and the risk of preterm birth (PTB). One important research objective is to identify critical periods of exposure and estimate the associated effects at different stages of pregnancy. However, population studies have reported inconsistent findings. This may be due to limitations from the standard analytic approach of treating PTB as a binary outcome without considering time-varying exposures together over the course of pregnancy. To address this research gap, we present a Bayesian hierarchical model for conducting a comprehensive examination of gestational air pollution exposure by estimating the joint effects of weekly exposures during different vulnerable periods. Our model also treats PTB as a time-to-event outcome to address the challenge of different exposure lengths among ongoing pregnancies. The proposed model is applied to a dataset of geocoded birth records in the Atlanta metropolitan area between 1999–2005 to examine the risk of PTB associated with gestational exposure to ambient fine particulate matter \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\lt 2.5\\,{\\rm \\mu}$\\end{document}m in aerodynamic diameter (PM\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$_{2.5}$\\end{document}). We find positive associations between PM\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$_{2.5}$\\end{document} exposure during early and mid-pregnancy, and evidence that associations are stronger for PTBs occurring around week 30. PMID:25572998

Predicting Residential Exposure to Phthalate Plasticizer Emitted from Vinyl Flooring: Sensitivity, Uncertainty, and Implications for Biomonitoring

PubMed Central

Xu, Ying; Cohen Hubal, Elaine A.; Little, John C.

2010-01-01

Background Because of the ubiquitous nature of phthalates in the environment and the potential for adverse human health effects, an urgent need exists to identify the most important sources and pathways of exposure. Objectives Using emissions of di(2-ethylhexyl) phthalate (DEHP) from vinyl flooring (VF) as an illustrative example, we describe a fundamental approach that can be used to identify the important sources and pathways of exposure associated with phthalates in indoor material. Methods We used a three-compartment model to estimate the emission rate of DEHP from VF and the evolving exposures via inhalation, dermal absorption, and oral ingestion of dust in a realistic indoor setting. Results A sensitivity analysis indicates that the VF source characteristics (surface area and material-phase concentration of DEHP), as well as the external mass-transfer coefficient and ventilation rate, are important variables that influence the steady-state DEHP concentration and the resulting exposure. In addition, DEHP is sorbed by interior surfaces, and the associated surface area and surface/air partition coefficients strongly influence the time to steady state. The roughly 40-fold range in predicted exposure reveals the inherent difficulty in using biomonitoring to identify specific sources of exposure to phthalates in the general population. Conclusions The relatively simple dependence on source and chemical-specific transport parameters suggests that the mechanistic modeling approach could be extended to predict exposures arising from other sources of phthalates as well as additional sources of other semivolatile organic compounds (SVOCs) such as biocides and flame retardants. This modeling approach could also provide a relatively inexpensive way to quantify exposure to many of the SVOCs used in indoor materials and consumer products. PMID:20123613

Predicting residential exposure to phthalate plasticizer emitted from vinyl flooring: sensitivity, uncertainty, and implications for biomonitoring.

PubMed

Xu, Ying; Cohen Hubal, Elaine A; Little, John C

2010-02-01

Because of the ubiquitous nature of phthalates in the environment and the potential for adverse human health effects, an urgent need exists to identify the most important sources and pathways of exposure. Using emissions of di(2-ethylhexyl) phthalate (DEHP) from vinyl flooring (VF) as an illustrative example, we describe a fundamental approach that can be used to identify the important sources and pathways of exposure associated with phthalates in indoor material. We used a three-compartment model to estimate the emission rate of DEHP from VF and the evolving exposures via inhalation, dermal absorption, and oral ingestion of dust in a realistic indoor setting. A sensitivity analysis indicates that the VF source characteristics (surface area and material-phase concentration of DEHP), as well as the external mass-transfer coefficient and ventilation rate, are important variables that influence the steady-state DEHP concentration and the resulting exposure. In addition, DEHP is sorbed by interior surfaces, and the associated surface area and surface/air partition coefficients strongly influence the time to steady state. The roughly 40-fold range in predicted exposure reveals the inherent difficulty in using biomonitoring to identify specific sources of exposure to phthalates in the general population. The relatively simple dependence on source and chemical-specific transport parameters suggests that the mechanistic modeling approach could be extended to predict exposures arising from other sources of phthalates as well as additional sources of other semivolatile organic compounds (SVOCs) such as biocides and flame retardants. This modeling approach could also provide a relatively inexpensive way to quantify exposure to many of the SVOCs used in indoor materials and consumer products.

Exposure to fluoride in drinking water and hip fracture risk: a meta-analysis of observational studies.

PubMed

Yin, Xin-Hai; Huang, Guang-Lei; Lin, Du-Ren; Wan, Cheng-Cheng; Wang, Ya-Dong; Song, Ju-Kun; Xu, Ping

2015-01-01

Many observational studies have shown that exposure to fluoride in drinking water is associated with hip fracture risk. However, the findings are varied or even contradictory. In this work, we performed a meta-analysis to assess the relationship between fluoride exposure and hip fracture risk. PubMed and EMBASE databases were searched to identify relevant observational studies from the time of inception until March 2014 without restrictions. Data from the included studies were extracted and analyzed by two authors. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were pooled using random- or fixed-effects models as appropriate. Sensitivity analyses and meta-regression were conducted to explore possible explanations for heterogeneity. Finally, publication bias was assessed. Fourteen observational studies involving thirteen cohort studies and one case-control study were included in the meta-analysis. Exposure to fluoride in drinking water does not significantly increase the incidence of hip fracture (RRs, 1.05; 95% CIs, 0.96-1.15). Sensitivity analyses based on adjustment for covariates, effect measure, country, sex, sample size, quality of Newcastle-Ottawa Scale scores, and follow-up period validated the strength of the results. Meta-regression showed that country, gender, quality of Newcastle-Ottawa Scale scores, adjustment for covariates and sample size were not sources of heterogeneity. Little evidence of publication bias was observed. The present meta-analysis suggests that chronic fluoride exposure from drinking water does not significantly increase the risk of hip fracture. Given the potential confounding factors and exposure misclassification, further large-scale, high-quality studies are needed to evaluate the association between exposure to fluoride in drinking water and hip fracture risk.

Exposure to Fluoride in Drinking Water and Hip Fracture Risk: A Meta-Analysis of Observational Studies

PubMed Central

Yin, Xin-Hai; Huang, Guang-Lei; Lin, Du-Ren; Wan, Cheng-Cheng; Wang, Ya-Dong; Song, Ju-Kun; Xu, Ping

2015-01-01

Background Many observational studies have shown that exposure to fluoride in drinking water is associated with hip fracture risk. However, the findings are varied or even contradictory. In this work, we performed a meta-analysis to assess the relationship between fluoride exposure and hip fracture risk. Methods PubMed and EMBASE databases were searched to identify relevant observational studies from the time of inception until March 2014 without restrictions. Data from the included studies were extracted and analyzed by two authors. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were pooled using random- or fixed-effects models as appropriate. Sensitivity analyses and meta-regression were conducted to explore possible explanations for heterogeneity. Finally, publication bias was assessed. Results Fourteen observational studies involving thirteen cohort studies and one case-control study were included in the meta-analysis. Exposure to fluoride in drinking water does not significantly increase the incidence of hip fracture (RRs, 1.05; 95% CIs, 0.96–1.15). Sensitivity analyses based on adjustment for covariates, effect measure, country, sex, sample size, quality of Newcastle–Ottawa Scale scores, and follow-up period validated the strength of the results. Meta-regression showed that country, gender, quality of Newcastle–Ottawa Scale scores, adjustment for covariates and sample size were not sources of heterogeneity. Little evidence of publication bias was observed. Conclusion The present meta-analysis suggests that chronic fluoride exposure from drinking water does not significantly increase the risk of hip fracture. Given the potential confounding factors and exposure misclassification, further large-scale, high-quality studies are needed to evaluate the association between exposure to fluoride in drinking water and hip fracture risk. PMID:26020536

Selection of software for mechanical engineering undergraduates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheah, C. T.; Yin, C. S.; Halim, T.

A major problem with the undergraduate mechanical course is the limited exposure of students to software packages coupled with the long learning curve on the existing software packages. This work proposes the use of appropriate software packages for the entire mechanical engineering curriculum to ensure students get sufficient exposure real life design problems. A variety of software packages are highlighted as being suitable for undergraduate work in mechanical engineering, e.g. simultaneous non-linear equations; uncertainty analysis; 3-D modeling software with the FEA; analysis tools for the solution of problems in thermodynamics, fluid mechanics, mechanical system design, and solid mechanics.

Agent Orange exposure and prevalence of self-reported diseases in Korean Vietnam veterans.

PubMed

Yi, Sang-Wook; Ohrr, Heechoul; Hong, Jae-Seok; Yi, Jee-Jeon

2013-09-01

The aim of this study was to evaluate the association between Agent Orange exposure and self-reported diseases in Korean Vietnam veterans. A postal survey of 114 562 Vietnam veterans was conducted. The perceived exposure to Agent Orange was assessed by a 6-item questionnaire. Two proximity-based Agent Orange exposure indices were constructed using division/brigade-level and battalion/company-level unit information. Adjusted odds ratios (ORs) for age and other confounders were calculated using a logistic regression model. The prevalence of all self-reported diseases showed monotonically increasing trends as the levels of perceived self-reported exposure increased. The ORs for colon cancer (OR, 1.13), leukemia (OR, 1.56), hypertension (OR, 1.03), peripheral vasculopathy (OR, 1.07), enterocolitis (OR, 1.07), peripheral neuropathy (OR, 1.07), multiple nerve palsy (OR, 1.14), multiple sclerosis (OR, 1.24), skin diseases (OR, 1.05), psychotic diseases (OR, 1.07) and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the division/brigade-level proximity-based exposure analysis, compared to the low exposure group. The ORs for cerebral infarction (OR, 1.08), chronic bronchitis (OR, 1.05), multiple nerve palsy (OR, 1.07), multiple sclerosis (OR, 1.16), skin diseases (OR, 1.05), and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the battalion/company-level analysis. Korean Vietnam veterans with high exposure to Agent Orange experienced a higher prevalence of several self-reported chronic diseases compared to those with low exposure by proximity-based exposure assessment. The strong positive associations between perceived self-reported exposure and all self-reported diseases should be evaluated with discretion because the likelihood of reporting diseases was directly related to the perceived intensity of Agent Orange exposure.

Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach.

PubMed

Cai, Yutong; Zijlema, Wilma L; Doiron, Dany; Blangiardo, Marta; Burton, Paul R; Fortier, Isabel; Gaye, Amadou; Gulliver, John; de Hoogh, Kees; Hveem, Kristian; Mbatchou, Stéphane; Morley, David W; Stolk, Ronald P; Elliott, Paul; Hansell, Anna L; Hodgson, Susan

2017-01-01

We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006-2013 (HUNT3, Lifelines and UK Biobank).Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM 10 ) and nitrogen dioxide (NO 2 )) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a "compute to the data" approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.PM 10 or NO 2 higher by 10 µg·m -3 was associated with 12.8% (95% CI 9.5-16.3%) and 1.9% (95% CI 1.1-2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.This study suggests that long-term ambient PM 10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation. Copyright ©ERS 2017.

Meta-analysis of cranial CT scans in children. A mathematical model to predict radiation-induced tumors.

PubMed

Stein, Sherman C; Hurst, Robert W; Sonnad, Seema S

2008-01-01

We aimed to estimate the risks of radiation exposure from a single head CT scan to children of different ages. We constructed a multistate time-dependent Markov model to simulate the course of children exposed to a head CT. The relevant literature was reviewed for probabilities, which were used to calculate tumor types, latencies after exposure and outcomes in the model. Where multiple approximations of the same probability had been reported, meta-analytic techniques were employed to compute pooled estimates. The model was then used to calculate the effect of the radiation exposure on life expectancy and quality of life for children following head CT at different ages. The tumors likely to be induced by low-level cranial irradiation include thyroid carcinoma (47%), meningioma (34%) and glioma (19%). According to the model, a single head CT is likely to cause one of these tumors in 0.22% of 1-year-olds, 30% of whom will consequently die. The exposure will shorten the life expectancy of all exposed 1-year-olds by an average of 0.04 years and their expected quality of life by 0.02 quality-adjusted life years. The risks of radiation exposure diminish for older children. The model predicts that the effective radiation dose from a single head CT is capable of inducing a thyroid or brain tumor in an infant or child. These tumors can severely impact both quality of life and life expectancy. Care should be taken before ordering CT scans in children, particularly in infants and toddlers. Copyright 2008 S. Karger AG, Basel.

Associations of maternal long-chain polyunsaturated fatty acids, methyl mercury, and infant development in the Seychelles Child Development Nutrition Study.

PubMed

Strain, J J; Davidson, Philip W; Bonham, Maxine P; Duffy, Emeir M; Stokes-Riner, Abbie; Thurston, Sally W; Wallace, Julie M W; Robson, Paula J; Shamlaye, Conrad F; Georger, Lesley A; Sloane-Reeves, Jean; Cernichiari, Elsa; Canfield, Richard L; Cox, Christopher; Huang, Li Shan; Janciuras, Joanne; Myers, Gary J; Clarkson, Thomas W

2008-09-01

Fish consumption during gestation can provide the fetus with long-chain polyunsaturated fatty acids (LCPUFA) and other nutrients essential for growth and development of the brain. However, fish consumption also exposes the fetus to the neurotoxicant, methyl mercury (MeHg). We studied the association between these fetal exposures and early child development in the Seychelles Child Development Nutrition Study (SCDNS). Specifically, we examined a priori models of Omega-3 and Omega-6 LCPUFA measures in maternal serum to test the hypothesis that these LCPUFA families before or after adjusting for prenatal MeHg exposure would reveal associations with child development assessed by the BSID-II at ages 9 and 30 months. There were 229 children with complete outcome and covariate data available for analysis. At 9 months, the PDI was positively associated with total Omega-3 LCPUFA and negatively associated with the ratio of Omega-6/Omega-3 LCPUFA. These associations were stronger in models adjusted for prenatal MeHg exposure. Secondary models suggested that the MeHg effect at 9 months varied by the ratio of Omega-6/Omega-3 LCPUFA. There were no significant associations between LCPUFA measures and the PDI at 30 months. There were significant adverse associations, however, between prenatal MeHg and the 30-month PDI when the LCPUFA measures were included in the regression analysis. The BSID-II mental developmental index (MDI) was not associated with any exposure variable. These data support the potential importance to child development of prenatal availability of Omega-3 LCPUFA present in fish and of LCPUFA in the overall diet. Furthermore, they indicate that the beneficial effects of LCPUFA can obscure the determination of adverse effects of prenatal MeHg exposure in longitudinal observational studies.

Associations of maternal long chain polyunsaturated fatty acids, methyl mercury, and infant development in the Seychelles Child Development Nutrition Study

PubMed Central

Strain, J.J.; Davidson, Philip W.; Bonham, Maxine P.; Duffy, Emeir M.; Stokes-Riner, Abbie; Thurston, Sally W.; Wallace, Julie M.W.; Robson, Paula J.; Shamlaye, Conrad F.; Georger, Lesley A.; Sloane-Reeves, Jean; Cernichiari, Elsa; Canfield, Richard L.; Cox, Christopher; Huang, Li Shan; Janciuras, Joanne; Myers, Gary J.; Clarkson, Thomas W.

2008-01-01

Fish consumption during gestation can provide the fetus with long chain polyunsaturated fatty acids (LCPUFA) and other nutrients essential for growth and development of the brain. However, fish consumption also exposes the fetus to the neurotoxicant, methyl mercury (MeHg). We studied the association between these fetal exposures and early child development in the Seychelles Child Development Nutrition Study (SCDNS). Specifically, we examined a priori models of Ω-3 and Ω-6 LCPUFA measures in maternal serum to test the hypothesis that these LCPUFA families before or after adjusting for prenatal MeHg exposure would reveal associations with child development assessed by the BSID-II at ages 9 and 30 months. There were 229 children with complete outcome and covariate data available for analysis. At 9 months, the PDI was positively associated with total Ω-3 LCPUFA and negatively associated with the ratio of Ω-6/Ω-3 LCPUFA. These associations were stronger in models adjusted for prenatal MeHg exposure. Secondary models suggested that the MeHg effect at 9 months varied by the ratio of Ω-6/Ω-3 LCPUFA. There were no significant associations between LCPUFA measures and the PDI at 30 months. There were significant adverse associations, however, between prenatal MeHg and the 30 month PDI when the LCPUFA measures were included in the regression analysis. The BSID-II Mental Developmental Index (MDI) was not associated with any exposure variable. These data support the potential importance to child development of prenatal availability of Ω-3 LCPUFA present in fish and of LCPUFA in the overall diet. Furthermore, they indicate that the beneficial effects of LCPUFA can obscure the determination of adverse effects of prenatal MeHg exposure in longitudinal observational studies. PMID:18590765

Neurobehavioral performance in adolescents is inversely associated with traffic exposure.

PubMed

Kicinski, Michal; Vermeir, Griet; Van Larebeke, Nicolas; Den Hond, Elly; Schoeters, Greet; Bruckers, Liesbeth; Sioen, Isabelle; Bijnens, Esmée; Roels, Harry A; Baeyens, Willy; Viaene, Mineke K; Nawrot, Tim S

2015-02-01

On the basis of animal research and epidemiological studies in children and elderly there is a growing concern that traffic exposure may affect the brain. The aim of our study was to investigate the association between traffic exposure and neurobehavioral performance in adolescents. We examined 606 adolescents. To model the exposure, we constructed a traffic exposure factor based on a biomarker of benzene (urinary trans,trans-muconic acid) and the amount of contact with traffic preceding the neurobehavioral examination (using distance-weighted traffic density and time spent in traffic). We used a Bayesian structural equation model to investigate the association between traffic exposure and three neurobehavioral domains: sustained attention, short-term memory, and manual motor speed. A one standard deviation increase in traffic exposure was associated with a 0.26 standard deviation decrease in sustained attention (95% credible interval: -0.02 to -0.51), adjusting for gender, age, smoking, passive smoking, level of education of the mother, socioeconomic status, time of the day, and day of the week. The associations between traffic exposure and the other neurobehavioral domains studied had the same direction but did not reach the level of statistical significance. The results remained consistent in the sensitivity analysis excluding smokers and passive smokers. The inverse association between sustained attention and traffic exposure was independent of the blood lead level. Our study in adolescents supports the recent findings in children and elderly suggesting that traffic exposure adversely affects the neurobehavioral function. Copyright © 2014 Elsevier Ltd. All rights reserved.

Controlling Mitochondrial Dynamics to Mitigate Noise-Induced Hearing Loss

DTIC Science & Technology

2016-10-01

exposure significantly reduced noise-induced auditory threshold shifts in our mouse model of NIHL. Additionally, protection against outer hair cell...and at 6 hours post-noise exposure. ‐ Perform analysis of outer auditory hair cells and synaptic ribbons from the different treatment groups...have made progress towards the completion of the outer hair cell counts (OHC) for this Subtask, particularly for study groups (1) mdivi-1/vehicle, and

Environmental arsenic exposure and serum matrix metalloproteinase-9.

PubMed

Burgess, Jefferey L; Kurzius-Spencer, Margaret; O'Rourke, Mary Kay; Littau, Sally R; Roberge, Jason; Meza-Montenegro, Maria Mercedes; Gutiérrez-Millán, Luis Enrique; Harris, Robin B

2013-03-01

The objective of this study was to evaluate the relationship between environmental arsenic exposure and serum matrix metalloproteinase (MMP)-9, a biomarker associated with cardiovascular disease and cancer. In a cross-sectional study of residents of Arizona, USA (n=215) and Sonora, Mexico (n=163), drinking water was assayed for total arsenic, and daily drinking water arsenic intake was estimated. Urine was speciated for arsenic, and concentrations were adjusted for specific gravity. Serum was analyzed for MMP-9 using ELISA. Mixed model linear regression was used to assess the relation among drinking water arsenic concentration, drinking water arsenic intake, urinary arsenic sum of species (the sum of arsenite, arsenate, monomethylarsonic acid and dimethylarsinic acid), and MMP-9, controlling for autocorrelation within households. Drinking water arsenic concentration and intake were positively associated with MMP-9, both in crude analysis and after adjustment for gender, country/ethnicity, age, body mass index, current smoking, and diabetes. Urinary arsenic sum of species was positively associated with MMP-9 in multivariable analysis only. Using Akaike's Information Criterion, arsenic concentration in drinking water provided a better fitting model of MMP-9 than either urinary arsenic or drinking water arsenic intake. In conclusion, arsenic exposure evaluated using all three exposure metrics was positively associated with MMP-9.

Environmental arsenic exposure and serum matrix metalloproteinase-9

PubMed Central

Burgess, Jefferey L.; Kurzius-Spencer, Margaret; O’Rourke, Mary Kay; Littau, Sally R.; Roberge, Jason; Meza-Montenegro, Maria Mercedes; Gutiérrez-Millán, Luis Enrique; Harris, Robin B.

2014-01-01

The objective of this study was to evaluate the relationship between environmental arsenic exposure and serum matrix metalloproteinase (MMP)-9, a biomarker associated with cardiovascular disease and cancer. In a cross-sectional study of residents of Arizona, USA (n=215) and Sonora, Mexico (n=163), drinking water was assayed for total arsenic, and daily drinking water arsenic intake estimated. Urine was speciated for arsenic and concentrations were adjusted for specific gravity. Serum was analyzed for MMP-9 using ELISA. Mixed model linear regression was used to assess the relation among drinking water arsenic concentration, drinking water arsenic intake, urinary arsenic sum of species (the sum of arsenite, arsenate, monomethylarsonic acid and dimethylarsinic acid), and MMP-9, controlling for autocorrelation within households. Drinking water arsenic concentration and intake were positively associated with MMP-9, both in crude analysis and after adjustment for gender, country/ethnicity, age, body mass index, current smoking and diabetes. Urinary arsenic sum of species was positively associated with MMP-9 in multivariable analysis only. Using Akaike’s Information Criterion, arsenic concentration in drinking water provided a better fitting model of MMP-9, than either urinary arsenic or drinking water arsenic intake. In conclusion, arsenic exposure was positively associated with MMP-9 using all three exposure metrics evaluated. PMID:23232971

Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error.

PubMed

Chang, Howard H; Peng, Roger D; Dominici, Francesca

2011-10-01

In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 μm. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.

Racial Differences in Perceptions of Air Pollution Health Risk: Does Environmental Exposure Matter?

PubMed Central

Chakraborty, Jayajit; Collins, Timothy W.; Grineski, Sara E.; Maldonado, Alejandra

2017-01-01

This article extends environmental risk perception research by exploring how potential health risk from exposure to industrial and vehicular air pollutants, as well as other contextual and socio-demographic factors, influence racial/ethnic differences in air pollution health risk perception. Our study site is the Greater Houston metropolitan area, Texas, USA—a racially/ethnically diverse area facing high levels of exposure to pollutants from both industrial and transportation sources. We integrate primary household-level survey data with estimates of excess cancer risk from ambient exposure to industrial and on-road mobile source emissions of air toxics obtained from the U.S. Environmental Protection Agency. Statistical analysis is based on multivariate generalized estimation equation models which account for geographic clustering of surveyed households. Our results reveal significantly higher risk perceptions for non-Hispanic Black residents and those exposed to greater cancer risk from industrial pollutants, and also indicate that gender influences the relationship between race/ethnicity and air pollution risk perception. These findings highlight the need to incorporate measures of environmental health risk exposure in future analysis of social disparities in risk perception. PMID:28125059

Movie exposure to smoking cues and adolescent smoking onset: a test for mediation through peer affiliations.

PubMed

Wills, Thomas A; Sargent, James D; Stoolmiller, Mike; Gibbons, Frederick X; Worth, Keilah A; Dal Cin, Sonya

2007-11-01

To determine whether the effect of movie exposure to smoking on adolescent smoking onset is mediated through increased affiliation with peers who smoke. A longitudinal study was conducted with a sample of 5th- 8th graders; persons who were nonsmokers at the baseline assessment (N = 2,614) were followed up 18 months later. Movie exposure to smoking cues was assessed at baseline with a rigorous coding procedure. A school-based survey and follow-up telephone interview determined whether the participant smoked cigarettes. Longitudinal structural modeling analysis indicated movie-smoking exposure was related to smoking onset both through an indirect effect involving increased affiliation with peer smokers and through a direct effect. The analysis controlled for demographics, parenting style, rebelliousness and sensation seeking, school performance, parental smoking, and sibling smoking; several of these variables also had mediated or direct effects to smoking onset. The effect of movie exposure on adolescent smoking onset is attributable in part to a social mechanism. Implications of media effects for prevention are discussed. (PsycINFO Database Record (c) 2007 APA, all rights reserved).

DEVELOPMENT AND APPLICATIONS OF CFD IN SUPPORT OF AIR QUALITY STUDIES OF ROADWAY AND BUILDING MICROENVIRONMENTS

EPA Science Inventory

There is a need to develop modeling and data analysis tools to increase our understanding of human exposures to air pollutants beyond what can be explained by "limited" field data. Modeling simulations of complex distributions of pollutant concentrations within roadw...

Ethnic Diversity, Inter-group Attitudes and Countervailing Pathways of Positive and Negative Inter-group Contact: An Analysis Across Workplaces and Neighbourhoods.

PubMed

Laurence, James; Schmid, Katharina; Hewstone, Miles

2018-01-01

This study advances the current literature investigating the relationship between contextual out-group exposure, inter-group attitudes and the role of inter-group contact. Firstly, it introduces the concept of contact-valence into this relationship; that is, whether contact is experienced positively or negatively. Secondly, it presents a comparative analysis of how processes of out-group exposure and frequency of (valenced) contact affect prejudice across both neighbourhoods and workplaces. Applying path analysis modelling to a nationally-representative sample of white British individuals in England, we demonstrate, across both contexts, that increasing out-group exposure is associated with higher rates of both positively- and negatively-valenced contact. This results in exposure exhibiting both positive and negative indirect associations with prejudice via more frequent inter-group mixing. These countervailing contact-pathways help explain how out-group exposure is associated with inter-group attitudes. In neighbourhoods, increasing numbers of individuals experiencing positive-contact suppress an otherwise negative effect of neighbourhood diversity (driven partly by increasing numbers of individuals reporting negative contact). Across workplaces the effect differs such that increasing numbers of individuals experiencing negative-contact suppress an otherwise positive effect of workplace diversity (driven largely by increasing numbers of individuals experiencing positive contact).

Whole genome expression analysis in primary bronchial epithelial cells after exposure to sulphur mustard.

PubMed

Jowsey, Paul A; Blain, Peter G

2014-11-04

Sulphur mustard (SM) is a highly toxic chemical agent and poses a current threat to both civilians and military personnel in the event of a deliberate malicious release. Acute SM toxicity develops over the course of several hours and mainly affects the skin and mucosal surfaces of the eyes and respiratory system. In cases of acute severe exposure, significant lung injury can result in respiratory failure and death. Systemic levels of SM can also be fatal, frequently due to immunodepletion and the subsequent development of secondary infections. Whilst the physical effects associated with SM exposure are well documented, the molecular mechanisms mediating these changes are poorly understood, hindering the development of an effective therapeutic strategy. To gain a better understanding of the mechanism of SM toxicity, this study investigated whole genome transcriptional changes after SM in primary human bronchial epithelial cells, as a model for inhalation exposure. The analysis revealed >400 transcriptional changes associated with SM exposure. Pathways analysis confirmed the findings of previous studies suggesting that DNA damage, cell cycle arrest, cell death and inflammation were important components of SM toxicity. In addition, several other interesting observations were made, suggesting that protein oxidation as well as effects on the mitotic apparatus may contribute to SM toxicity. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Joint nonparametric correction estimator for excess relative risk regression in survival analysis with exposure measurement error

PubMed Central

Wang, Ching-Yun; Cullings, Harry; Song, Xiao; Kopecky, Kenneth J.

2017-01-01

SUMMARY Observational epidemiological studies often confront the problem of estimating exposure-disease relationships when the exposure is not measured exactly. In the paper, we investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a nonparametric correction (NPC) estimator using data from the subcohort, and further propose a joint nonparametric correction (JNPC) estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of JNPC and NPC is further developed. The proposed estimators are nonparametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses. PMID:29354018

Low-frequency magnetic fields do not aggravate disease in mouse models of Alzheimer's disease and amyotrophic lateral sclerosis

PubMed Central

Liebl, Martina P.; Windschmitt, Johannes; Besemer, Anna S.; Schäfer, Anne-Kathrin; Reber, Helmut; Behl, Christian; Clement, Albrecht M.

2015-01-01

Low-frequency magnetic fields (LF-MF) generated by power lines represent a potential environmental health risk and are classified as possibly carcinogenic by the World Health Organization. Epidemiological studies indicate that LF-MF might propagate neurodegenerative diseases like Alzheimer's disease (AD) or amyotrophic lateral sclerosis (ALS). We conducted a comprehensive analysis to determine whether long-term exposure to LF-MF (50 Hz, 1 mT) interferes with disease development in established mouse models for AD and ALS, namely APP23 mice and mice expressing mutant Cu/Zn-superoxide dismutase (SOD1), respectively. Exposure for 16 months did not aggravate learning deficit of APP23 mice. Likewise, disease onset and survival of SOD1G85R or SOD1G93A mice were not altered upon LF-MF exposure for ten or eight months, respectively. These results and an extended biochemical analysis of protein aggregation, glial activation and levels of toxic protein species suggests that LF-MF do not affect cellular processes involved in the pathogenesis of AD or ALS. PMID:25717019

Application of Wavelet Filters in an Evaluation of ...

EPA Pesticide Factsheets

Air quality model evaluation can be enhanced with time-scale specific comparisons of outputs and observations. For example, high-frequency (hours to one day) time scale information in observed ozone is not well captured by deterministic models and its incorporation into model performance metrics lead one to devote resources to stochastic variations in model outputs. In this analysis, observations are compared with model outputs at seasonal, weekly, diurnal and intra-day time scales. Filters provide frequency specific information that can be used to compare the strength (amplitude) and timing (phase) of observations and model estimates. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollu

Size-selective pulmonary dose indices for metal-working fluid aerosols in machining and grinding operations in the automobile manufacturing industry.

PubMed

Woskie, S R; Smith, T J; Hallock, M F; Hammond, S K; Rosenthal, F; Eisen, E A; Kriebel, D; Greaves, I A

1994-01-01

The current metal-working fluid exposures at three locations that manufacture automotive parts were assessed in conjunction with epidemiological studies of the mortality and respiratory morbidity experiences of workers at these plants. A rationale is presented for selecting and characterizing epidemiologic exposure groups in this environment. More than 475 full-shift personal aerosol samples were taken using a two-stage personal cascade impactor with median size cut-offs of 9.8 microns and 3.5 microns, plus a backup filter. For a sample of 403 workers exposed to aerosols of machining or grinding fluids, the mean total exposure was 706 micrograms/m3 (standard error (SE) = 21 micrograms/m3). Among 72 assemblers unexposed to machining fluids, the mean total exposure was 187 +/- 10 (SE) micrograms/m3. An analysis of variance model identified factors significantly associated with exposure level and permitted estimates of exposure for workers in the unsampled machine type/metal-working fluid groups. Comparison of the results obtained from personal impactor samples with predictions from an aerosol-deposition model for the human respiratory tract showed high correlation. However, the amount collected on the impactor stage underestimates extrathoracic deposition and overestimates tracheobronchial and alveolar deposition, as calculated by the deposition model. When both the impactor concentration and the deposition-model concentration were used to estimate cumulative thoracic concentrations for the worklives of a subset of auto workers, there was no significant difference in the rank order of the subjects' cumulative concentration. However, the cumulative impactor concentration values were significantly higher than the cumulative deposition-model concentration values for the subjects.

Quantitative disease progression model of α‐1 proteinase inhibitor therapy on computed tomography lung density in patients with α‐1 antitrypsin deficiency

PubMed Central

Rogers, James A.; Vit, Oliver; Bexon, Martin; Sandhaus, Robert A.; Burdon, Jonathan; Chorostowska‐Wynimko, Joanna; Thompson, Philip; Stocks, James; McElvaney, Noel G.; Chapman, Kenneth R.; Edelman, Jonathan M.

2017-01-01

Aims Early‐onset emphysema attributed to α‐1 antitrypsin deficiency (AATD) is frequently overlooked and undertreated. RAPID‐RCT/RAPID‐OLE, the largest clinical trials of purified human α‐1 proteinase inhibitor (A1‐PI; 60 mg kg–1 week–1) therapy completed to date, demonstrated for the first time that A1‐PI is clinically effective in slowing lung tissue loss in AATD. A posthoc pharmacometric analysis was undertaken to further explore dose, exposure and response. Methods A disease progression model was constructed, utilizing observed A1‐PI exposure and lung density decline rates (measured by computed tomography) from RAPID‐RCT/RAPID‐OLE, to predict effects of population variability and higher doses on A1‐PI exposure and clinical response. Dose–exposure and exposure–response relationships were characterized using nonlinear and linear mixed effects models, respectively. The dose–exposure model predicts summary exposures and not individual concentration kinetics; covariates included baseline serum A1‐PI, forced expiratory volume in 1 s and body weight. The exposure–response model relates A1‐PI exposure to lung density decline rate at varying exposure levels. Results A dose of 60 mg kg–1 week–1 achieved trough serum levels >11 μmol l–1 (putative ‘protective threshold’) in ≥98% patients. Dose–exposure–response simulations revealed increasing separation between A1‐PI and placebo in the proportions of patients achieving higher reductions in lung density decline rate; improvements in decline rates ≥0.5 g l–1 year–1 occurred more often in patients receiving A1‐PI: 63 vs. 12%. Conclusion Weight‐based A1‐PI dosing reliably raises serum levels above the 11 μmol l–1 threshold. However, our exposure–response simulations question whether this is the maximal, clinically effective threshold for A1‐PI therapy in AATD. The model suggested higher doses of A1‐PI would yield greater clinical effects. PMID:28662542

Visible lesion laser thresholds in Cynomolgus (Macaca fascicularis) retina with a 1064 nm 12-ns pulsed laser

NASA Astrophysics Data System (ADS)

Oliver, Jeffrey W.; Stolarski, David J.; Noojin, Gary D.; Hodnett, Harvey M.; Imholte, Michelle L.; Rockwell, Benjamin A.; Kumru, Semih S.

2007-02-01

A series of experiments in a new animal model for retinal damage, cynomolgus monkeys (Macaca fascicularis), have been conducted to determine the damage threshold for 12.5-nanosecond laser exposures at 1064 nm. These results provide a direct comparison to threshold values obtained in rhesus monkey (Macaca mulatta), which is the model historically used in establishing retinal maximum permissible exposure (MPE) limits. In this study, the irradiance level of a collimated Gaussian laser beam of 2.5 mm diameter at the cornea was randomly varied to produce a rectangular grid of exposures on the retina. Exposures sites were fundoscopically evaluated at post-irradiance intervals of 1 hour and 24 hours. Probit analysis was performed on dose-response data to obtain probability of response curves. The 50% probability of damage (ED50) values for 1 and 24 hours post-exposure are 28.5(22.7-38.4) μJ and 17.0(12.9-21.8) μJ, respectively. These values compare favorably to data obtained with the rhesus model, 28.7(22.3-39.3) μJ and 19.1(13.6-24.4) μJ, suggesting that the cynomolgus monkey may be a suitable replacement for rhesus monkey in photoacoustic minimum visible lesion threshold studies.

Cytogenetic damages in peripheral blood of monkey lymphocytes under simulation of cosmonauts irradiation.

NASA Astrophysics Data System (ADS)

Petrov, Vladislav; Ivanov, Alexandr; Barteneva, Svetlana; Snigiryeva, Galina; Shafirkin, Alexandr

Earth modeling of crewmember exposure should be performed for correct estimating radiation hazard during the flight. Such modeling was planned in a monkey experiment for investigating consequences of exposure to a man during an interplanetary flight. It should reflect a chronic impact of galactic cosmic rays and acute and fractional irradiation specified for solar cosmic rays and radiation belts respectively. Due to the difficulty of modeling a chronic impact with the help of a charged particles accelerator it can be used the gamma source. While irradiating big animal groups during a long-term period of time it is preferably to replace chronic irradiation by an equal fractional one. In this case the chosen characteristics of fractional irradiation should ensure the appearances of radiobiological consequences equal to the ones caused by the modeled chronic exposure. So for developing an exposure scheme in the monkey experiment (with Macaca -Rhesus) the model of the acting residual dose, that takes into account repair and recovery processes in the exposed body was used. The total dose value was in the limits from 2.32 Gy up to 3.5 Gy depending on the exposure character. The acting residual dose in all versions of exposure was 2.0 Gy for every monkey. While performing the experiment all the requirements of bioethics for the work with animals were observed. The objects of interest were genomic damages in lymphocytes of monkey's peripheral blood. The data about the CAF during the exposure and at various time moments after exposure particularly directly after the completion of chronicle and fractional irradiation were analyzed. CAF -dose of acute single gamma-irradiation in the range 0 -1.5Gy relationship (calibration curve) was defined in vitro. In addition the rate of the aberrant cells elimination within three months after the irradiation completion was estimated. On the basis of the obtained CAF data we performed verification of applicability of cytogenetic analysis for estimating the monkey gamma -dose exposure in the experiment It was obtained that this method permits to estimate the acting residual dose with accuracy of 30

Early Indication of Noise-induced Hearing Loss from PMP Use in Adolescents: A Cross-Sectional Analysis

PubMed Central

Colon, Diana C.; Verdugo-Raab, Ulla; Alvarez, Carmelo P.; Steffens, Thomas; Marcrum, Steven C.; Kolb, Stefanie; Herr, Caroline; Twardella, Dorothee

2016-01-01

Context: Distortion product otoacoustic emissions (DPOAEs) may indicate preclinical noise-induced hearing loss (NIHL) in adolescents from unsafe personal music player (PMP) use. Aims: The objective, therefore, was to observe preclinical signs of NIHL in 9th grade adolescents with clinically normal hearing by comparing DPOAE signals between different levels of A-weighted equivalent PMP exposure. Settings and Design: Subjects were recruited from all secondary-level schools located in the city of Regensburg, Germany during two academic years 2009/2010 and 2010/2011. Subjects and Methods: A-weighted equivalent sound pressure levels (SPLs) for a 40-hour work week (LAeq,40h) were estimated from questionnaire responses on output and duration of PMP use of the previous week. Subjects were then categorized into four levels of exposure: <80, 80–85, >85 to <90, and ≥90 A-weighted Decibel [dB(A)]. DPOAE signals were collected by trained audiological staff, applying a standard optimized protocol, at the Department of Otorhinolaryngology of the University Hospital Regensburg. Statistical Analysis Used: Mean DPOAE signals were compared between levels by unpaired t test. Novel linear regression models adjusting for other leisure noise exposures and with outcome variables DPoutcome and 4 kilo Hertz (kHz) DPOAEs estimated effects between levels. Results: A total of 1468 subjects (56% female, mostly aged 15 or 16 years) were available for analysis. Comparison of DPOAE means by PMP exposure typically showed no greater than 1 dB difference between groups. In fact, comparisons between ≥90 dB(A) and <80 dB(A) presented the least differences in magnitude. Both DPoutcome and 4 kHz linear regression models presented a weak association with the 4-level PMP exposure variable. An expected dose-response to PMP exposure was not observed in any analyses. Conclusions: DPOAE signal strength alone cannot indicate preclinical NIHL in adolescents. PMID:27991459

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases.

PubMed

Imai, Chisato; Hashizume, Masahiro

2015-03-01

Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

A review of the cohorts with environmental and occupational mineral fiber exposure.

PubMed

Metintas, Selma; Ak, Guntulu; Metintas, Muzaffer

2018-04-20

The aim of the study was to examine factors associated with Malignant Mesothelioma (MM) incidence rate of the groups with occupational asbestos and environmental asbestos or erionite exposure in rural area. In this ecological study, a total of 21 cohort datasets (8 environmental and 13 occupational) were evaluated. Data were analyzed using a multiple linear regression analysis model. In environmental cohorts, the risk of MM incidence was higher in women and people exposed to erionite. In this cohort, the incidence rate of MM increased as the median exposure time increased, while the incidence decreased as the median cumulative exposure dose increased. In occupational cohorts, the incidence rate of MM was positively correlated with the median cumulative exposure dose. The risk of mesothelioma was lower in those exposed to tremolite than others. Environmental asbestos exposure is as important as occupational exposure to develop MM, and it has its own unique exposure features on the risk of MM.

Social stressors and air pollution across New York City communities: a spatial approach for assessing correlations among multiple exposures.

PubMed

Shmool, Jessie L C; Kubzansky, Laura D; Newman, Ogonnaya Dotson; Spengler, John; Shepard, Peggy; Clougherty, Jane E

2014-11-06

Recent toxicological and epidemiological evidence suggests that chronic psychosocial stress may modify pollution effects on health. Thus, there is increasing interest in refined methods for assessing and incorporating non-chemical exposures, including social stressors, into environmental health research, towards identifying whether and how psychosocial stress interacts with chemical exposures to influence health and health disparities. We present a flexible, GIS-based approach for examining spatial patterns within and among a range of social stressors, and their spatial relationships with air pollution, across New York City, towards understanding their combined effects on health. We identified a wide suite of administrative indicators of community-level social stressors (2008-2010), and applied simultaneous autoregressive models and factor analysis to characterize spatial correlations among social stressors, and between social stressors and air pollutants, using New York City Community Air Survey (NYCCAS) data (2008-2009). Finally, we provide an exploratory ecologic analysis evaluating possible modification of the relationship between nitrogen dioxide (NO2) and childhood asthma Emergency Department (ED) visit rates by social stressors, to demonstrate how the methods used to assess stressor exposure (and/or consequent psychosocial stress) may alter model results. Administrative indicators of a range of social stressors (e.g., high crime rate, residential crowding rate) were not consistently correlated (rho = - 0.44 to 0.89), nor were they consistently correlated with indicators of socioeconomic position (rho = - 0.54 to 0.89). Factor analysis using 26 stressor indicators suggested geographically distinct patterns of social stressors, characterized by three factors: violent crime and physical disorder, crowding and poor access to resources, and noise disruption and property crimes. In an exploratory ecologic analysis, these factors were differentially associated with area-average NO2 and childhood asthma ED visits. For example, only the 'violent crime and disorder' factor was significantly associated with asthma ED visits, and only the 'crowding and resource access' factor modified the association between area-level NO2 and asthma ED visits. This spatial approach enabled quantification of complex spatial patterning and confounding between chemical and non-chemical exposures, and can inform study design for epidemiological studies of separate and combined effects of multiple urban exposures.

Heating of tissues by microwaves: a model analysis.

PubMed

Foster, K R; Lozano-Nieto, A; Riu, P J; Ely, T S

1998-01-01

We consider the thermal response times for heating of tissue subject to nonionizing (microwave or infrared) radiation. The analysis is based on a dimensionless form of the bioheat equation. The thermal response is governed by two time constants: one (tau1) pertains to heat convection by blood flow, and is of the order of 20-30 min for physiologically normal perfusion rates; the second (tau2) characterizes heat conduction and varies as the square of a distance that characterizes the spatial extent of the heating. Two idealized cases are examined. The first is a tissue block with an insulated surface, subject to irradiation with an exponentially decreasing specific absorption rate, which models a large surface area of tissue exposed to microwaves. The second is a hemispherical region of tissue exposed at a spatially uniform specific absorption rate, which models localized exposure. In both cases, the steady-state temperature increase can be written as the product of the incident power density and an effective time constant tau(eff), which is defined for each geometry as an appropriate function of tau1 and tau2. In appropriate limits of the ratio of these time constants, the local temperature rise is dominated by conductive or convective heat transport. Predictions of the block model agree well with recent data for the thresholds for perception of warmth or pain from exposure to microwave energy. Using these concepts, we developed a thermal averaging time that might be used in standards for human exposure to microwave radiation, to limit the temperature rise in tissue from radiation by pulsed sources. We compare the ANSI exposure standards for microwaves and infrared laser radiation with respect to the maximal increase in tissue temperature that would be allowed at the maximal permissible exposures. A historical appendix presents the origin of the 6-min averaging time used in the microwave standard.

Developmental Fluoride Neurotoxicity: A Systematic Review and Meta-Analysis

PubMed Central

Sun, Guifan; Zhang, Ying; Grandjean, Philippe

2012-01-01

Background: Although fluoride may cause neurotoxicity in animal models and acute fluoride poisoning causes neurotoxicity in adults, very little is known of its effects on children’s neurodevelopment. Objective: We performed a systematic review and meta-analysis of published studies to investigate the effects of increased fluoride exposure and delayed neurobehavioral development. Methods: We searched the MEDLINE, EMBASE, Water Resources Abstracts, and TOXNET databases through 2011 for eligible studies. We also searched the China National Knowledge Infrastructure (CNKI) database, because many studies on fluoride neurotoxicity have been published in Chinese journals only. In total, we identified 27 eligible epidemiological studies with high and reference exposures, end points of IQ scores, or related cognitive function measures with means and variances for the two exposure groups. Using random-effects models, we estimated the standardized mean difference between exposed and reference groups across all studies. We conducted sensitivity analyses restricted to studies using the same outcome assessment and having drinking-water fluoride as the only exposure. We performed the Cochran test for heterogeneity between studies, Begg’s funnel plot, and Egger test to assess publication bias, and conducted meta-regressions to explore sources of variation in mean differences among the studies. Results: The standardized weighted mean difference in IQ score between exposed and reference populations was –0.45 (95% confidence interval: –0.56, –0.35) using a random-effects model. Thus, children in high-fluoride areas had significantly lower IQ scores than those who lived in low-fluoride areas. Subgroup and sensitivity analyses also indicated inverse associations, although the substantial heterogeneity did not appear to decrease. Conclusions: The results support the possibility of an adverse effect of high fluoride exposure on children’s neurodevelopment. Future research should include detailed individual-level information on prenatal exposure, neurobehavioral performance, and covariates for adjustment. PMID:22820538

Review and developments of dissemination models for airborne carbon fibers

NASA Technical Reports Server (NTRS)

Elber, W.

1980-01-01

Dissemination prediction models were reviewed to determine their applicability to a risk assessment for airborne carbon fibers. The review showed that the Gaussian prediction models using partial reflection at the ground agreed very closely with a more elaborate diffusion analysis developed for the study. For distances beyond 10,000 m the Gaussian models predicted a slower fall-off in exposure levels than the diffusion models. This resulting level of conservatism was preferred for the carbon fiber risk assessment. The results also showed that the perfect vertical-mixing models developed herein agreed very closely with the diffusion analysis for all except the most stable atmospheric conditions.

Variability in quartz exposure in the construction industry: implications for assessing exposure-response relations.

PubMed

Tjoe Nij, Evelyn; Höhr, Doris; Borm, Paul; Burstyn, Igor; Spierings, Judith; Steffens, Friso; Lumens, Mieke; Spee, Ton; Heederik, Dick

2004-03-01

The aims of this study were to determine implications of inter- and intraindividual variation in exposure to respirable (quartz) dust and of heterogeneity in dust characteristics for epidemiologic research in construction workers. Full-shift personal measurements (n = 67) from 34 construction workers were collected. The between-worker and day-to-day variances of quartz and respirable dust exposure were estimated using mixed models. Heterogeneity in dust characteristics was evaluated by electron microscopic analysis and electron spin resonance. A grouping strategy based on job title resulted in a 2- and 3.5-fold reduction in expected attenuation of a hypothetical exposure-response relation for respirable dust and quartz exposure, respectively, compared to an individual based approach. Material worked on explained most of the between-worker variance in respirable dust and quartz exposure. However, for risk assessment in epidemiology, grouping workers based on the materials they work on is not practical. Microscopic characterization of dust samples showed large quantities of aluminum silicates and large quantities of smaller particles, resulting in a D(50) between 1 and 2 microm. For risk analysis, job title can be used to create exposure groups, although error is introduced by the heterogeneity of dust produced by different construction workers activities and by the nonuniformity of exposure groups. A grouping scheme based on materials worked on would be superior, for both exposure and risk assessment, but is not practical when assessing past exposure. In dust from construction sites, factors are present that are capable of influencing the toxicological potency.

Neurodevelopmental Low-dose Bisphenol A Exposure Leads to Early Life-stage Hyperactivity and Learning Deficits in Adult Zebrafish

PubMed Central

Saili, Katerine S.; Corvi, Margaret M.; Weber, Daniel N.; Patel, Ami U.; Das, Siba R.; Przybyla, Jennifer; Anderson, Kim A.; Tanguay, Robert L.

2011-01-01

Developmental bisphenol A (BPA) exposure has been implicated in adverse behavior and learning deficits. The mode of action underlying these effects is unclear. The zebrafish model was employed to investigate the neurobehavioral effects of developmental bisphenol A (BPA) exposure. The objectives of this study were to identify whether low-dose, developmental BPA exposure affects larval zebrafish locomotor behavior and whether learning deficits occur in adults exposed during development. Two control compounds, 17β-estradiol (an estrogen receptor ligand) and GSK4716 (a synthetic estrogen related receptor gamma ligand), were included. Larval toxicity assays were used to determine appropriate BPA, 17β-estradiol, and GSK4716 concentrations for behavior testing. BPA tissue uptake was analyzed using HPLC and lower doses were extrapolated using a linear regression analysis. Larval behavior tests were conducted using a ViewPoint Zebrabox. Adult learning tests were conducted using a custom-built T-maze. BPA exposure to ≤30 μM was nonteratogenic in zebrafish. Neurodevelopmental BPA exposure to 0.01, 0.1, or 1 μM led to larval hyperactivity or learning deficits in adult zebrafish. Exposure to 0.1 μM 17β-estradiol or GSK4716 also led to larval hyperactivity. This study demonstrates the efficacy of using the larval zebrafish model for studying the neurobehavioral effects of low-dose developmental BPA exposure. PMID:22108044

Quantifying riverine and storm-surge flood risk by single-family residence: application to Texas.

PubMed

Czajkowski, Jeffrey; Kunreuther, Howard; Michel-Kerjan, Erwann

2013-12-01

The development of catastrophe models in recent years allows for assessment of the flood hazard much more effectively than when the federally run National Flood Insurance Program (NFIP) was created in 1968. We propose and then demonstrate a methodological approach to determine pure premiums based on the entire distribution of possible flood events. We apply hazard, exposure, and vulnerability analyses to a sample of 300,000 single-family residences in two counties in Texas (Travis and Galveston) using state-of-the-art flood catastrophe models. Even in zones of similar flood risk classification by FEMA there is substantial variation in exposure between coastal and inland flood risk. For instance, homes in the designated moderate-risk X500/B zones in Galveston are exposed to a flood risk on average 2.5 times greater than residences in X500/B zones in Travis. The results also show very similar average annual loss (corrected for exposure) for a number of residences despite their being in different FEMA flood zones. We also find significant storm-surge exposure outside of the FEMA designated storm-surge risk zones. Taken together these findings highlight the importance of a microanalysis of flood exposure. The process of aggregating risk at a flood zone level-as currently undertaken by FEMA-provides a false sense of uniformity. As our analysis indicates, the technology to delineate the flood risks exists today. © 2013 Society for Risk Analysis.

Exposure and Vulnerability Geospatial Analysis Using Earth Observation Data in the City of Liege, Belgium

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Lenartz, F.; Lefebre, F.; Lauwaet, D.; Poelmans, L.; Wolff, E.

2017-05-01

Risk situation can be mitigated by prevention measures, early warning tools and adequate monitoring of past experiences where Earth Observation and geospatial analysis have an adding value. This paper discusses the potential use of Earth Observation data and especially Land Cover / Land Use map in addressing within the three aspects of the risk assessment: danger, exposure and vulnerability. Evidences of the harmful effects of air pollution or heat waves are widely admitted and should increase in the context of global warming. Moreover, urban areas are generally warmer than rural surroundings, the so-called urban heat island. Combined with in-situ measurements, this paper presents models of city or local climate (air pollution and urban heat island), with a resolution of less than one kilometer, developed by integrating several sources of information including Earth Observation data and in particular Land Cover / Land Use. This assessment of the danger is then be related to a map of exposure and vulnerable people. Using dasymetric method to disaggregate statistical information on Land Cover / Land Use data, the SmartPop project analyzes in parallel the map of danger with the maps of people exposure A special focus on some categories at risk such as the elderly has been proposed by Aubrecht and Ozceylan (2013). Perspectives of the project includes the integration of a new Land Cover / Land Use map in the danger, exposure and vulnerability models and proposition of several aspects of risk assessment with the stakeholders of Wallonia.

Estimating associations of mobile phone use and brain tumours taking into account laterality: a comparison and theoretical evaluation of applied methods.

PubMed

Frederiksen, Kirsten; Deltour, Isabelle; Schüz, Joachim

2012-12-10

Estimating exposure-outcome associations using laterality information on exposure and on outcome is an issue, when estimating associations of mobile phone use and brain tumour risk. The exposure is localized; therefore, a potential risk is expected to exist primarily on the side of the head, where the phone is usually held (ipsilateral exposure), and to a lesser extent at the opposite side of the head (contralateral exposure). Several measures of the associations with ipsilateral and contralateral exposure, dealing with different sampling designs, have been presented in the literature. This paper presents a general framework for the analysis of such studies using a likelihood-based approach in a competing risks model setting. The approach clarifies the implicit assumptions required for the validity of the presented estimators, particularly that in some approaches the risk with contralateral exposure is assumed to be zero. The performance of the estimators is illustrated in a simulation study showing for instance that while in some scenarios there is a loss of statistical power, others - in case of a positive ipsilateral exposure-outcome association - would result in a negatively biased estimate of the contralateral exposure parameter, irrespective of any additional recall bias. In conclusion, our theoretical evaluations and results from the simulation study emphasize the importance of setting up a formal model, which furthermore allows for estimation in more complicated and perhaps more realistic exposure settings, such as taking into account exposure to both sides of the head. Copyright © 2012 John Wiley & Sons, Ltd.

Exposure Knowledge and Risk Perception of RF EMF

PubMed Central

Freudenstein, Frederik; Wiedemann, Peter M.; Varsier, Nadège

2015-01-01

The presented study is part of the EU-Project Low EMF Exposure Future Networks (LEXNET), which deals among other things with the issue of whether a reduction of the radiofrequency (RF) electro-magnetic fields (EMF) exposure will result in more acceptance of wireless communication networks in the public sphere. We assume that the effects of any reduction of EMF exposure will depend on the subjective link between exposure perception and risk perception (RP). Therefore we evaluated respondents’ RP of different RF EMF sources and their subjective knowledge about various exposure characteristics with regard to their impact on potential health risks. The results show that participants are more concerned about base stations than about all other RF EMF sources. Concerning the subjective exposure knowledge the results suggest that people have a quite appropriate impact model. The question how RF EMF RP is actually affected by the knowledge about the various exposure characteristics was tested in a linear regression analysis. The regression indicates that these features – except distance – do influence people’s general RF EMF RP. In addition, we analyzed the effect of the quality of exposure knowledge on RF EMF RP of various sources. The results show a tendency that better exposure knowledge leads to higher RP, especially for mobile phones. The study provides empirical support for models of the relationships between exposure perception and RP. It is not the aim to extrapolate these findings to the whole population because the samples are not exactly representative for the general public in the participating countries. PMID:25629026

Characterization of exposure in epidemiological studies on air pollution from biodegradable wastes: Misclassification and comparison of exposure assessment strategies.

PubMed

Cantuaria, Manuella Lech; Suh, Helen; Løfstrøm, Per; Blanes-Vidal, Victoria

2016-11-01

The assignment of exposure is one of the main challenges faced by environmental epidemiologists. However, misclassification of exposures has not been explored in population epidemiological studies on air pollution from biodegradable wastes. The objective of this study was to investigate the use of different approaches for assessing exposure to air pollution from biodegradable wastes by analyzing (1) the misclassification of exposure that is committed by using these surrogates, (2) the existence of differential misclassification (3) the effects that misclassification may have on health effect estimates and the interpretation of epidemiological results, and (4) the ability of the exposure measures to predict health outcomes using 10-fold cross validation. Four different exposure assessment approaches were studied: ammonia concentrations at the residence (Metric I), distance to the closest source (Metric II), number of sources within certain distances from the residence (Metric IIIa,b) and location in a specific region (Metric IV). Exposure-response models based on Metric I provided the highest predictive ability (72.3%) and goodness-of-fit, followed by IV, III and II. When compared to Metric I, Metric IV yielded the best results for exposure misclassification analysis and interpretation of health effect estimates, followed by Metric IIIb, IIIa and II. The study showed that modelled NH 3 concentrations provide more accurate estimations of true exposure than distances-based surrogates, and that distance-based surrogates (especially those based on distance to the closest point source) are imprecise methods to identify exposed populations, although they may be useful for initial studies. Copyright © 2016 Elsevier GmbH. All rights reserved.

LDEF materials data analysis: Representative examples

NASA Technical Reports Server (NTRS)

Pippin, H. Gary; Crutcher, E. R.

1992-01-01

Results of measurements on silverized teflon, heat shrink tubing and nylon tie downs on the wire harness clamps, silvered hex nuts, and contamination deposits are presented. We interpret the results in terms of our microenvironments exposure model and locations on the Long Duration Exposure Facility (LDEF). Distinct changes in the surface properties of FEP were observed as a function of UV exposure. Significant differences in outgassing characteristics were detected for hardware on the interior row 3 relative to identical hardware on the interior row 3 relative to identical hardware on nearby rows. The implications for in service performance are reviewed.

Prenatal Exposure to Perfluoroalkyl Substances and Behavioral Development in Children.

PubMed

Quaak, Ilona; de Cock, Marijke; de Boer, Michiel; Lamoree, Marja; Leonards, Pim; van de Bor, Margot

2016-05-19

In recent years, prevalence rates of behavioral disorders in children have increased. One factor possibly implied in the etiology of behavioral disorders is exposure to perfluoroalkyl substances (PFASs). The use of PFASs is highly integrated into everyday life, and exposure is ubiquitous. Exposure to PFASs during early life may be particularly harmful, as it represents a critical time window for brain development. However, research in the area is limited, especially among preschool children. The objective of the current study was to explore the relationship between prenatal exposure to several PFASs and behavioral development at the age of 18 months. Data from the Dutch cohort LINC (Linking Maternal Nutrition to Child Health) were used. Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord plasma. The total exposure of PFASs was also calculated (ΣPFASs). Behavioral development was assessed with the Child Behavior Checklist 1.5-5 (CBCL 1.5-5). The CBCL scales "Attention Deficit Hyperactivity Disorder" (ADHD) and "Externalizing problems" were used for further analysis. Separate regression models were composed for each combination, in which exposure levels were classified in tertiles. Both whole population and sex-stratified analyses were performed. A family history of ADHD, the educational level, smoking or using alcohol or illicit drugs during pregnancy were considered as confounders. In total, data from 76 mother-child pairs was included. No significant associations were found between prenatal PFAS exposure and ADHD scores in the whole population and in the sex-stratified analyses. With regard to externalizing behavior, a significant negative association was found between the highest levels of ΣPFAS exposure and externalizing problem behavior in the whole population, but only in the crude model. After stratifying for sex, boys in the second and third tertile of exposure to PFOA presented significantly lower scores on the Externalizing Problem Scale than boys with the lowest exposure levels in the adjusted model. Girls exposed to higher levels of ΣPFAS exposure (T2) showed significantly lower scores on the Externalizing Problem Scale, in both crude and adjusted models. No significant associations with PFOS were found. RESULTS from the current study show that prenatal exposure to PFOA was negatively related to externalizing behavior in boys. RESULTS were different for boys and girls, emphasizing that mechanisms at work might be sex-dependent. However, results should be interpreted with caution as the sample size was small.

Compilation of Published PM2.5 Emission Rates for Cooking, Candles and Incense for Use in Modeling of Exposures in Residences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Tianchao; Singer, Brett C.; Logue, Jennifer M.

2012-08-01

recent analysis of health impacts from air pollutant inhalation in homes found that PM2.5 is the most damaging at the population level. Chronic exposure to elevated PM2.5 has the potential to damage human respiratory systems, and may result in premature death. PM2.5 exposures in homes can be mitigated through various approaches including kitchen exhaust ventilation, filtration, indoor pollutant source reduction and designing ventilation systems to reduce the entry of PM2.5 from outdoors. Analysis of the potential benefits and costs of various approaches can be accomplished using computer codes that simulate the key physical processes including emissions, dilution and ventilation. Themore » largest sources of PM2.5 in residences broadly are entry from outdoors and emissions from indoor combustion. The largest indoor sources are tobacco combustion (smoking), cooking and the burning of candles and incense. Data on the magnitude of PM2.5 and other pollutant emissions from these events and processes are required to conduct simulations for analysis. The goal of this study was to produce a database of pollutant emission rates associated with cooking and the burning of candles and incense. The target use of these data is for indoor air quality modeling.« less

SAGE Analysis of Transcriptome Responses in Arabidopsis Roots Exposed to 2,4,6-Trinitrotoluene1

PubMed Central

Ekman, Drew R.; Lorenz, W. Walter; Przybyla, Alan E.; Wolfe, N. Lee; Dean, Jeffrey F.D.

2003-01-01

Serial analysis of gene expression was used to profile transcript levels in Arabidopsis roots and assess their responses to 2,4,6-trinitrotoluene (TNT) exposure. SAGE libraries representing control and TNT-exposed seedling root transcripts were constructed, and each was sequenced to a depth of roughly 32,000 tags. More than 19,000 unique tags were identified overall. The second most highly induced tag (27-fold increase) represented a glutathione S-transferase. Cytochrome P450 enzymes, as well as an ABC transporter and a probable nitroreductase, were highly induced by TNT exposure. Analyses also revealed an oxidative stress response upon TNT exposure. Although some increases were anticipated in light of current models for xenobiotic metabolism in plants, evidence for unsuspected conjugation pathways was also noted. Identifying transcriptome-level responses to TNT exposure will better define the metabolic pathways plants use to detoxify this xenobiotic compound, which should help improve phytoremediation strategies directed at TNT and other nitroaromatic compounds. PMID:14551330

Exposomics research using suspect screening and non ...

EPA Pesticide Factsheets

High-resolution mass spectrometry (HRMS) is used for suspect screening (SSA) and non-targeted analysis (NTA) in an attempt to characterize xenobiotic chemicals in various samples broadly and efficiently. These important techniques aid characterization of the exposome, the totality of human exposures, and provide critical information on thousands of chemicals in commerce for which exposure data are lacking. The Environmental Protection Agency (EPA) SSA and NTA capabilities consist of analytical instrumentation [liquid chromatography (LC) with time of flight (TOF) and quadrupole-TOF (Q-TOF) HRMS], workflows (feature extraction, formula generation, structure prediction, spectral matching, chemical confirmation), and tools (databases; models for predicting retention time, functional use, media occurrence, and media concentration; and schemes for ranking features and chemicals). Suspect screening (SSA) and non-targeted analysis (NTA) are used to characterize xenobiotic chemicals in various samples and aid characterization of the exposome, the totality of human exposures, and provide critical information on thousands of chemicals in commerce for which exposure data are lacking.

Developmental cigarette smoke exposure II: Hepatic proteome profiles in 6 month old adult offspring.

PubMed

Neal, Rachel E; Chen, Jing; Webb, Cindy; Stocke, Kendall; Gambrell, Caitlin; Greene, Robert M; Pisano, M Michele

2016-10-01

Utilizing a mouse model of 'active' developmental cigarette smoke exposure (CSE) [gestational day (GD) 1 through postnatal day (PD) 21] characterized by offspring low birth weight, the impact of developmental CSE on liver proteome profiles of adult offspring at 6 months of age was determined. Liver tissue was collected from Sham- and CSE-offspring for 2D-SDS-PAGE based proteome analysis with Partial Least Squares-Discriminant Analysis (PLS-DA). A similar study conducted at the cessation of exposure to cigarette smoke documented decreased gluconeogenesis coupled to oxidative stress in weanling offspring. In the current study, exposure throughout development to cigarette smoke resulted in impaired hepatic carbohydrate metabolism, decreased serum glucose levels, and increased gluconeogenic regulatory enzyme abundances during the fed-state coupled to decreased expression of SIRT1 as well as increased PEPCK and PGC1α expression. Together these findings indicate inappropriately timed gluconeogenesis that may reflect impaired insulin signaling in mature offspring exposed to 'active' developmental CSE. Copyright © 2016 Elsevier Inc. All rights reserved.

Relationship between mediation analysis and the structured life course approach.

PubMed

Howe, Laura D; Smith, Andrew D; Macdonald-Wallis, Corrie; Anderson, Emma L; Galobardes, Bruna; Lawlor, Debbie A; Ben-Shlomo, Yoav; Hardy, Rebecca; Cooper, Rachel; Tilling, Kate; Fraser, Abigail

2016-08-01

Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome). © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Inverse odds ratio-weighted estimation for causal mediation analysis.

PubMed

Tchetgen Tchetgen, Eric J

2013-11-20

An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio-weighted approach to estimate so-called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.

Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China

NASA Astrophysics Data System (ADS)

Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song

2017-06-01

Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.

Using landscape analysis to assess and model tsunami damage in Aceh province, Sumatra

Treesearch

Louis R. Iverson; Anantha Prasad

2007-01-01

The nearly unprecedented loss of life resulting from the earthquake and tsunami of December 26,2004, was greatest in the province of Aceh, Sumatra (Indonesia). We evaluated tsunami damage and built empirical vulnerability models of damage/no damage based on elevation, distance from shore, vegetation, and exposure. We found that highly predictive models are possible and...

Economic Costs of Childhood Lead Exposure in Low- and Middle-Income Countries

PubMed Central

Trasande, Leonardo

2013-01-01

Background: Children’s blood lead levels have declined worldwide, especially after the removal of lead in gasoline. However, significant exposure remains, particularly in low- and middle-income countries. To date, there have been no global estimates of the costs related to lead exposure in children in developing countries. Objective: Our main aim was to estimate the economic costs attributable to childhood lead exposure in low- and middle-income countries. Methods: We developed a regression model to estimate mean blood lead levels in our population of interest, represented by each 1-year cohort of children < 5 years of age. We used an environmentally attributable fraction model to estimate lead-attributable economic costs and limited our analysis to the neurodevelopmental impacts of lead, assessed as decrements in IQ points. Our main outcome was lost lifetime economic productivity due to early childhood exposure. Results: We estimated a total cost of $977 billions of international dollars in low- and middle-income countries, with economic losses equal to $134.7 billion in Africa [4.03% of gross domestic product (GDP)], $142.3 billion in Latin America and the Caribbean (2.04% of GDP), and $699.9 billion in Asia (1.88% of GDP). Our sensitivity analysis indicates a total economic loss in the range of $728.6–1162.5 billion. Conclusions: We estimated that, in low- and middle-income countries, the burden associated with childhood lead exposure amounts to 1.20% of world GDP in 2011. For comparison, in the United States and Europe lead-attributable economic costs have been estimated at $50.9 and $55 billion, respectively, suggesting that the largest burden of lead exposure is now borne by low- and middle-income countries. Citation: Attina TM, Trasande L. 2013. Economic costs of childhood lead exposure in low- and middle-income countries. Environ Health Perspect 121:1097–1102; http://dx.doi.org/10.1289/ehp.1206424 PMID:23797342

Laparoscopy and tribology: the effect of laparoscopic gas on peritoneal fluid.

PubMed

Ott, D E

2001-02-01

To assess the changes in viscosity of peritoneal fluid during laparoscopic exposure to CO2 insufflation. Analysis and mathematic modeling of peritoneal fluid viscosity in vivo and in vitro as a result of exposure to unconditioned CO2 (Canadian Task Force classification II-2). Medical school university research laboratory and hospital. Peritoneal fluid from 45 women. Peritoneal fluid was obtained at laparoscopy before insufflation and tested for viscosity after exposure to currently used raw dry unconditioned CO2. Peritoneal fluid viscosity was tested by viscometric methods and mathematic modeling. Initial viscosity of peritoneal fluid before gas exposure was 1.425 centipoise (cP). Viscosity measurements were obtained at 20-second intervals for gas flows of 1 and 3 L/minute. Increases in viscosity occur rapidly, and by 200 seconds it was 59 cP and 98 cP for 1 and 3 L flow rates, respectively. Very dry CO2 for laparoscopy causes peritoneal fluid viscosity to increase dramatically. (J Am Assoc Gynecol Laparosc 8(1):117-123, 2001)

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

PubMed

Salis, Michele; Ager, Alan A; Alcasena, Fermin J; Arca, Bachisio; Finney, Mark A; Pellizzaro, Grazia; Spano, Donatella

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Needlestick and other potential blood and body fluid exposures among health care workers in British Columbia, Canada.

PubMed

Alamgir, Hasanat; Cvitkovich, Yuri; Astrakianakis, George; Yu, Shicheng; Yassi, Annalee

2008-02-01

Health care workers have high risk of exposure to human blood and body fluids (BBF) from patients in acute care and residents in nursing homes or personal homes. This analysis examined the epidemiology for BBF exposure across health care settings (acute care, nursing homes, and community care). Detailed analysis of BBF exposure among the health care workforce in 3 British Columbian health regions was conducted by Poisson regression modeling, with generalized estimating equations to determine the relative risk associated with various occupations. Acute care had the majority of needlestick, sharps, and splash events with the BBF exposure rate in acute care 2 to 3 times higher compared with nursing home and community care settings. Registered nurses had the highest frequency of needlestick, sharps, and splash events. Laboratory assistants had the highest exposure rates from needlestick injuries and splashes, whereas licensed practical nurses had the highest exposure rate from sharps. Most needlestick injuries (51.3%) occurred at the patient's bedside. Sharps incidents occurred primarily in operating rooms (26.9%) and at the patient's bedside (20.9%). Splashes occurred most frequently at the patient's bedside (46.1%) and predominantly affected the eyes or face/mouth. The majority of needlestick/sharps injuries occurred during use for registered nurses, during disposal for licensed practical nurses, and after disposal for care aides. The high risk of BBF exposure for some occupations indicates there is room for improvement to reduce BBF exposure by targeting high-risk groups for prevention strategies.

Space Radiation Cancer Risk Projections and Uncertainties - 2010

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Kim, Myung-Hee Y.; Chappell, Lori J.

2011-01-01

Uncertainties in estimating health risks from galactic cosmic rays greatly limit space mission lengths and potential risk mitigation evaluations. NASA limits astronaut exposures to a 3% risk of exposure-induced death and protects against uncertainties using an assessment of 95% confidence intervals in the projection model. Revisions to this model for lifetime cancer risks from space radiation and new estimates of model uncertainties are described here. We review models of space environments and transport code predictions of organ exposures, and characterize uncertainties in these descriptions. We summarize recent analysis of low linear energy transfer radio-epidemiology data, including revision to Japanese A-bomb survivor dosimetry, longer follow-up of exposed cohorts, and reassessments of dose and dose-rate reduction effectiveness factors. We compare these projections and uncertainties with earlier estimates. Current understanding of radiation quality effects and recent data on factors of relative biological effectiveness and particle track structure are reviewed. Recent radiobiology experiment results provide new information on solid cancer and leukemia risks from heavy ions. We also consider deviations from the paradigm of linearity at low doses of heavy ions motivated by non-targeted effects models. New findings and knowledge are used to revise the NASA risk projection model for space radiation cancer risks.

Occupational COPD and job exposure matrices: a systematic review and meta-analysis

PubMed Central

Sadhra, Steven; Kurmi, Om P; Sadhra, Sandeep S; Lam, Kin Bong Hubert; Ayres, Jon G

2017-01-01

Background The association between occupational exposure and COPD reported previously has mostly been derived from studies relying on self-reported exposure to vapors, gases, dust, or fumes (VGDF), which could be subjective and prone to biases. The aim of this study was to assess the strength of association between exposure and COPD from studies that derived exposure by job exposure matrices (JEMs). Methods A systematic search of JEM-based occupational COPD studies published between 1980 and 2015 was conducted in PubMed and EMBASE, followed by meta-analysis. Meta-analysis was performed using a random-effects model, with results presented as a pooled effect estimate with 95% confidence intervals (CIs). The quality of study (risk of bias and confounding) was assessed by 13 RTI questionnaires. Heterogeneity between studies and its possible sources were assessed by Egger test and meta-regression, respectively. Results In all, 61 studies were identified and 29 were included in the meta-analysis. Based on JEM-based studies, there was 22% (pooled odds ratio =1.22; 95% CI 1.18–1.27) increased risk of COPD among those exposed to airborne pollutants arising from occupation. Comparatively, higher risk estimates were obtained for general populations JEMs (based on expert consensus) than workplace-based JEM were derived using measured exposure data (1.26; 1.20–1.33 vs 1.14; 1.10–1.19). Higher risk estimates were also obtained for self-reported exposure to VGDF than JEMs-based exposure to VGDF (1.91; 1.72–2.13 vs 1.10; 1.06–1.24). Dusts, particularly biological dusts (1.33; 1.17–1.51), had the highest risk estimates for COPD. Although the majority of occupational COPD studies focus on dusty environments, no difference in risk estimates was found for the common forms of occupational airborne pollutants. Conclusion Our findings highlight the need to interpret previous studies with caution as self-reported exposure to VGDF may have overestimated the risk of occupational COPD. PMID:28260879

Radiation Quality Effects on Transcriptome Profiles in 3-D Cultures After Charged Particle Irradiation

NASA Technical Reports Server (NTRS)

Patel, Zarana S.; Kidane, Yared H.; Huff, Janice L.

2014-01-01

In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.

The relationship between occupational noise and vibration exposure and headache/eyestrain, based on the fourth Korean Working Condition Survey (KWCS).

PubMed

Kim, Jihyun; Lee, Wanhyung; Won, Jong-Uk; Yoon, Jin-Ha; Seok, Hongdeok; Kim, Yeong-Kwang; Lee, Seunghyun; Roh, Jaehoon

2017-01-01

The individual and combined effect of occupational noise and vibration exposures, on workers' health has not been thoroughly investigated. In order to find better ways to prevent and manage workers' headache, this study aimed to investigate the effects of occupational noise and vibration exposure on headache/eyestrain. We used data from the fourth Korean Working Condition Survey (2014). After applying inclusion and exclusion criteria, 25,751 workers were included. Occupational noise and vibration exposure and the prevalence of headache/eyestrain were investigated by self-reported survey. Chi-square tests were used to compare differences in baseline characteristics between the group with headache/eyestrain and the group without. Odds ratios and 95% confidence intervals were estimated using a logistic regression model adjusted for several covariates. Area under the receiver operating characteristics curve (AUROC) analysis was used to evaluate the effect of occupational noise and/or vibration exposure. Among the 25,751 study subjects, 4,903 had experienced headache/eyestrain in the preceding year. There were significant differences in age, education level, household income, occupational classification, shift work, occupational vibration exposure, and occupational noise exposure between the two groups (all p<0.05). The odds ratios between each exposure and headache/eyestrain increased proportionally with the level of exposure, increasing from 1.08 to 1.26 with increasing vibration exposure, and from 1.25 to 1.41 with increasing noise exposure. According to the AUROC analysis, the predictive power of each exposure was significant, and increased when the two exposures were considered in combination. The findings of this study show that both occupational noise and vibration exposures are associated with headache/eyestrain; noise exposure more strongly so. However, when the two exposures are considered in combination, the explanatory power for headache/eyestrain is increased. Therefore, efforts aimed at reducing and managing occupational noise and vibration exposure are crucial to maintaining workers' health.

The relationship between occupational noise and vibration exposure and headache/eyestrain, based on the fourth Korean Working Condition Survey (KWCS)

PubMed Central

Kim, Jihyun; Lee, Wanhyung; Won, Jong-Uk; Yoon, Jin-Ha; Seok, Hongdeok; Kim, Yeong-Kwang; Lee, Seunghyun

2017-01-01

Introduction The individual and combined effect of occupational noise and vibration exposures, on workers’ health has not been thoroughly investigated. In order to find better ways to prevent and manage workers’ headache, this study aimed to investigate the effects of occupational noise and vibration exposure on headache/eyestrain. Methods We used data from the fourth Korean Working Condition Survey (2014). After applying inclusion and exclusion criteria, 25,751 workers were included. Occupational noise and vibration exposure and the prevalence of headache/eyestrain were investigated by self-reported survey. Chi-square tests were used to compare differences in baseline characteristics between the group with headache/eyestrain and the group without. Odds ratios and 95% confidence intervals were estimated using a logistic regression model adjusted for several covariates. Area under the receiver operating characteristics curve (AUROC) analysis was used to evaluate the effect of occupational noise and/or vibration exposure. Results Among the 25,751 study subjects, 4,903 had experienced headache/eyestrain in the preceding year. There were significant differences in age, education level, household income, occupational classification, shift work, occupational vibration exposure, and occupational noise exposure between the two groups (all p<0.05). The odds ratios between each exposure and headache/eyestrain increased proportionally with the level of exposure, increasing from 1.08 to 1.26 with increasing vibration exposure, and from 1.25 to 1.41 with increasing noise exposure. According to the AUROC analysis, the predictive power of each exposure was significant, and increased when the two exposures were considered in combination. Discussion The findings of this study show that both occupational noise and vibration exposures are associated with headache/eyestrain; noise exposure more strongly so. However, when the two exposures are considered in combination, the explanatory power for headache/eyestrain is increased. Therefore, efforts aimed at reducing and managing occupational noise and vibration exposure are crucial to maintaining workers’ health. PMID:28542287

Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

PubMed Central

Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E.; Harper, Martin

2015-01-01

This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure. PMID:23252451

Stressful working conditions and poor self-rated health among financial services employees.

PubMed

Silva, Luiz Sérgio; Barreto, Sandhi Maria

2012-06-01

To assess the association between exposure to adverse psychosocial working conditions and poor self-rated health among bank employees. A cross-sectional study including a sample of 2,054 employees of a government bank was conducted in 2008. Self-rated health was assessed by a single question: "In general, would you say your health is (...)." Exposure to adverse psychosocial working conditions was evaluated by the effort-reward imbalance model and the demand-control model. Information on other independent variables was obtained through a self-administered semi-structured questionnaire. A multiple logistic regression analysis was performed and odds ratio calculated to assess independent associations between adverse psychosocial working conditions and poor self-rated health. The overall prevalence of poor self-rated health was 9%, with no significant gender difference. Exposure to high demand and low control environment at work was associated with poor self-rated health. Employees with high effort-reward imbalance and overcommitment also reported poor self-rated health, with a dose-response relationship. Social support at work was inversely related to poor self-rated health, with a dose-response relationship. Exposure to adverse psychosocial work factors assessed based on the effort-reward imbalance model and the demand-control model is independently associated with poor self-rated health among the workers studied.

Vaccinating women previously exposed to human papillomavirus: a cost-effectiveness analysis of the bivalent vaccine.

PubMed

Turner, Hugo C; Baussano, Iacopo; Garnett, Geoff P

2013-01-01

Recent trials have indicated that women with prior exposure to Human papillomavirus (HPV) subtypes 16/18 receive protection against reinfection from the HPV vaccines. However, many of the original models investigating the cost effectiveness of different vaccination strategies for the protection of cervical cancer assumed, based on the trial results at that time, that these women received no protection. We developed a deterministic, dynamic transmission model that incorporates the vaccine-induced protection of women with prior exposure to HPV. The model was used to estimate the cost effectiveness of progressively extending a vaccination programme using the bivalent vaccine to older age groups both with and without protection of women with prior exposure. We did this under a range of assumptions on the level of natural immunity. Our modelling projections indicate that including the protection of women with prior HPV exposure can have a profound effect on the cost effectiveness of vaccinating adults. The impact of this protection is inversely related to the level of natural immunity. Our results indicate that adult vaccination strategies should potentially be reassessed, and that it is important to include the protection of non-naive women previously infected with HPV in future studies. Furthermore, they also highlight the need for a more thorough investigation of this protection.

FDTD analysis of temperature elevation in the lens of human and rabbit models due to near-field and far-field exposures at 2.45 GHz.

PubMed

Oizumi, Takuya; Laakso, Ilkka; Hirata, Akimasa; Fujiwara, Osamu; Watanabe, Soichi; Taki, Masao; Kojima, Masami; Sasaki, Hiroshi; Sasaki, Kazuyuki

2013-07-01

The eye is said to be one of the most sensitive organs to microwave heating. According to previous studies, the possibility of microwave-induced cataract formation has been experimentally investigated in rabbit and monkey eyes, but not for the human eye due to ethical reasons. In the present study, the temperature elevation in the lens, the skin around the eye and the core temperature of numerical human and rabbit models for far-field and near-field exposures at 2.45 GHz are investigated. The temperature elevations in the human and rabbit models were compared with the threshold temperatures for inducing cataracts, thermal pain in the skin and reversible health effects such as heat exhaustion or heat stroke. For plane-wave exposure, the core temperature elevation is shown to be essential both in the human and in the rabbit models as suggested in the international guidelines and standards. For localised exposure of the human eye, the temperature elevation of the skin was essential, and the lens temperature did not reach its threshold for thermal pain. On the other hand, the lens temperature elevation was found to be dominant for the rabbit eye.

Risk assessment of consuming agricultural products irrigated with reclaimed wastewater: An exposure model

NASA Astrophysics Data System (ADS)

van Ginneken, Meike; Oron, Gideon

2000-09-01

This study assesses health risks to consumers due to the use of agricultural products irrigated with reclaimed wastewater. The analysis is based on a definition of an exposure model which takes into account several parameters: (1) the quality of the applied wastewater, (2) the irrigation method, (3) the elapsed times between irrigation, harvest, and product consumption, and (4) the consumers' habits. The exposure model is used for numerical simulation of human consumers' risks using the Monte Carlo simulation method. The results of the numerical simulation show large deviations, probably caused by uncertainty (impreciseness in quality of input data) and variability due to diversity among populations. There is a 10-orders of magnitude difference in the risk of infection between the different exposure scenarios with the same water quality. This variation indicates the need for setting risk-based criteria for wastewater reclamation rather than single water quality guidelines. Extra data are required to decrease uncertainty in the risk assessment. Future research needs to include definition of acceptable risk criteria, more accurate dose-response modeling, information regarding pathogen survival in treated wastewater, additional data related to the passage of pathogens into and in the plants during irrigation, and information regarding the behavior patterns of the community of human consumers.

Spatial modeling of personalized exposure dynamics: the case of pesticide use in small-scale agricultural production landscapes of the developing world.

PubMed

Leyk, Stefan; Binder, Claudia R; Nuckols, John R

2009-03-30

Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America. Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research. This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions. The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.

Levels and predictors of airborne and internal exposure to chromium and nickel among welders--results of the WELDOX study.

PubMed

Weiss, Tobias; Pesch, Beate; Lotz, Anne; Gutwinski, Eleonore; Van Gelder, Rainer; Punkenburg, Ewald; Kendzia, Benjamin; Gawrych, Katarzyna; Lehnert, Martin; Heinze, Evelyn; Hartwig, Andrea; Käfferlein, Heiko U; Hahn, Jens-Uwe; Brüning, Thomas

2013-03-01

The objective of this analysis was to investigate levels and determinants of exposure to airborne and urinary chromium (Cr, CrU) and nickel (Ni, NiU) among 241 welders. Respirable and inhalable welding fume was collected during a shift, and the metal content was determined using inductively coupled plasma mass spectrometry. In post-shift urine, CrU and NiU were measured by means of graphite furnace atom absorption spectrometry, with resulting concentrations varying across a wide range. Due to a large fraction below the limits of quantitation we applied multiple imputations to the log-transformed exposure variables for the analysis of the data. Respirable Cr and Ni were about half of the concentrations of inhalable Cr and Ni, respectively. CrU and NiU were determined with medians of 1.2 μg/L (interquartile range <1.00; 3.61) and 2.9 μg/L (interquartile range <1.50; 5.97). Furthermore, Cr and Ni correlated in respirable welding fume (r=0.79, 95% CI 0.74-0.85) and urine (r=0.55, 95% CI 0.44-0.65). Regression models identified exposure-modulating variables in form of multiplicative factors and revealed slightly better model fits for Cr (R(2) respirable Cr 48%, CrU 55%) than for Ni (R(2) respirable Ni 42%, NiU 38%). The air concentrations were mainly predicted by the metal content in electrodes or base material in addition to the welding technique. Respirable Cr and Ni were good predictors for CrU and NiU, respectively. Exposure was higher when welding was performed in confined spaces or with inefficient ventilation, and lower in urine when respirators were used. In conclusion, statistical modelling allowed the evaluation of determinants of internal and external exposure to Cr and Ni in welders. Welding parameters were stronger predictors than workplace conditions. Airborne exposure was lowest inside respirators with supply of purified air. Copyright © 2012 Elsevier GmbH. All rights reserved.

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Personal Exposure to Mixtures of Volatile Organic Compounds: Modeling and Further Analysis of the RIOPA Data

PubMed Central

Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

2015-01-01

INTRODUCTION Emission sources of volatile organic compounds (VOCs) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are known to affect VOC exposures, many personal, environmental, and socioeconomic determinants remain to be identified, and the significance and applicability of the determinants reported in the literature are uncertain. To help answer these unresolved questions and overcome limitations of previous analyses, this project used several novel and powerful statistical modeling and analysis techniques and two large data sets. The overall objectives of this project were (1) to identify and characterize exposure distributions (including extreme values), (2) evaluate mixtures (including dependencies), and (3) identify determinants of VOC exposure. METHODS VOC data were drawn from two large data sets: the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study (1999–2001) and the National Health and Nutrition Examination Survey (NHANES; 1999–2000). The RIOPA study used a convenience sample to collect outdoor, indoor, and personal exposure measurements in three cities (Elizabeth, NJ; Houston, TX; Los Angeles, CA). In each city, approximately 100 households with adults and children who did not smoke were sampled twice for 18 VOCs. In addition, information about 500 variables associated with exposure was collected. The NHANES used a nationally representative sample and included personal VOC measurements for 851 participants. NHANES sampled 10 VOCs in common with RIOPA. Both studies used similar sampling methods and study periods. Specific Aim 1 To estimate and model extreme value exposures, extreme value distribution models were fitted to the top 10% and 5% of VOC exposures. Health risks were estimated for individual VOCs and for three VOC mixtures. Simulated extreme value data sets, generated for each VOC and for fitted extreme value and lognormal distributions, were compared with measured concentrations (RIOPA observations) to evaluate each model’s goodness of fit. Mixture distributions were fitted with the conventional finite mixture of normal distributions and the semi-parametric Dirichlet process mixture (DPM) of normal distributions for three individual VOCs (chloroform, 1,4-DCB, and styrene). Goodness of fit for these full distribution models was also evaluated using simulated data. Specific Aim 2 Mixtures in the RIOPA VOC data set were identified using positive matrix factorization (PMF) and by toxicologic mode of action. Dependency structures of a mixture’s components were examined using mixture fractions and were modeled using copulas, which address correlations of multiple components across their entire distributions. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) were evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks were calculated for mixtures, and results from copulas and multivariate lognormal models were compared with risks based on RIOPA observations. Specific Aim 3 Exposure determinants were identified using stepwise regressions and linear mixed-effects models (LMMs). RESULTS Specific Aim 1 Extreme value exposures in RIOPA typically were best fitted by three-parameter generalized extreme value (GEV) distributions, and sometimes by the two-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extreme values. Among the VOCs measured in RIOPA, 1,4-dichlorobenzene (1,4-DCB) was associated with the greatest cancer risks; for example, for the highest 10% of measurements of 1,4-DCB, all individuals had risk levels above 10−4, and 13% of all participants had risk levels above 10−2. Of the full-distribution models, the finite mixture of normal distributions with two to four clusters and the DPM of normal distributions had superior performance in comparison with the lognormal models. DPM distributions provided slightly better fit than the finite mixture distributions; the advantages of the DPM model were avoiding certain convergence issues associated with the finite mixture distributions, adaptively selecting the number of needed clusters, and providing uncertainty estimates. Although the results apply to the RIOPA data set, GEV distributions and mixture models appear more broadly applicable. These models can be used to simulate VOC distributions, which are neither normally nor lognormally distributed, and they accurately represent the highest exposures, which may have the greatest health significance. Specific Aim 2 Four VOC mixtures were identified and apportioned by PMF; they represented gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection byproducts, and cleaning products and odorants. The last mixture (cleaning products and odorants) accounted for the largest fraction of an individual’s total exposure (average of 42% across RIOPA participants). Often, a single compound dominated a mixture but the mixture fractions were heterogeneous; that is, the fractions of the compounds changed with the concentration of the mixture. Three VOC mixtures were identified by toxicologic mode of action and represented VOCs associated with hematopoietic, liver, and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10−3 for about 10% of RIOPA participants. The dependency structures of the VOC mixtures in the RIOPA data set fitted Gumbel (two mixtures) and t copulas (four mixtures). These copula types emphasize dependencies found in the upper and lower tails of a distribution. The copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy and performed better than multivariate lognormal distributions. Specific Aim 3 In an analysis focused on the home environment and the outdoor (close to home) environment, home VOC concentrations dominated personal exposures (66% to 78% of the total exposure, depending on VOC); this was largely the result of the amount of time participants spent at home and the fact that indoor concentrations were much higher than outdoor concentrations for most VOCs. In a different analysis focused on the sources inside the home and outside (but close to the home), it was assumed that 100% of VOCs from outside sources would penetrate the home. Outdoor VOC sources accounted for 5% (d-limonene) to 81% (carbon tetrachloride [CTC]) of the total exposure. Personal exposure and indoor measurements had similar determinants depending on the VOC. Gasoline-related VOCs (e.g., benzene and methyl tert-butyl ether [MTBE]) were associated with city, residences with attached garages, pumping gas, wind speed, and home air exchange rate (AER). Odorant and cleaning-related VOCs (e.g., 1,4-DCB and chloroform) also were associated with city, and a residence’s AER, size, and family members showering. Dry-cleaning and industry-related VOCs (e.g., tetrachloroethylene [or perchloroethylene, PERC] and trichloroethylene [TCE]) were associated with city, type of water supply to the home, and visits to the dry cleaner. These and other relationships were significant, they explained from 10% to 40% of the variance in the measurements, and are consistent with known emission sources and those reported in the literature. Outdoor concentrations of VOCs had only two determinants in common: city and wind speed. Overall, personal exposure was dominated by the home setting, although a large fraction of indoor VOC concentrations were due to outdoor sources. City of residence, personal activities, household characteristics, and meteorology were significant determinants. Concentrations in RIOPA were considerably lower than levels in the nationally representative NHANES for all VOCs except MTBE and 1,4-DCB. Differences between RIOPA and NHANES results can be explained by contrasts between the sampling designs and staging in the two studies, and by differences in the demographics, smoking, employment, occupations, and home locations. A portion of these differences are due to the nature of the convenience (RIOPA) and representative (NHANES) sampling strategies used in the two studies. CONCLUSIONS Accurate models for exposure data, which can feature extreme values, multiple modes, data below the MDL, heterogeneous interpollutant dependency structures, and other complex characteristics, are needed to estimate exposures and risks and to develop control and management guidelines and policies. Conventional and novel statistical methods were applied to data drawn from two large studies to understand the nature and significance of VOC exposures. Both extreme value distributions and mixture models were found to provide excellent fit to single VOC compounds (univariate distributions), and copulas may be the method of choice for VOC mixtures (multivariate distributions), especially for the highest exposures, which fit parametric models poorly and which may represent the greatest health risk. The identification of exposure determinants, including the influence of both certain activities (e.g., pumping gas) and environments (e.g., residences), provides information that can be used to manage and reduce exposures. The results obtained using the RIOPA data set add to our understanding of VOC exposures and further investigations using a more representative population and a wider suite of VOCs are suggested to extend and generalize results. PMID:25145040

Constraining parameters of the neutron star in the supernova remnant HESS J1731-347

NASA Astrophysics Data System (ADS)

Klochkov, D.; Suleimanov, V.; Puehlhofer, G.; Werner, K.; Santangelo, A.

2014-07-01

The Central Compact Object (CCO) in HESS J1731-347, presumably a neutron star, is one of the brightest sources in this class. Like other CCOs, it potentially provides an "undisturbed" view of thermal radiation generated at the neutron star surface. The shape and normalization of the corresponding X-ray spectrum depends on the emitting area, surface redshift, and gravity acceleration. Thus, its modeling under certain assumptions allows the mass and radius of the neutron star to be constrained. In our analysis, we model the spectrum of the CCO accumulated with XMM-Newton over ˜100 ksec exposure time in three observations. The exposure time has increased by a factor of five since our previous analysis of the source. For the spectral fitting, we use our hydrogen and carbon atmosphere models calculated assuming hydrostatic and radiative equilibria and taking into account pressure ionization and the presence of spectral lines (in case of carbon). We present the resulting constraints on the mass, radius, distance, and temperature of the neutron star.

Social inequalities in residential exposure to road traffic noise: an environmental justice analysis based on the RECORD Cohort Study.

PubMed

Havard, Sabrina; Reich, Brian J; Bean, Kathy; Chaix, Basile

2011-05-01

To explore social inequalities in residential exposure to road traffic noise in an urban area. Environmental injustice in road traffic noise exposure was investigated in Paris, France, using the RECORD Cohort Study (n = 2130) and modelled noise data. Associations were assessed by estimating noise exposure within the local area around participants' residence, considering various socioeconomic variables defined at both individual and neighbourhood level, and comparing different regression models attempting or not to control for spatial autocorrelation in noise levels. After individual-level adjustment, participants' noise exposure increased with neighbourhood educational level and dwelling value but also with proportion of non-French citizens, suggesting seemingly contradictory findings. However, when country of citizenship was defined according to its human development level, noise exposure in fact increased and decreased with the proportions of citizens from advantaged and disadvantaged countries, respectively. These findings were consistent with those reported for the other socioeconomic characteristics, suggesting higher road traffic noise exposure in advantaged neighbourhoods. Substantial collinearity between neighbourhood explanatory variables and spatial random effects caused identifiability problems that prevented successful control for spatial autocorrelation. Contrary to previous literature, this study shows that people living in advantaged neighbourhoods were more exposed to road traffic noise in their residential environment than their deprived counterparts. This case study demonstrates the need to systematically perform sensitivity analyses with multiple socioeconomic characteristics to avoid incorrect inferences about an environmental injustice situation and the complexity of effectively controlling for spatial autocorrelation when fixed and random components of the model are correlated.

Investigating the effect of chemical stress and resource ...

EPA Pesticide Factsheets

Modeling exposure and recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating population status and remediation success. The Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Herein, we develop a density dependent matrix population model for Atlantic killifish that analyzes both size-structure and age class-structure of the population so that we could readily incorporate output from a dynamic energy budget (DEB) model currently under development. This population modeling approach emphasizes application in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) and/or laboratory analysis to link effects due to chemical stress to adverse outcomes in whole organisms and populations. We applied the model using data for killifish exposed to dioxin-like compounds, taken from a previously published study. Specifically, the model was used to investigate population trajectories for Atlantic killifish with dietary exposures to 112, 296, and 875 pg/g of dioxin with effects on fertility and survival rates. All effects were expressed relative to control fish. Further, the population model was employed to examine age and size distributions of a population exposed to resource limitation in addition to chemical stress. For each dietary exposure concentration o

Modelling deuterium release from tungsten after high flux high temperature deuterium plasma exposure

NASA Astrophysics Data System (ADS)

Grigorev, Petr; Matveev, Dmitry; Bakaeva, Anastasiia; Terentyev, Dmitry; Zhurkin, Evgeny E.; Van Oost, Guido; Noterdaeme, Jean-Marie

2016-12-01

Tungsten is a primary candidate for plasma facing materials for future fusion devices. An important safety concern in the design of plasma facing components is the retention of hydrogen isotopes. Available experimental data is vast and scattered, and a consistent physical model of retention of hydrogen isotopes in tungsten is still missing. In this work we propose a model of non-equilibrium hydrogen isotopes trapping under fusion relevant plasma exposure conditions. The model is coupled to a diffusion-trapping simulation tool and is used to interpret recent experiments involving high plasma flux exposures. From the computational analysis performed, it is concluded that high flux high temperature exposures (T = 1000 K, flux = 1024 D/m2/s and fluence of 1026 D/m2) result in generation of sub-surface damage and bulk diffusion, so that the retention is driven by both sub-surface plasma-induced defects (bubbles) and trapping at natural defects. On the basis of the non-equilibrium trapping model we have estimated the amount of H stored in the sub-surface region to be ∼10-5 at-1, while the bulk retention is about 4 × 10-7 at-1, calculated by assuming the sub-surface layer thickness of about 10 μm and adjusting the trap concentration to comply with the experimental results for the integral retention.

[CLIMATE CHANGE AND ALLERGIC AIRWAY DISEASE] OBSERVATIONAL,LABORATORY, AND MODELING STUDIES OF THE IMPACTS OF CLIMATE CHANGE ONALLERGIC AIRWAY DISEASE

EPA Science Inventory

Based on these data and preliminary studies, this proposal will be composed of a multiscale source-to-dose analysis approach for assessing the exposure interactions of environmental and biological systems. Once the entire modeling system is validated, it will run f...

Association Between Cd Exposure and Risk of Prostate Cancer

PubMed Central

Ju-Kun, Song; Yuan, Dong-Bo; Rao, Hao-Fu; Chen, Tian-Fei; Luan, Bo-Shi; Xu, Xiao-Ming; Jiang, Fu-Neng; Zhong, Wei-De; Zhu, Jian-Guo

2016-01-01

Abstract Several observational studies on the association between Cd exposure and risk of prostate cancer have yielded inconsistent results. To address this issue, we conducted a meta-analysis to evaluate the correlation between Cd exposure and risk of prostate cancer. Relevant studies in PubMed and Embase databases were retrieved until October 2015. We compared the highest and lowest meta-analyses to quantitatively evaluate the relationship between Cd exposure and risk of prostate cancer. Summary estimates were obtained using a random-effects model. In the general population, high Cd exposure was not associated with increased prostate cancer (OR 1.21; 95% CI 0.91–1.64), whereas the combined standardized mortality ratio of the association between Cd exposure and risk of prostate cancer was 1.66 (95% CI 1.10–2.50) in populations exposed to occupational Cd. In addition, high D-Cd intake (OR 1.07; 95% CI 0.96–1.20) and U-Cd concentration (OR 0.86; 95% CI 0.48–1.55) among the general population was not related to the increased risk of prostate cancer. In the dose analysis, the summary relative risk was 1.07 (95% CI 0.73–1.57) for each 0.5 μg/g creatinine increase in U-Cd and 1.02 (95% CI 0.99–1.06) for each 10 μg/day increase of dietary Cd intake. However, compared with nonoccupational exposure, high occupational Cd exposure may be associated with the increased risk of prostate cancer. This meta-analysis suggests high Cd exposure as a risk factor for prostate cancer in occupational rather than nonoccupational populations. However, these results should be carefully interpreted because of the significant heterogeneity among studies. Additional large-scale and high-quality prospective studies are needed to confirm the association between Cd exposure and risk of prostate cancer. PMID:26871808

Predictors of lung cancer among former asbestos-exposed workers.

PubMed

Świątkowska, Beata; Szubert, Zuzanna; Sobala, Wojciech; Szeszenia-Dąbrowska, Neonila

2015-09-01

Despite extensive literature concerning the risk of lung cancer incidence among asbestos workers there is still lack of data specifying the association between the level of exposure and the frequency of cancer occurrence. The aim of the analysis was to assess the influence of smoking and selected factors related to occupational exposure on the risk of the incidence of lung cancer among the workers who were exposed to asbestos dust in the past. The assessment was performed based on the case-control studies carried out within a cohort including 7,374 former workers of asbestos processing plants, examined over the years 2000-2013. Analysis of the material was based on the calculation of the odds ratio (OR) using conditional logistic regression modeling, adjusted for cigarette smoking, cumulative exposure, branch and time since last exposure. During the survey period there were 165 cases of lung cancer. Among the individuals who smoked, the relative risk of lung cancer incidence was twice as high in the persons smoking more than 20 pack-years (OR=2.23; 95% CI: 1.45-3.46) than it was in the case of the non-smokers. Analysis revealed that the risk of lung cancer in the group with the highest exposure was two times higher in comparison with the low cumulative asbestos exposure (OR=1.99; 95% CI: 1.22-3.25). The risk continued to increase until 30 years after cessation of asbestos exposure and started to decline many years after the last exposure. Influence of the mentioned above characteristics is particularly visible for tumors located in the lower parts of the lungs. Our findings confirm the strong evidence that the lung cancer risk is associated with asbestos exposure and it increases along with the increasing exposure. A strategy of smoking cessation among the individuals exposed to asbestos dust would potentially have health promoting effects. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

EVALUATION OF VADOSE ZONE AND SOURCE MODELS FOR MULTI-MEDIA, MULTI-PATHWAY, MULTI-RECEPTOR RISK ASSESSMENT USING LARGE SOIL COLUMN EXPERIMENT DATA

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) is developing a comprehensive environmental exposure and risk analysis software system for agency-wide application using the methodology of a Multi-media, Multi-pathway, Multi-receptor Risk Assessment (3MRA) model. This software sys...

Residential exposure to pesticides as risk factor for childhood and young adult brain tumors: A systematic review and meta-analysis.

PubMed

Van Maele-Fabry, Geneviève; Gamet-Payrastre, Laurence; Lison, Dominique

2017-09-01

Accumulating evidence suggests a positive association between exposure to non-agricultural pesticides and childhood brain tumors (CBT). (1) To conduct a systematic review and meta-analysis of published studies on the association between residential/household/domestic exposure to pesticides and childhood brain tumors. (2) To clarify variables that could impact the results. Publications in English were identified from a MEDLINE search through 28 February 2017 and from the reference list of identified publications. Risk estimates were extracted from 18 case-control studies published between 1979 and 2016 and study quality assessments were performed. Summary odds ratios (mOR) were calculated according to fixed and random-effect meta-analysis models. Separate analyses were conducted after stratification for study quality, critical exposure period, exposure location, specific exposures, pesticide category, application methods, type of pest treated, type of CBT, child's age at diagnosis and geographic location. Statistically significant associations were observed with CBT after combining all studies (mOR: 1.26; 95% CI: 1.13-1.40) without evidence of inconsistency between study results or publication bias. Specifically, increased risks were observed for several groupings and more particularly for gliomas and exposure involving insecticides. Statistical significance was also reached for high quality studies, for all exposure periods, for indoor exposure and, more particularly, during the prenatal period for all stratifications involving insecticides (except for outdoor use), for pet treatments, for flea/tick treatment, for studies from USA/Canada and studies from Europe (borderline) as well as for data from studies including children of up to 10years at diagnosis and of up to 15years. Our findings support an association between residential exposure to pesticides and childhood brain tumors. Although causality cannot be established, these results add to the evidence leading to recommend limiting residential use of pesticides and to support public health policies serving this objective. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of air quality zone classification methods based on ambient air concentration exposure.

PubMed

Freeman, Brian; McBean, Ed; Gharabaghi, Bahram; Thé, Jesse

2017-05-01

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO 2 and 8-hr O 3 within a zone that meets the compliance requirements of each method. The first method, the "3 Strike" method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method. A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.

Assessing uncertainty in published risk estimates using ...

EPA Pesticide Factsheets

Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective is to characterize model uncertainty by evaluating estimates across published epidemiologic studies of the same cohort.Methods: This analysis was based on 5 studies analyzing a cohort of 2,357 workers employed from 1950-74 in a chromate production plant in Maryland. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability within and between model forms. A total of 5 similarly parameterized analyses were considered across model form, and 16 analyses with alternative parameterizations were considered within model form (10 Cox; 6 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients (betas) for 5 similar analyses ranged from 2.47 to 4.33 (mean=2.97, σ2=0.63). Within the 10 Cox models, coefficients ranged from 2.53 to 4.42 (mean=3.29, σ2=0.

Determining β-lactam exposure threshold to suppress resistance development in Gram-negative bacteria.

PubMed

Tam, Vincent H; Chang, Kai-Tai; Zhou, Jian; Ledesma, Kimberly R; Phe, Kady; Gao, Song; Van Bambeke, Françoise; Sánchez-Díaz, Ana María; Zamorano, Laura; Oliver, Antonio; Cantón, Rafael

2017-05-01

β-Lactams are commonly used for nosocomial infections and resistance to these agents among Gram-negative bacteria is increasing rapidly. Optimized dosing is expected to reduce the likelihood of resistance development during antimicrobial therapy, but the target for clinical dose adjustment is not well established. We examined the likelihood that various dosing exposures would suppress resistance development in an in vitro hollow-fibre infection model. Two strains of Klebsiella pneumoniae and two strains of Pseudomonas aeruginosa (baseline inocula of ∼10 8  cfu/mL) were examined. Various dosing exposures of cefepime, ceftazidime and meropenem were simulated in the hollow-fibre infection model. Serial samples were obtained to ascertain the pharmacokinetic simulations and viable bacterial burden for up to 120 h. Drug concentrations were determined by a validated LC-MS/MS assay and the simulated exposures were expressed as C min /MIC ratios. Resistance development was detected by quantitative culture on drug-supplemented media plates (at 3× the corresponding baseline MIC). The C min /MIC breakpoint threshold to prevent bacterial regrowth was identified by classification and regression tree (CART) analysis. For all strains, the bacterial burden declined initially with the simulated exposures, but regrowth was observed in 9 out of 31 experiments. CART analysis revealed that a C min /MIC ratio ≥3.8 was significantly associated with regrowth prevention (100% versus 44%, P  = 0.001). The development of β-lactam resistance during therapy could be suppressed by an optimized dosing exposure. Validation of the proposed target in a well-designed clinical study is warranted. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Occupational safety considerations with hydrazine fuels

NASA Technical Reports Server (NTRS)

Clewell, H. J.; Haddad, T. S.; George, M. E.; Mcdougal, J. N.; Andersen, M. E.

1992-01-01

A simple pharmacokinetic model and a specially designed dermal vapor exposure chamber which provides respiratory protection were used to determine the rate of penetration of hydrazine and 1,1-dimethylhydrazine (UDMH) vapor through the skin of rats. Parameters for the pharmacokinetic model were determined from intravenous and inhalation exposure data. The model was then used to estimate the skin permeation coefficient for hydrazine or UDMH vapor from the dermal-vapor exposure data. This analysis indicates that UDMH vapor has a relatively high permeability through skin (0.7 cm/hr), a value somewhat higher than was obtained for hydrazine by the same procedure (0.09 cm/hr). Based on these skin permeability results, a skin-only vapor exposure limit giving protection equivalent to the inhalation Threshold Limit Value (TLV) could be calculated. The current TLV's for UDMH and hydrazine are 0.5 and 0.1 ppm, respectively. The corresponding skin-only TLV equivalents, for personnel wearing respiratory protection, are 32 ppm for UDMH and 48 ppm for hydrazine. Should the proposed lowering to the TLV's for these compounds to 0.01 ppm be adopted, the equivalent skin-only TLV's would become 0.64 ppm for UDMH and 4.8 for hydrazine.

Multi-length-scale Material Model for SiC/SiC Ceramic-Matrix Composites (CMCs): Inclusion of In-Service Environmental Effects

NASA Astrophysics Data System (ADS)

Grujicic, M.; Galgalikar, R.; Snipes, J. S.; Ramaswami, S.

2016-01-01

In our recent work, a multi-length-scale room-temperature material model for SiC/SiC ceramic-matrix composites (CMCs) was derived and parameterized. The model was subsequently linked with a finite-element solver so that it could be used in a general room-temperature, structural/damage analysis of gas-turbine engine CMC components. Due to its multi-length-scale character, the material model enabled inclusion of the effects of fiber/tow (e.g., the volume fraction, size, and properties of the fibers; fiber-coating material/thickness; decohesion properties of the coating/matrix interfaces; etc.) and ply/lamina (e.g., the 0°/90° cross-ply versus plain-weave architectures, the extent of tow crimping in the case of the plain-weave plies, cohesive properties of the inter-ply boundaries, etc.) length-scale microstructural/architectural parameters on the mechanical response of the CMCs. One of the major limitations of the model is that it applies to the CMCs in their as-fabricated conditions (i.e., the effect of prolonged in-service environmental exposure and the associated material aging-degradation is not accounted for). In the present work, the model is upgraded to include such in-service environmental-exposure effects. To demonstrate the utility of the upgraded material model, it is used within a finite-element structural/failure analysis involving impact of a toboggan-shaped turbine shroud segment by a foreign object. The results obtained clearly revealed the effects that different aspects of the in-service environmental exposure have on the material degradation and the extent of damage suffered by the impacted CMC toboggan-shaped shroud segment.

Persistent erectile dysfunction in men exposed to the 5α-reductase inhibitors, finasteride, or dutasteride

PubMed Central

Yarnold, Paul R.; Cashy, John; Brannigan, Robert E.; Nardone, Beatrice; Micali, Giuseppe; West, Dennis Paul

2017-01-01

Importance Case reports describe persistent erectile dysfunction (PED) associated with exposure to 5α-reductase inhibitors (5α-RIs). Clinical trial reports and the manufacturers’ full prescribing information (FPI) for finasteride and dutasteride state that risk of sexual adverse effects is not increased by longer duration of 5α-RI exposure and that sexual adverse effects of 5α-RIs resolve in men who discontinue exposure. Objective Our chief objective was to assess whether longer duration of 5α-RI exposure increases risk of PED, independent of age and other known risk factors. Men with shorter 5α-RI exposure served as a comparison control group for those with longer exposure. Design We used a single-group study design and classification tree analysis (CTA) to model PED (lasting ≥90 days after stopping 5α-RI). Covariates included subject attributes, diseases, and drug exposures associated with sexual dysfunction. Setting Our data source was the electronic medical record data repository for Northwestern Medicine. Subjects The analysis cohorts comprised all men exposed to finasteride or dutasteride or combination products containing one of these drugs, and the subgroup of men 16–42 years old and exposed to finasteride ≤1.25 mg/day. Main outcome and measures Our main outcome measure was diagnosis of PED beginning after first 5α-RI exposure, continuing for at least 90 days after stopping 5α-RI, and with contemporaneous treatment with a phosphodiesterase-5 inhibitor (PDE5I). Other outcome measures were erectile dysfunction (ED) and low libido. PED was determined by manual review of medical narratives for all subjects with ED. Risk of an adverse effect was expressed as number needed to harm (NNH). Results Among men with 5α-RI exposure, 167 of 11,909 (1.4%) developed PED (persistence median 1,348 days after stopping 5α-RI, interquartile range (IQR) 631.5–2320.5 days); the multivariable model predicting PED had four variables: prostate disease, duration of 5α-RI exposure, age, and nonsteroidal anti-inflammatory drug (NSAID) use. Of 530 men with new ED, 167 (31.5%) had new PED. Men without prostate disease who combined NSAID use with >208.5 days of 5α-RI exposure had 4.8-fold higher risk of PED than men with shorter exposure (NNH 59.8, all p < 0.002). Among men 16–42 years old and exposed to finasteride ≤1.25 mg/day, 34 of 4,284 (0.8%) developed PED (persistence median 1,534 days, IQR 651–2,351 days); the multivariable model predicting PED had one variable: duration of 5α-RI exposure. Of 103 young men with new ED, 34 (33%) had new PED. Young men with >205 days of finasteride exposure had 4.9-fold higher risk of PED (NNH 108.2, p < 0.004) than men with shorter exposure. Conclusion and relevance Risk of PED was higher in men with longer exposure to 5α-RIs. Among young men, longer exposure to finasteride posed a greater risk of PED than all other assessed risk factors. PMID:28289563

Rotenone and paraquat perturb dopamine metabolism: a computational analysis of pesticide toxicity

PubMed Central

Qi, Zhen; Miller, Gary W.; Voit, Eberhard O.

2014-01-01

Pesticides, such as rotenone and paraquat, are suspected in the pathogenesis of Parkinson’s disease (PD), whose hallmark is the progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Thus, compounds expected to play a role in the pathogenesis of PD will likely impact the function of dopaminergic neurons. To explore the relationship between pesticide exposure and dopaminergic toxicity, we developed a custom-tailored mathematical model of dopamine metabolism and utilized it to infer potential mechanisms underlying the toxicity of rotenone and paraquat, asking how these pesticides perturb specific processes. We performed two types of analyses, which are conceptually different and complement each other. The first analysis, a purely algebraic reverse engineering approach, analytically and deterministically computes the altered profile of enzyme activities that characterize the effects of a pesticide. The second method consists of large-scale Monte Carlo simulations that statistically reveal possible mechanisms of pesticides. The results from the reverse engineering approach show that rotenone and paraquat exposures lead to distinctly different flux perturbations. Rotenone seems to affect all fluxes associated with dopamine compartmentalization, whereas paraquat exposure perturbs fluxes associated with dopamine and its breakdown metabolites. The statistical results of the Monte-Carlo analysis suggest several specific mechanisms. The findings are interesting, because no a priori assumptions are made regarding specific pesticide actions, and all parameters characterizing the processes in the dopamine model are treated in an unbiased manner. Our results show how approaches from computational systems biology can help identify mechanisms underlying the toxicity of pesticide exposure. PMID:24269752

Toxicokinetics/toxicodynamics of arsenic for farmed juvenile milkfish Chanos chanos and human consumption risk in BFD-endemic area of Taiwan.

PubMed

Chou, Berry Yun-Hua; Liao, Chung-Min; Lin, Ming-Chao; Cheng, Hsu-Hui

2006-05-01

This paper presents a toxicokinetic/toxicodynamic analysis to appraise arsenic (As) bioaccumulation in farmed juvenile milkfish Chanos chanos at blackfoot disease (BFD)-endemic area in Taiwan, whereas probabilistic incremental lifetime cancer risk (ILCR) and hazard quotient (HQ) models are also employed to assess the range of exposures for the fishers and non-fishers who eat the contaminated fish. We conducted a 7-day exposure experiment to obtain toxicokinetic parameters, whereas a simple critical body burden toxicity model was verified with LC50(t) data obtained from a 7-day acute toxicity bioassay. Acute toxicity bioassay indicates that 96-h LC50 for juvenile milkfish exposed to As is 7.29 (95% CI: 3.10-10.47) mg l(-1). Our risk analysis for milkfish reared in BFD-endemic area indicates a low likelihood that survival is being affected by waterborne As. Human risk analysis demonstrates that 90%-tile probability exposure ILCRs for fishers in BFD-endemic area have orders of magnitude of 10(-3), indicating a high potential carcinogenic risk, whereas there is no significant cancer risk for non-fishers (ILCRs around 10(-5)). All predicted 90%-tiles of HQ are less than 1 for non-fishers, yet larger than 10 for fishers which indicate larger contributions from farmed milkfish consumptions. Sensitivity analysis indicates that to increase the accuracy of the results, efforts should focus on a better definition of probability distributions for milkfish daily consumption rate and As level in milkfish. Here we show that theoretical human health risks for consuming As-contaminated milkfish in the BFD-endemic area are alarming under a conservative condition based on a probabilistic risk assessment model.

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study

PubMed Central

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Ruuskanen, Juhani; Jantunen, Matti J; Pekkanen, Juha

2007-01-01

Background The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Methods Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. Results The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. Conclusion When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results. PMID:17714598

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study.

PubMed

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Ruuskanen, Juhani; Jantunen, Matti J; Pekkanen, Juha

2007-08-23

The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.

Chronic toxicity of selected polycyclic aromatic hydrocarbons to algae and crustaceans using passive dosing.

PubMed

Bragin, Gail E; Parkerton, Thomas F; Redman, Aaron D; Letinksi, Daniel J; Butler, Josh D; Paumen, Miriam Leon; Sutherland, Cary A; Knarr, Tricia M; Comber, Mike; den Haan, Klaas

2016-12-01

Because of the large number of possible aromatic hydrocarbon structures, predictive toxicity models are needed to support substance hazard and risk assessments. Calibration and evaluation of such models requires toxicity data with well-defined exposures. The present study has applied a passive dosing method to generate reliable chronic effects data for 8 polycyclic aromatic hydrocarbons (PAHs) on the green algae Pseudokirchneriella subcapitata and the crustacean Ceriodaphnia dubia. The observed toxicity of these substances on algal growth rate and neonate production were then compared with available literature toxicity data for these species, as well as target lipid model and chemical activity-based model predictions. The use of passive dosing provided well-controlled exposures that yielded more consistent data sets than attained by past literature studies. Results from the present study, which were designed to exclude the complicating influence of ultraviolet light, were found to be well described by both target lipid model and chemical activity effect models. The present study also found that the lack of chronic effects for high molecular weight PAHs was consistent with the limited chemical activity that could be achieved for these compounds in the aqueous test media. Findings from this analysis highlight that variability in past literature toxicity data for PAHs may be complicated by both poorly controlled exposures and photochemical processes that can modulate both exposure and toxicity. Environ Toxicol Chem 2016;35:2948-2957. © 2016 SETAC. © 2016 SETAC.

Population Pharmacokinetics and Exposure-Response of a Fixed-Dose Combination of Azilsartan Medoxomil and Chlorthalidone in Patients With Stage 2 Hypertension.

PubMed

Tsai, Max C; Wu, Jingtao; Kupfer, Stuart; Vakilynejad, Majid

2016-08-01

Population pharmacokinetic and exposure-response models for azilsartan medoxomil (AZL-M) and chlorthalidone (CLD) were developed using data from an 8-week placebo-controlled phase 3, factorial study of 20, 40, and 80 mg AZL-M every day (QD) and 12.5 and 25 mg CLD QD in fixed-dose combination (FDC) in subjects with moderate to severe essential hypertension. A 2-compartment model with first-order absorption and elimination was developed to describe pharmacokinetics. An Emax model for exposure-response analysis evaluated AZL-M/CLD effects on ambulatory systolic blood pressure (SBP). Estimated oral clearance and apparent volume of distribution (central compartment) were 1.47 L/h and 3.98 L for AZL, and 4.13 L/h and 62.1 L for CLD. Age as a covariate had the largest effect on AZL and CLD exposure (±20% change). Predicted maximal SBP responses (Emax ) were -15.6 and -23.9 mm Hg for AZL and CLD. Subgroup analysis identified statistically significant Emax differences for black vs nonblack subjects, whereby the reduced AZL response in black subjects was offset by greater response to CLD. The estimated Emax for AZL and CLD was generally greater in subjects with higher baseline BP. In conclusion, no dose adjustments to AZL-M or CLD are warranted based on identified covariates, and antihypertensive efficacy of AZL-M/CLD combination therapy is comparable in black and nonblack subjects. © 2015, The Authors. The Journal of Clinical Pharmacology Published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.

Exposure-Response Analysis of Micafungin in Neonatal Candidiasis: Pooled Analysis of Two Clinical Trials.

PubMed

Kovanda, Laura L; Walsh, Thomas J; Benjamin, Daniel K; Arrieta, Antonio; Kaufman, David A; Smith, P Brian; Manzoni, Paolo; Desai, Amit V; Kaibara, Atsunori; Bonate, Peter L; Hope, William W

2018-06-01

Neonatal candidiasis causes significant morbidity and mortality in high risk infants. The micafungin dosage regimen of 10 mg/kg established for the treatment of neonatal candidiasis is based on a laboratory animal model of neonatal hematogenous Candida meningoencephalitis and pharmacokinetic (PK)-pharmacodynamic (PD) bridging studies. However, little is known about the how these PK-PD data translate clinically. Micafungin plasma concentrations from infants were used to construct a population PK model using Pmetrics software. Bayesian posterior estimates for infants with invasive candidiasis were used to evaluate the relationship between drug exposure and mycologic response using logistic regression. Sixty-four infants 3-119 days of age were included, of which 29 (45%) infants had invasive candidiasis. A 2-compartment PK model fits the data well. Allometric scaling was applied to clearance and volume normalized to the mean population weight (kg). The mean (standard deviation) estimates for clearance and volume in the central compartment were 0.07 (0.05) L/h/1.8 kg and 0.61 (0.53) L/1.8 kg, respectively. No relationship between average daily area under concentration-time curve or average daily area under concentration-time curve:minimum inhibitory concentration ratio and mycologic response was demonstrated (P > 0.05). Although not statistically significant, mycologic response was numerically higher when area under concentration-time curves were at or above the PD target. While a significant exposure-response relationship was not found, PK-PD experiments support higher exposures of micafungin in infants with invasive candidiasis. More patients would clarify this relationship; however, low incidence deters the feasibility of these studies.

An Animal Model of Chronic Aplastic Bone Marrow Failure Following Pesticide Exposure in Mice

PubMed Central

Chatterjee, Sumanta; Chaklader, Malay; Basak, Pratima; Das, Prosun; Das, Madhurima; Pereira, Jacintha Archana; Dutta, Ranjan Kumar; Chaudhuri, Samaresh; Law, Sujata

2010-01-01

The wide use of pesticides for agriculture, domestic and industrial purposes and evaluation of their subsequent effect is of major concern for public health. Human exposure to these contaminants especially bone marrow with its rapidly renewing cell population is one of the most sensitive tissues to these toxic agents represents a risk for the immune system leading to the onset of different pathologies. In this experimental protocol we have developed a mouse model of pesticide(s) induced hypoplastic/aplastic marrow failure to study quantitative changes in the bone marrow hematopoietic stem cell (BMHSC) population through flowcytometric analysis, defects in the stromal microenvironment through short term adherent cell colony (STACC) forming assay and immune functional capacity of the bone marrow derived cells through cell mediated immune (CMI) parameter study. A time course dependent analysis for consecutive 90 days were performed to monitor the associated changes in the marrow’s physiology after 30th, 60th and 90th days of chronic pesticide exposure. The peripheral blood showed maximum lowering of the blood cell count after 90 days which actually reflected the bone marrow scenario. Severe depression of BMHSC population, immune profile of the bone marrow derived cells and reduction of adherent cell colonies pointed towards an essentially empty and hypoplastic marrow condition that resembled the disease aplastic anemia. The changes were accompanied by splenomegaly and splenic erythroid hyperplasia. In conclusion, this animal model allowed us a better understanding of clinico-biological findings of the disease aplastic anemia following toxic exposure to the pesticide(s) used for agricultural and industrial purposes. PMID:24855541

Efficacy of hair analysis for monitoring exposure to uranium: a mini-review.

PubMed

Joksić, Agnes Šömen; Katz, Sidney A

2014-01-01

In spite of the ease with which samples may be collected and the stability of the samples after collection, the use of hair mineral analysis for monitoring environmental exposures and evaluating heavy metal poisonings has remained controversial since its initial applications for these purposes in the early 1950s. Among the major arguments against using hair mineral analysis in general were the absence of biokinetic models and/or metabolic data that adequately described the incorporation of trace elements into the hair, the absence of correlations between the concentrations of trace elements in the hair and their concentrations in other tissues, the inability to distinguish between trace elements that were deposited in the hair endogenously and those that were deposited on the hair exogenously, the absence of reliable reference ranges for interpreting the results of hair mineral analysis and a lack of standard procedures for the collecting, preparing and analyzing the hair samples. The developments of the past two decades addressing these objections are reviewed here, and arguments supporting the use of hair analysis for monitoring environmental and/or occupational exposures to uranium are made on the basis of the information presented in this review.

Asbestos exposure and laryngeal cancer mortality.

PubMed

Peng, Wen-Jia; Mi, Jing; Jiang, Yu-Hong

2016-05-01

Occupational exposure to asbestos occurs in many workplaces and is well known to cause asbestosis, lung cancer, and mesothelioma. However, the link between asbestos exposure and other malignancies was not confirmed. The aim of the current meta-analysis was to provide a summary measure of risk for laryngeal cancer associated with occupational asbestos exposure. Systematic review and meta-analysis. Electronic databases were searched for studies characterizing the association between asbestos and laryngeal cancer. Standardized mortality rate (SMR) with its 95% confidence interval (CI) of each study was combined using a fixed or random effect model. Significantly increased SMR for laryngeal cancer was observed when subjects were exposed to asbestos (SMR = 1.69, 95% CI = 1.45-1.97, P < .001), with little evidence of heterogeneity among studies (Q = 15.39, P = .803, I(2) = 0.0%). Effect estimates were larger for cohorts controlling for male subjects, Europe and Oceania, mining and textile industries, exposure to crocidolite, long study follow-up (>25 years), and SMR for lung cancer > 2.0. Publication bias was not detect by Begg test (P = .910) and Egger test (P = .340). Our study supports the association of exposure to asbestos with an increased risk of laryngeal cancer mortality among male workers. NA Laryngoscope, 126:1169-1174, 2016. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Multivariate Analysis of Longitudinal Rates of Change

PubMed Central

Bryan, Matthew; Heagerty, Patrick J.

2016-01-01

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed by Roy and Lin [1]; Proust-Lima, Letenneur and Jacqmin-Gadda [2]; and Gray and Brookmeyer [3] among others. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, Gray and Brookmeyer [3] introduce an “accelerated time” method which assumes that covariates rescale time in longitudinal models for disease progression. In this manuscript we detail an alternative multivariate model formulation that directly structures longitudinal rates of change, and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. PMID:27417129

The effects of road traffic and aircraft noise exposure on children's episodic memory: the RANCH project.

PubMed

Matheson, Mark; Clark, Charlotte; Martin, Rocio; van Kempen, Elise; Haines, Mary; Barrio, Isabel Lopez; Hygge, Staffan; Stansfeld, Stephen

2010-01-01

Previous studies have found that chronic exposure to aircraft noise has a negative effect on children's performance on tests of episodic memory. The present study extended the design of earlier studies in three ways: firstly, by examining the effects of two noise sources, aircraft and road traffic, secondly, by examining exposure-effect relationships, and thirdly, by carrying out parallel field studies in three European countries, allowing cross-country comparisons to be made. A total of 2844 children aged between 8 years 10 months and 12 years 10 months (mean age 10 years 6 months) completed classroom-based tests of cued recall, recognition memory and prospective memory. Questionnaires were also completed by the children and their parents in order to provide information about socioeconomic context. Multilevel modeling analysis revealed aircraft noise to be associated with an impairment of recognition memory in a linear exposure-effect relationship. The analysis also found road traffic noise to be associated with improved performance on cued recall in a linear exposure-effect relationship. No significant association was found between exposure to aircraft noise and cued recall or prospective memory. Likewise, no significant association was found between road traffic noise and recognition or prospective memory. Taken together, these findings indicate that exposure to aircraft noise and road traffic noise can impact on certain aspects of children's episodic memory.

Non-thermal Plasma Exposure Rapidly Attenuates Bacterial AHL-Dependent Quorum Sensing and Virulence.

PubMed

Flynn, Padrig B; Busetti, Alessandro; Wielogorska, Ewa; Chevallier, Olivier P; Elliott, Christopher T; Laverty, Garry; Gorman, Sean P; Graham, William G; Gilmore, Brendan F

2016-05-31

The antimicrobial activity of atmospheric pressure non-thermal plasma has been exhaustively characterised, however elucidation of the interactions between biomolecules produced and utilised by bacteria and short plasma exposures are required for optimisation and clinical translation of cold plasma technology. This study characterizes the effects of non-thermal plasma exposure on acyl homoserine lactone (AHL)-dependent quorum sensing (QS). Plasma exposure of AHLs reduced the ability of such molecules to elicit a QS response in bacterial reporter strains in a dose-dependent manner. Short exposures (30-60 s) produce of a series of secondary compounds capable of eliciting a QS response, followed by the complete loss of AHL-dependent signalling following longer exposures. UPLC-MS analysis confirmed the time-dependent degradation of AHL molecules and their conversion into a series of by-products. FT-IR analysis of plasma-exposed AHLs highlighted the appearance of an OH group. In vivo assessment of the exposure of AHLs to plasma was examined using a standard in vivo model. Lettuce leaves injected with the rhlI/lasI mutant PAO-MW1 alongside plasma treated N-butyryl-homoserine lactone and n-(3-oxo-dodecanoyl)-homoserine lactone, exhibited marked attenuation of virulence. This study highlights the capacity of atmospheric pressure non-thermal plasma to modify and degrade AHL autoinducers thereby attenuating QS-dependent virulence in P. aeruginosa.

Non-thermal Plasma Exposure Rapidly Attenuates Bacterial AHL-Dependent Quorum Sensing and Virulence

PubMed Central

Flynn, Padrig B.; Busetti, Alessandro; Wielogorska, Ewa; Chevallier, Olivier P.; Elliott, Christopher T.; Laverty, Garry; Gorman, Sean P.; Graham, William G.; Gilmore, Brendan F.

2016-01-01

The antimicrobial activity of atmospheric pressure non-thermal plasma has been exhaustively characterised, however elucidation of the interactions between biomolecules produced and utilised by bacteria and short plasma exposures are required for optimisation and clinical translation of cold plasma technology. This study characterizes the effects of non-thermal plasma exposure on acyl homoserine lactone (AHL)-dependent quorum sensing (QS). Plasma exposure of AHLs reduced the ability of such molecules to elicit a QS response in bacterial reporter strains in a dose-dependent manner. Short exposures (30–60 s) produce of a series of secondary compounds capable of eliciting a QS response, followed by the complete loss of AHL-dependent signalling following longer exposures. UPLC-MS analysis confirmed the time-dependent degradation of AHL molecules and their conversion into a series of by-products. FT-IR analysis of plasma-exposed AHLs highlighted the appearance of an OH group. In vivo assessment of the exposure of AHLs to plasma was examined using a standard in vivo model. Lettuce leaves injected with the rhlI/lasI mutant PAO-MW1 alongside plasma treated N-butyryl-homoserine lactone and n-(3-oxo-dodecanoyl)-homoserine lactone, exhibited marked attenuation of virulence. This study highlights the capacity of atmospheric pressure non-thermal plasma to modify and degrade AHL autoinducers thereby attenuating QS-dependent virulence in P. aeruginosa. PMID:27242335

Considerations in STS payload environmental verification

NASA Technical Reports Server (NTRS)

Keegan, W. B.

1978-01-01

Considerations regarding the Space Transportation System (STS) payload environmental verification are reviewed. It is noted that emphasis is placed on testing at the subassembly level and that the basic objective of structural dynamic payload verification is to ensure reliability in a cost-effective manner. Structural analyses consist of: (1) stress analysis for critical loading conditions, (2) model analysis for launch and orbital configurations, (3) flight loads analysis, (4) test simulation analysis to verify models, (5) kinematic analysis of deployment/retraction sequences, and (6) structural-thermal-optical program analysis. In addition to these approaches, payload verification programs are being developed in the thermal-vacuum area. These include the exposure to extreme temperatures, temperature cycling, thermal-balance testing and thermal-vacuum testing.

Collaborative Platform for DFM

DTIC Science & Technology

2007-12-20

generation litho hotspot checkers have also been implemented in automated hotspot fixers that can automatically fix designs by making small changes...processing side (ex. new CMP models, etch models, litho models) and on the circuit side (ex. Process aware circuit analysis or yield optimization...Since final gate CD is a function of not only litho , but Post Exposure Bake, ashing, and etch, the processing module can be augmented with more

Biological Effects of Protracted Exposure to Ionizing Radiation: Review, Analysis, and Model Development

DTIC Science & Technology

1991-11-01

dynamics, physiological changes, morphologi- cal changes, cell/tissue damage and recovery mechanisms, and existing radiobiological injury and recovery...humans and the ferret. The gut injury model (GIM) is a three-compartment hierarchial- type tissue model to simulate radiation-induced changes in the...Prodromal Symptoms Diarrhea Gastrointestinal Symptoms Dose Rate Cell Survival Intestinal Injury Fatigability Cell Damage Cell Repair Cell Proliferation

Long-Term Air Pollution and Traffic Noise Exposures and Mild Cognitive Impairment in Older Adults: A Cross-Sectional Analysis of the Heinz Nixdorf Recall Study.

PubMed

Tzivian, Lilian; Dlugaj, Martha; Winkler, Angela; Weinmayr, Gudrun; Hennig, Frauke; Fuks, Kateryna B; Vossoughi, Mohammad; Schikowski, Tamara; Weimar, Christian; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Hoffmann, Barbara

2016-09-01

Mild cognitive impairment (MCI) describes the intermediate state between normal cognitive aging and dementia. Adverse effects of air pollution (AP) on cognitive functions have been proposed, but investigations of simultaneous exposure to noise are scarce. We analyzed the cross-sectional associations of long-term exposure to AP and traffic noise with overall MCI and amnestic (aMCI) and nonamnestic (naMCI) MCI. At the second examination of the population-based Heinz Nixdorf Recall study, cognitive assessment was completed in 4,086 participants who were 50-80 years old. Of these, 592 participants were diagnosed as having MCI (aMCI, n = 309; naMCI, n = 283) according to previously published criteria using five neuropsychological subtests. We assessed long-term residential concentrations for size-fractioned particulate matter (PM) and nitrogen oxides with land use regression, and for traffic noise [weighted 24-hr (LDEN) and night-time (LNIGHT) means]. Logistic regression models adjusted for individual risk factors were calculated to estimate the association of environmental exposures with MCI in single- and two-exposure models. Most air pollutants and traffic noise were associated with overall MCI and aMCI. For example, an interquartile range increase in PM2.5 and a 10 A-weighted decibel [dB(A)] increase in LDEN were associated with overall MCI as follows [odds ratio (95% confidence interval)]: 1.16 (1.05, 1.27) and 1.40 (1.03, 1.91), respectively, and with aMCI as follows: 1.22 (1.08, 1.38) and 1.53 (1.05, 2.24), respectively. In two-exposure models, AP and noise associations were attenuated [e.g., for aMCI, PM2.5 1.13 (0.98, 1.30) and LDEN 1.46 (1.11, 1.92)]. Long-term exposures to air pollution and traffic noise were positively associated with MCI, mainly with the amnestic subtype. Tzivian L, Dlugaj M, Winkler A, Weinmayr G, Hennig F, Fuks KB, Vossoughi M, Schikowski T, Weimar C, Erbel R, Jöckel KH, Moebus S, Hoffmann B, on behalf of the Heinz Nixdorf Recall study Investigative Group. 2016. Long-term air pollution and traffic noise exposures and mild cognitive impairment in older adults: a cross-sectional analysis of the Heinz Nixdorf Recall Study. Environ Health Perspect 124:1361-1368; http://dx.doi.org/10.1289/ehp.1509824.