Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on binary outcomes.

PubMed

Austin, Peter C

2018-05-20

Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (eg, dose or quantity of medication, income, or years of education). We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of continuous exposures on binary outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. We examined both the use of ordinary least squares to estimate the propensity function and the use of the covariate balancing propensity score algorithm. The use of methods based on the GPS was compared with the use of G-computation. All methods resulted in essentially unbiased estimation of the population dose-response function. However, GPS-based weighting tended to result in estimates that displayed greater variability and had higher mean squared error when the magnitude of confounding was strong. Of the methods based on the GPS, covariate adjustment using the GPS tended to result in estimates with lower variability and mean squared error when the magnitude of confounding was strong. We illustrate the application of these methods by estimating the effect of average neighborhood income on the probability of death within 1 year of hospitalization for an acute myocardial infarction. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

PubMed Central

Burgess, Stephen; Daniel, Rhian M; Butterworth, Adam S; Thompson, Simon G

2015-01-01

Background: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. Methods: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. Results: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. Conclusions: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes. PMID:25150977

Integrating workplace exposure databases for occupational medicine services and epidemiologic studies at a former nuclear weapons facility.

PubMed

Ruttenber, A J; McCrea, J S; Wade, T D; Schonbeck, M F; LaMontagne, A D; Van Dyke, M V; Martyny, J W

2001-02-01

We outline methods for integrating epidemiologic and industrial hygiene data systems for the purpose of exposure estimation, exposure surveillance, worker notification, and occupational medicine practice. We present examples of these methods from our work at the Rocky Flats Plant--a former nuclear weapons facility that fabricated plutonium triggers for nuclear weapons and is now being decontaminated and decommissioned. The weapons production processes exposed workers to plutonium, gamma photons, neutrons, beryllium, asbestos, and several hazardous chemical agents, including chlorinated hydrocarbons and heavy metals. We developed a job exposure matrix (JEM) for estimating exposures to 10 chemical agents in 20 buildings for 120 different job categories over a production history spanning 34 years. With the JEM, we estimated lifetime chemical exposures for about 12,000 of the 16,000 former production workers. We show how the JEM database is used to estimate cumulative exposures over different time periods for epidemiological studies and to provide notification and determine eligibility for a medical screening program developed for former workers. We designed an industrial hygiene data system for maintaining exposure data for current cleanup workers. We describe how this system can be used for exposure surveillance and linked with the JEM and databases on radiation doses to develop lifetime exposure histories and to determine appropriate medical monitoring tests for current cleanup workers. We also present time-line-based graphical methods for reviewing and correcting exposure estimates and reporting them to individual workers.

Instrumental Variable Analysis with a Nonlinear Exposure–Outcome Relationship

PubMed Central

Davies, Neil M.; Thompson, Simon G.

2014-01-01

Background: Instrumental variable methods can estimate the causal effect of an exposure on an outcome using observational data. Many instrumental variable methods assume that the exposure–outcome relation is linear, but in practice this assumption is often in doubt, or perhaps the shape of the relation is a target for investigation. We investigate this issue in the context of Mendelian randomization, the use of genetic variants as instrumental variables. Methods: Using simulations, we demonstrate the performance of a simple linear instrumental variable method when the true shape of the exposure–outcome relation is not linear. We also present a novel method for estimating the effect of the exposure on the outcome within strata of the exposure distribution. This enables the estimation of localized average causal effects within quantile groups of the exposure or as a continuous function of the exposure using a sliding window approach. Results: Our simulations suggest that linear instrumental variable estimates approximate a population-averaged causal effect. This is the average difference in the outcome if the exposure for every individual in the population is increased by a fixed amount. Estimates of localized average causal effects reveal the shape of the exposure–outcome relation for a variety of models. These methods are used to investigate the relations between body mass index and a range of cardiovascular risk factors. Conclusions: Nonlinear exposure–outcome relations should not be a barrier to instrumental variable analyses. When the exposure–outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure–outcome relation can be estimated. PMID:25166881

Instrumental variables vs. grouping approach for reducing bias due to measurement error.

PubMed

Batistatou, Evridiki; McNamee, Roseanne

2008-01-01

Attenuation of the exposure-response relationship due to exposure measurement error is often encountered in epidemiology. Given that error cannot be totally eliminated, bias correction methods of analysis are needed. Many methods require more than one exposure measurement per person to be made, but the `group mean OLS method,' in which subjects are grouped into several a priori defined groups followed by ordinary least squares (OLS) regression on the group means, can be applied with one measurement. An alternative approach is to use an instrumental variable (IV) method in which both the single error-prone measure and an IV are used in IV analysis. In this paper we show that the `group mean OLS' estimator is equal to an IV estimator with the group mean used as IV, but that the variance estimators for the two methods are different. We derive a simple expression for the bias in the common estimator which is a simple function of group size, reliability and contrast of exposure between groups, and show that the bias can be very small when group size is large. We compare this method with a new proposal (group mean ranking method), also applicable with a single exposure measurement, in which the IV is the rank of the group means. When there are two independent exposure measurements per subject, we propose a new IV method (EVROS IV) and compare it with Carroll and Stefanski's (CS IV) proposal in which the second measure is used as an IV; the new IV estimator combines aspects of the `group mean' and `CS' strategies. All methods are evaluated in terms of bias, precision and root mean square error via simulations and a dataset from occupational epidemiology. The `group mean ranking method' does not offer much improvement over the `group mean method.' Compared with the `CS' method, the `EVROS' method is less affected by low reliability of exposure. We conclude that the group IV methods we propose may provide a useful way to handle mismeasured exposures in epidemiology with or without replicate measurements. Our finding may also have implications for the use of aggregate variables in epidemiology to control for unmeasured confounding.

Health Risk Assessment of Lead Ingestion Exposure by Particle Sizes in Crumb Rubber on Artificial Turf Considering Bioavailability

PubMed Central

Kim, Sunduk; Yang, Ji-Yeon; Kim, Ho-Hyun; Yeo, In-Young; Shin, Dong-Chun

2012-01-01

Objectives The purpose of this study was to assess the risk of ingestion exposure of lead by particle sizes of crumb rubber in artificial turf filling material with consideration of bioavailability. Methods This study estimated the ingestion exposure by particle sizes (more than 250 um or less than 250 um) focusing on recyclable ethylene propylene diene monomer crumb rubber being used as artificial turf filling. Analysis on crumb rubber was conducted using body ingestion exposure estimate method in which total content test method, acid extraction method and digestion extraction method are reflected. Bioavailability which is a calibrating factor was reflected in ingestion exposure estimate method and applied in exposure assessment and risk assessment. Two methods using acid extraction and digestion extraction concentration were compared and evaluated. Results As a result of the ingestion exposure of crumb rubber material, the average lead exposure amount to the digestion extraction result among crumb rubber was calculated to be 1.56×10-4 mg/kg-day for low grade elementary school students and 4.87×10-5 mg/kg-day for middle and high school students in 250 um or less particle size, and that to the acid extraction result was higher than the digestion extraction result. Results of digestion extraction and acid extraction showed that the hazard quotient was estimated by about over 2 times more in particle size of lower than 250 um than in higher than 250 um. There was a case of an elementary school student in which the hazard quotient exceeded 0.1. Conclusions Results of this study confirm that the exposure of lead ingestion and risk level increases as the particle size of crumb rubber gets smaller. PMID:22355803

Comparison of gestational dating methods and implications ...

EPA Pesticide Factsheets

OBJECTIVES: Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassificat ion and inconsistencies in risk estimates, particularly if exposure assignment is also gestation-dependent. This paper examines a'what-if' scenario in which alternative methods are used and attempts to elucidate how method choice affects observed results.METHODS: We constructed two 20-week gestational age cohorts of pregnancies between 2000 and 2005 (New Jersey, Pennsylvania, Ohio, USA) using live birth certificates : one defined preterm birth (PTB) status using CE and one using LMP. Within these, we estimated risk for 4 categories of preterm birth (PTBs per 106 pregnancies) and risk differences (RD (95% Cl s)) associated with exposure to particulate matter (PM2. 5).RESULTS: More births were classified preterm using LMP (16%) compared with CE (8%). RD divergences increased between cohorts as exposure period approached delivery. Among births between 28 and 31 weeks, week 7 PM2.5 exposure conveyed RDs of 44 (21 to 67) for CE and 50 (18 to 82) for LMP populations, while week 24 exposure conveyed RDs of 33 (11 to 56) and -20 (-50 to 10), respectively.CONCLUSIONS: Different results from analyses restricted to births with both CE and LMP are most likely due to differences in dating methods rather than selection issues. Results are sensitive t

INTEGRATED PROBABILISTIC AND DETERMINISTIC MODELING TECHNIQUES IN ESTIMATING EXPOSURE TO WATER-BORNE CONTAMINANTS: PART 2 PHARMACOKINETIC MODELING

EPA Science Inventory

The Total Exposure Model (TEM) uses deterministic and stochastic methods to estimate the exposure of a person performing daily activities of eating, drinking, showering, and bathing. There were 250 time histories generated, by subject with activities, for the three exposure ro...

Estimating post-marketing exposure to pharmaceutical products using ex-factory distribution data.

PubMed

Telfair, Tamara; Mohan, Aparna K; Shahani, Shalini; Klincewicz, Stephen; Atsma, Willem Jan; Thomas, Adrian; Fife, Daniel

2006-10-01

The pharmaceutical industry has an obligation to identify adverse reactions to drug products during all phases of drug development, including the post-marketing period. Estimates of population exposure to pharmaceutical products are important to the post-marketing surveillance of drugs, and provide a context for assessing the various risks and benefits, including drug safety, associated with drug treatment. This paper describes a systematic approach to estimating post-marketing drug exposure using ex-factory shipment data to estimate the quantity of medication available, and dosage information (stratified by indication or other factors as appropriate) to convert the quantity of medication to person time of exposure. Unlike the non-standardized methods often used to estimate exposure, this approach provides estimates whose calculations are explicit, documented, and consistent across products and over time. The methods can readily be carried out by an individual or small group specializing in this function, and lend themselves to automation. The present estimation approach is practical and relatively uncomplicated to implement. We believe it is a useful innovation. Copyright 2006 John Wiley & Sons, Ltd.

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

In-residence, multiple route exposures to chlorpyrifos and diazinon estimated by indirect method models

NASA Astrophysics Data System (ADS)

Moschandreas, D. J.; Kim, Y.; Karuchit, S.; Ari, H.; Lebowitz, M. D.; O'Rourke, M. K.; Gordon, S.; Robertson, G.

One of the objectives of the National Human Exposure Assessment Survey (NHEXAS) is to estimate exposures to several pollutants in multiple media and determine their distributions for the population of Arizona. This paper presents modeling methods used to estimate exposure distributions of chlorpyrifos and diazinon in the residential microenvironment using the database generated in Arizona (NHEXAS-AZ). A four-stage probability sampling design was used for sample selection. Exposures to pesticides were estimated using the indirect method of exposure calculation by combining measured concentrations of the two pesticides in multiple media with questionnaire information such as time subjects spent indoors, dietary and non-dietary items they consumed, and areas they touched. Most distributions of in-residence exposure to chlorpyrifos and diazinon were log-normal or nearly log-normal. Exposures to chlorpyrifos and diazinon vary by pesticide and route as well as by various demographic characteristics of the subjects. Comparisons of exposure to pesticides were investigated among subgroups of demographic categories, including gender, age, minority status, education, family income, household dwelling type, year the dwelling was built, pesticide use, and carpeted areas within dwellings. Residents with large carpeted areas within their dwellings have higher exposures to both pesticides for all routes than those in less carpet-covered areas. Depending on the route, several other determinants of exposure to pesticides were identified, but a clear pattern could not be established regarding the exposure differences between several subpopulation groups.

Estimating the dose response relationship for occupational radiation exposure measured with minimum detection level.

PubMed

Xue, Xiaonan; Shore, Roy E; Ye, Xiangyang; Kim, Mimi Y

2004-10-01

Occupational exposures are often recorded as zero when the exposure is below the minimum detection level (BMDL). This can lead to an underestimation of the doses received by individuals and can lead to biased estimates of risk in occupational epidemiologic studies. The extent of the exposure underestimation is increased with the magnitude of the minimum detection level (MDL) and the frequency of monitoring. This paper uses multiple imputation methods to impute values for the missing doses due to BMDL. A Gibbs sampling algorithm is developed to implement the method, which is applied to two distinct scenarios: when dose information is available for each measurement (but BMDL is recorded as zero or some other arbitrary value), or when the dose information available represents the summation of a series of measurements (e.g., only yearly cumulative exposure is available but based on, say, weekly measurements). Then the average of the multiple imputed exposure realizations for each individual is used to obtain an unbiased estimate of the relative risk associated with exposure. Simulation studies are used to evaluate the performance of the estimators. As an illustration, the method is applied to a sample of historical occupational radiation exposure data from the Oak Ridge National Laboratory.

Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on survival or time-to-event outcomes.

PubMed

Austin, Peter C

2018-01-01

Propensity score methods are frequently used to estimate the effects of interventions using observational data. The propensity score was originally developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (e.g. pack-years of cigarettes smoked, dose of medication, or years of education). We describe how the GPS can be used to estimate the effect of continuous exposures on survival or time-to-event outcomes. To do so we modified the concept of the dose-response function for use with time-to-event outcomes. We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of quantitative exposures on survival or time-to-event outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. The use of methods based on the GPS was compared with the use of conventional G-computation and weighted G-computation. Conventional G-computation resulted in estimates of the dose-response function that displayed the lowest bias and the lowest variability. Amongst the two GPS-based methods, covariate adjustment using the GPS tended to have the better performance. We illustrate the application of these methods by estimating the effect of average neighbourhood income on the probability of survival following hospitalization for an acute myocardial infarction.

CAREX Canada: an enhanced model for assessing occupational carcinogen exposure

PubMed Central

Peters, Cheryl E; Ge, Calvin B; Hall, Amy L; Davies, Hugh W; Demers, Paul A

2015-01-01

Objectives To estimate the numbers of workers exposed to known and suspected occupational carcinogens in Canada, building on the methods of CARcinogen EXposure (CAREX) projects in the European Union (EU). Methods CAREX Canada consists of estimates of the prevalence and level of exposure to occupational carcinogens. CAREX Canada includes occupational agents evaluated by the International Agency for Research on Cancer as known, probable or possible human carcinogens that were present and feasible to assess in Canadian workplaces. A Canadian Workplace Exposure Database was established to identify the potential for exposure in particular industries and occupations, and to create exposure level estimates among priority agents, where possible. CAREX EU data were reviewed for relevance to the Canadian context and the proportion of workers likely to be exposed by industry and occupation in Canada was assigned using expert assessment and agreement by a minimum of two occupational hygienists. These proportions were used to generate prevalence estimates by linkage with the Census of Population for 2006, and these estimates are available by industry, occupation, sex and province. Results CAREX Canada estimated the number of workers exposed to 44 known, probable and suspected carcinogens. Estimates of levels of exposure were further developed for 18 priority agents. Common exposures included night shift work (1.9 million exposed), solar ultraviolet radiation exposure (1.5 million exposed) and diesel engine exhaust (781 000 exposed). Conclusions A substantial proportion of Canadian workers are exposed to known and suspected carcinogens at work. PMID:24969047

Estimating survival probabilities by exposure levels: utilizing vital statistics and complex survey data with mortality follow-up.

PubMed

Landsman, V; Lou, W Y W; Graubard, B I

2015-05-20

We present a two-step approach for estimating hazard rates and, consequently, survival probabilities, by levels of general categorical exposure. The resulting estimator utilizes three sources of data: vital statistics data and census data are used at the first step to estimate the overall hazard rate for a given combination of gender and age group, and cohort data constructed from a nationally representative complex survey with linked mortality records, are used at the second step to divide the overall hazard rate by exposure levels. We present an explicit expression for the resulting estimator and consider two methods for variance estimation that account for complex multistage sample design: (1) the leaving-one-out jackknife method, and (2) the Taylor linearization method, which provides an analytic formula for the variance estimator. The methods are illustrated with smoking and all-cause mortality data from the US National Health Interview Survey Linked Mortality Files, and the proposed estimator is compared with a previously studied crude hazard rate estimator that uses survey data only. The advantages of a two-step approach and possible extensions of the proposed estimator are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Semiparametric methods for estimation of a nonlinear exposure‐outcome relationship using instrumental variables with application to Mendelian randomization

PubMed Central

Staley, James R.

2017-01-01

ABSTRACT Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure‐outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure‐outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure‐outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure. PMID:28317167

Modeling Of In-Vehicle Human Exposure to Ambient Fine Particulate Matter

PubMed Central

Liu, Xiaozhen; Frey, H. Christopher

2012-01-01

A method for estimating in-vehicle PM2.5 exposure as part of a scenario-based population simulation model is developed and assessed. In existing models, such as the Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), in-vehicle exposure is estimated using linear regression based on area-wide ambient PM2.5 concentration. An alternative modeling approach is explored based on estimation of near-road PM2.5 concentration and an in-vehicle mass balance. Near-road PM2.5 concentration is estimated using a dispersion model and fixed site monitor (FSM) data. In-vehicle concentration is estimated based on air exchange rate and filter efficiency. In-vehicle concentration varies with road type, traffic flow, windspeed, stability class, and ventilation. Average in-vehicle exposure is estimated to contribute 10 to 20 percent of average daily exposure. The contribution of in-vehicle exposure to total daily exposure can be higher for some individuals. Recommendations are made for updating exposure models and implementation of the alternative approach. PMID:23101000

Correction of odds ratios in case-control studies for exposure misclassification with partial knowledge of the degree of agreement among experts who assessed exposures.

PubMed

Burstyn, Igor; Gustafson, Paul; Pintos, Javier; Lavoué, Jérôme; Siemiatycki, Jack

2018-02-01

Estimates of association between exposures and diseases are often distorted by error in exposure classification. When the validity of exposure assessment is known, this can be used to adjust these estimates. When exposure is assessed by experts, even if validity is not known, we sometimes have information about interrater reliability. We present a Bayesian method for translating the knowledge of interrater reliability, which is often available, into knowledge about validity, which is often needed but not directly available, and applying this to correct odds ratios (OR). The method allows for inclusion of observed potential confounders in the analysis, as is common in regression-based control for confounding. Our method uses a novel type of prior on sensitivity and specificity. The approach is illustrated with data from a case-control study of lung cancer risk and occupational exposure to diesel engine emissions, in which exposure assessment was made by detailed job history interviews with study subjects followed by expert judgement. Using interrater agreement measured by kappas (κ), we estimate sensitivity and specificity of exposure assessment and derive misclassification-corrected confounder-adjusted OR. Misclassification-corrected and confounder-adjusted OR obtained with the most defensible prior had a posterior distribution centre of 1.6 with 95% credible interval (Crl) 1.1 to 2.6. This was on average greater in magnitude than frequentist point estimate of 1.3 (95% Crl 1.0 to 1.7). The method yields insights into the degree of exposure misclassification and appears to reduce attenuation bias due to misclassification of exposure while the estimated uncertainty increased. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparing exposure assessment methods for traffic-related air pollution in an adverse pregnancy outcome study

PubMed Central

Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate

2011-01-01

Background Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. Objectives To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly-used exposure assessment methods. Methods We identified 81,186 singleton births during 1997–2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NO), nitrogen oxides (NOx), ozone (O3), and particulate matter less than 2.5 (PM2.5) or less than 10 (PM10) μm in aerodynamic diameter], both unadjusted and temporally-adjusted land-use regression (LUR) model estimates (NO, NO2, and NOx), CALINE4 line-source air dispersion model estimates (NOx and PM2.5), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. Results We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO2, and NOx) and modeled through CALINE4 (NOx and PM2.5) and LUR (NO2 and NOx). Increased risk of preterm birth and very preterm birth were also positively associated with PM10 and PM2.5 air pollution measured at ambient stations. For LUR-modeled NO2 and NOx exposures, elevated risks for all the outcomes were observed in Los Angeles only – the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally-adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. Conclusion We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. PMID:21453913

Comparison of methods for estimating the attributable risk in the context of survival analysis.

PubMed

Gassama, Malamine; Bénichou, Jacques; Dartois, Laureen; Thiébaut, Anne C M

2017-01-23

The attributable risk (AR) measures the proportion of disease cases that can be attributed to an exposure in the population. Several definitions and estimation methods have been proposed for survival data. Using simulations, we compared four methods for estimating AR defined in terms of survival functions: two nonparametric methods based on Kaplan-Meier's estimator, one semiparametric based on Cox's model, and one parametric based on the piecewise constant hazards model, as well as one simpler method based on estimated exposure prevalence at baseline and Cox's model hazard ratio. We considered a fixed binary exposure with varying exposure probabilities and strengths of association, and generated event times from a proportional hazards model with constant or monotonic (decreasing or increasing) Weibull baseline hazard, as well as from a nonproportional hazards model. We simulated 1,000 independent samples of size 1,000 or 10,000. The methods were compared in terms of mean bias, mean estimated standard error, empirical standard deviation and 95% confidence interval coverage probability at four equally spaced time points. Under proportional hazards, all five methods yielded unbiased results regardless of sample size. Nonparametric methods displayed greater variability than other approaches. All methods showed satisfactory coverage except for nonparametric methods at the end of follow-up for a sample size of 1,000 especially. With nonproportional hazards, nonparametric methods yielded similar results to those under proportional hazards, whereas semiparametric and parametric approaches that both relied on the proportional hazards assumption performed poorly. These methods were applied to estimate the AR of breast cancer due to menopausal hormone therapy in 38,359 women of the E3N cohort. In practice, our study suggests to use the semiparametric or parametric approaches to estimate AR as a function of time in cohort studies if the proportional hazards assumption appears appropriate.

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

Comparing children's GPS tracks with geospatial proxies for exposure to junk food.

PubMed

Sadler, Richard C; Gilliland, Jason A

2015-01-01

Various geospatial techniques have been employed to estimate children's exposure to environmental cardiometabolic risk factors, including junk food. But many studies uncritically rely on exposure proxies which differ greatly from actual exposure. Misrepresentation of exposure by researchers could lead to poor decisions and ineffective policymaking. This study conducts a GIS-based analysis of GPS tracks--'activity spaces'--and 21 proxies for activity spaces (e.g. buffers, container approaches) for a sample of 526 children (ages 9-14) in London, Ontario, Canada. These measures are combined with a validated food environment database (including fast food and convenience stores) to create a series of junk food exposure estimates and quantify the errors resulting from use of different proxy methods. Results indicate that exposure proxies consistently underestimate exposure to junk foods by as much as 68%. This underestimation is important to policy development because children are exposed to more junk food than estimated using typical methods. Copyright © 2015 Elsevier Ltd. All rights reserved.

SYNTHESIS OF METHODS FOR ESTIMATING PEDESTRIAN AND BICYCLIST EXPOSURE TO RISK AT AREAWIDE LEVELS AND ON SPECIFIC TRANSPORTATION FACILITIES

DOT National Transportation Integrated Search

2017-01-01

This report summarizes the variety of methods used to estimate and evaluate exposure to risk in pedestrian and bicyclist safety analyses. In the literature, the most common definition of risk was a measure of the probability of a crash to occur given...

Effect of geocoding errors on traffic-related air pollutant exposure and concentration estimates

EPA Science Inventory

Exposure to traffic-related air pollutants is highest very near roads, and thus exposure estimates are sensitive to positional errors. This study evaluates positional and PM2.5 concentration errors that result from the use of automated geocoding methods and from linearized approx...

Confounding by season in ecologic studies of seasonal exposures and outcomes: examples from estimates of mortality due to influenza.

PubMed

Jackson, Michael L

2009-10-01

Many health outcomes exhibit seasonal variation in incidence, including accidents, suicides, and infections. For seasonal outcomes it can be difficult to distinguish the causal roles played by factors that also vary seasonally, such as weather, air pollution, and pathogen circulation. Various approaches to estimating the association between a seasonal exposure and a seasonal outcome in ecologic studies are reviewed, using studies of influenza-related mortality as an example. Because mortality rates vary seasonally and circulation of other respiratory viruses peaks during influenza season, it is a challenge to estimate which winter deaths were caused by influenza. Results of studies that estimated the contribution of influenza to all-cause mortality using different methods on the same data are compared. Methods for estimating associations between season exposures and outcomes vary greatly in their advantages, disadvantages, and assumptions. Even when applied to identical data, different methods can give greatly different results for the expected contribution of influenza to all-cause mortality. When the association between exposures and outcomes that vary seasonally is estimated, models must be selected carefully, keeping in mind the assumptions inherent in each model.

High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization.

PubMed

Biryol, Derya; Nicolas, Chantel I; Wambaugh, John; Phillips, Katherine; Isaacs, Kristin

2017-11-01

Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C 0 ) and chemical properties. The most predictive variables in the resulting model were C 0 , molecular weight, log K ow , and food type (R 2 =0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C 0 based on the functional role of chemicals in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R 2 =0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations. While these HT methods have large uncertainties (and thus may not be appropriate for assessments of single chemicals), they can provide critical refinement to aggregate exposure predictions used in risk-based chemical priority-setting. Published by Elsevier Ltd.

Modular Exposure Disaggregation Methodologies for Catastrophe Modelling using GIS and Remotely-Sensed Data

NASA Astrophysics Data System (ADS)

Foulser-Piggott, R.; Saito, K.; Spence, R.

2012-04-01

Loss estimates produced by catastrophe models are dependent on the quality of the input data, including both the hazard and exposure data. Currently, some of the exposure data input into a catastrophe model is aggregated over an area and therefore an estimate of the risk in this area may have a low level of accuracy. In order to obtain a more detailed and accurate loss estimate, it is necessary to have higher resolution exposure data. However, high resolution exposure data is not commonly available worldwide and therefore methods to infer building distribution and characteristics at higher resolution from existing information must be developed. This study is focussed on the development of disaggregation methodologies for exposure data which, if implemented in current catastrophe models, would lead to improved loss estimates. The new methodologies developed for disaggregating exposure data make use of GIS, remote sensing and statistical techniques. The main focus of this study is on earthquake risk, however the methods developed are modular so that they may be applied to different hazards. A number of different methods are proposed in order to be applicable to different regions of the world which have different amounts of data available. The new methods give estimates of both the number of buildings in a study area and a distribution of building typologies, as well as a measure of the vulnerability of the building stock to hazard. For each method, a way to assess and quantify the uncertainties in the methods and results is proposed, with particular focus on developing an index to enable input data quality to be compared. The applicability of the methods is demonstrated through testing for two study areas, one in Japan and the second in Turkey, selected because of the occurrence of recent and damaging earthquake events. The testing procedure is to use the proposed methods to estimate the number of buildings damaged at different levels following a scenario earthquake event. This enables the results of the models to be compared with real data and the relative performance of the different methodologies to be evaluated. A sensitivity analysis is also conducted for two main reasons. Firstly, to determine the key input variables in the methodology that have the most significant impact on the resulting loss estimate. Secondly, to enable the uncertainty in the different approaches to be quantified and therefore provide a range of uncertainty in the loss estimates.

Accounting for multiple climate components when estimating climate change exposure and velocity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

Relation of Whole Blood Carboxyhemoglobin Concentration to Ambient Carbon Monoxide Exposure Estimated Using Regression

PubMed Central

Rudra, Carole B.; Williams, Michelle A.; Sheppard, Lianne; Koenig, Jane Q.; Schiff, Melissa A.; Frederick, Ihunnaya O.; Dills, Russell

2010-01-01

Exposure to carbon monoxide (CO) and other ambient air pollutants is associated with adverse pregnancy outcomes. While there are several methods of estimating CO exposure, few have been evaluated against exposure biomarkers. The authors examined the relation between estimated CO exposure and blood carboxyhemoglobin concentration in 708 pregnant western Washington State women (1996–2004). Carboxyhemoglobin was measured in whole blood drawn around 13 weeks’ gestation. CO exposure during the month of blood draw was estimated using a regression model containing predictor terms for year, month, street and population densities, and distance to the nearest major road. Year and month were the strongest predictors. Carboxyhemoglobin level was correlated with estimated CO exposure (ρ = 0.22, 95% confidence interval (CI): 0.15, 0.29). After adjustment for covariates, each 10% increase in estimated exposure was associated with a 1.12% increase in median carboxyhemoglobin level (95% CI: 0.54, 1.69). This association remained after exclusion of 286 women who reported smoking or being exposed to secondhand smoke (ρ = 0.24). In this subgroup, the median carboxyhemoglobin concentration increased 1.29% (95% CI: 0.67, 1.91) for each 10% increase in CO exposure. Monthly estimated CO exposure was moderately correlated with an exposure biomarker. These results support the validity of this regression model for estimating ambient CO exposures in this population and geographic setting. PMID:20308199

Relation of whole blood carboxyhemoglobin concentration to ambient carbon monoxide exposure estimated using regression.

PubMed

Rudra, Carole B; Williams, Michelle A; Sheppard, Lianne; Koenig, Jane Q; Schiff, Melissa A; Frederick, Ihunnaya O; Dills, Russell

2010-04-15

Exposure to carbon monoxide (CO) and other ambient air pollutants is associated with adverse pregnancy outcomes. While there are several methods of estimating CO exposure, few have been evaluated against exposure biomarkers. The authors examined the relation between estimated CO exposure and blood carboxyhemoglobin concentration in 708 pregnant western Washington State women (1996-2004). Carboxyhemoglobin was measured in whole blood drawn around 13 weeks' gestation. CO exposure during the month of blood draw was estimated using a regression model containing predictor terms for year, month, street and population densities, and distance to the nearest major road. Year and month were the strongest predictors. Carboxyhemoglobin level was correlated with estimated CO exposure (rho = 0.22, 95% confidence interval (CI): 0.15, 0.29). After adjustment for covariates, each 10% increase in estimated exposure was associated with a 1.12% increase in median carboxyhemoglobin level (95% CI: 0.54, 1.69). This association remained after exclusion of 286 women who reported smoking or being exposed to secondhand smoke (rho = 0.24). In this subgroup, the median carboxyhemoglobin concentration increased 1.29% (95% CI: 0.67, 1.91) for each 10% increase in CO exposure. Monthly estimated CO exposure was moderately correlated with an exposure biomarker. These results support the validity of this regression model for estimating ambient CO exposures in this population and geographic setting.

[Regression on order statistics and its application in estimating nondetects for food exposure assessment].

PubMed

Yu, Xiaojin; Liu, Pei; Min, Jie; Chen, Qiguang

2009-01-01

To explore the application of regression on order statistics (ROS) in estimating nondetects for food exposure assessment. Regression on order statistics was adopted in analysis of cadmium residual data set from global food contaminant monitoring, the mean residual was estimated basing SAS programming and compared with the results from substitution methods. The results show that ROS method performs better obviously than substitution methods for being robust and convenient for posterior analysis. Regression on order statistics is worth to adopt,but more efforts should be make for details of application of this method.

Statistical modeling of occupational chlorinated solvent exposures for case–control studies using a literature-based database

PubMed Central

Hein, Misty J.; Waters, Martha A.; Ruder, Avima M.; Stenzel, Mark R.; Blair, Aaron; Stewart, Patricia A.

2010-01-01

Objectives: Occupational exposure assessment for population-based case–control studies is challenging due to the wide variety of industries and occupations encountered by study participants. We developed and evaluated statistical models to estimate the intensity of exposure to three chlorinated solvents—methylene chloride, 1,1,1-trichloroethane, and trichloroethylene—using a database of air measurement data and associated exposure determinants. Methods: A measurement database was developed after an extensive review of the published industrial hygiene literature. The database of nearly 3000 measurements or summary measurements included sample size, measurement characteristics (year, duration, and type), and several potential exposure determinants associated with the measurements: mechanism of release (e.g. evaporation), process condition, temperature, usage rate, type of ventilation, location, presence of a confined space, and proximity to the source. The natural log-transformed measurement levels in the exposure database were modeled as a function of the measurement characteristics and exposure determinants using maximum likelihood methods. Assuming a single lognormal distribution of the measurements, an arithmetic mean exposure intensity level was estimated for each unique combination of exposure determinants and decade. Results: The proportions of variability in the measurement data explained by the modeled measurement characteristics and exposure determinants were 36, 38, and 54% for methylene chloride, 1,1,1-trichloroethane, and trichloroethylene, respectively. Model parameter estimates for the exposure determinants were in the anticipated direction. Exposure intensity estimates were plausible and exhibited internal consistency, but the ability to evaluate validity was limited. Conclusions: These prediction models can be used to estimate chlorinated solvent exposure intensity for jobs reported by population-based case–control study participants that have sufficiently detailed information regarding the exposure determinants. PMID:20418277

Assessment of public health impact of work-related asthma.

PubMed

Jaakkola, Maritta S; Jaakkola, Jouni J K

2012-03-05

Asthma is among the most common chronic diseases in working-aged populations and occupational exposures are important causal agents. Our aims were to evaluate the best methods to assess occurrence, public health impact, and burden to society related to occupational or work-related asthma and to achieve comparable estimates for different populations. We addressed three central questions: 1: What is the best method to assess the occurrence of occupational asthma? We evaluated: 1) assessment of the occurrence of occupational asthma per se, and 2) assessment of adult-onset asthma and the population attributable fractions due to specific occupational exposures. 2: What are the best methods to assess public health impact and burden to society related to occupational or work-related asthma? We evaluated methods based on assessment of excess burden of disease due to specific occupational exposures. 3: How to achieve comparable estimates for different populations? We evaluated comparability of estimates of occurrence and burden attributable to occupational asthma based on different methods. Assessment of the occurrence of occupational asthma per se can be used in countries with good coverage of the identification system for occupational asthma, i.e. countries with well-functioning occupational health services. Assessment based on adult-onset asthma and population attributable fractions due to specific occupational exposures is a good approach to estimate the occurrence of occupational asthma at the population level. For assessment of public health impact from work-related asthma we recommend assessing excess burden of disease due to specific occupational exposures, including excess incidence of asthma complemented by an assessment of disability from it. International comparability of estimates can be best achieved by methods based on population attributable fractions. Public health impact assessment for occupational asthma is central in prevention and health policy planning and could be improved by purposeful development of methods for assessing health benefits from preventive actions. Registry-based methods are suitable for evaluating time-trends of occurrence at a given population but for international comparisons they face serious limitations. Assessment of excess burden of disease due to specific occupational exposure is a useful measure, when there is valid information on population exposure and attributable fractions.

Estimation of surface area concentration of workplace incidental nanoparticles based on number and mass concentrations

NASA Astrophysics Data System (ADS)

Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.

2011-10-01

Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SAREF) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SAPSD) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SAINV1) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SAINV2) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SAPSD was 0.7-1.8 times higher and SAINV1 and SAINV2 were 2.2-8 times higher than SAREF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SAREF. However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SAREF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SAPSD) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.

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

RESIDENTIAL INDOOR EXPOSURES OF CHILDREN TO PESTICIDES FOLLOWING LAWN APPLICATIONS

EPA Science Inventory

Methods have been developed to estimate children's residential exposures to pesticide residues and applied in a small field study of indoor exposures resulting from the intrusion of lawn-applied herbicide into the home. Sampling methods included size-selective indoor air sampli...

A Method for Semi-quantitative Assessment of Exposure to Pesticides of Applicators and Re-entry Workers: An Application in Three Farming Systems in Ethiopia.

PubMed

Negatu, Beyene; Vermeulen, Roel; Mekonnen, Yalemtshay; Kromhout, Hans

2016-07-01

To develop an inexpensive and easily adaptable semi-quantitative exposure assessment method to characterize exposure to pesticide in applicators and re-entry farmers and farm workers in Ethiopia. Two specific semi-quantitative exposure algorithms for pesticides applicators and re-entry workers were developed and applied to 601 farm workers employed in 3 distinctly different farming systems [small-scale irrigated, large-scale greenhouses (LSGH), and large-scale open (LSO)] in Ethiopia. The algorithm for applicators was based on exposure-modifying factors including application methods, farm layout (open or closed), pesticide mixing conditions, cleaning of spraying equipment, intensity of pesticide application per day, utilization of personal protective equipment (PPE), personal hygienic behavior, annual frequency of application, and duration of employment at the farm. The algorithm for re-entry work was based on an expert-based re-entry exposure intensity score, utilization of PPE, personal hygienic behavior, annual frequency of re-entry work, and duration of employment at the farm. The algorithms allowed estimation of daily, annual and cumulative lifetime exposure for applicators, and re-entry workers by farming system, by gender, and by age group. For all metrics, highest exposures occurred in LSGH for both applicators and female re-entry workers. For male re-entry workers, highest cumulative exposure occurred in LSO farms. Female re-entry workers appeared to be higher exposed on a daily or annual basis than male re-entry workers, but their cumulative exposures were similar due to the fact that on average males had longer tenure. Factors related to intensity of exposure (like application method and farm layout) were indicated as the main driving factors for estimated potential exposure. Use of personal protection, hygienic behavior, and duration of employment in surveyed farm workers contributed less to the contrast in exposure estimates. This study indicated that farmers' and farm workers' exposure to pesticides can be inexpensively characterized, ranked, and classified. Our method could be extended to assess exposure to specific active ingredients provided that detailed information on pesticides used is available. The resulting exposure estimates will consequently be used in occupational epidemiology studies in Ethiopia and other similar countries with few resources. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

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

Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

PubMed

Samoli, Evangelia; Butland, Barbara K

2017-12-01

Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

Measurement Error and Environmental Epidemiology: A Policy Perspective

PubMed Central

Edwards, Jessie K.; Keil, Alexander P.

2017-01-01

Purpose of review Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making. Recent findings We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention. Summary Under a policy perspective, the analysis must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology. PMID:28138941

Efficient estimation of the attributable fraction when there are monotonicity constraints and interactions.

PubMed

Traskin, Mikhail; Wang, Wei; Ten Have, Thomas R; Small, Dylan S

2013-01-01

The PAF for an exposure is the fraction of disease cases in a population that can be attributed to that exposure. One method of estimating the PAF involves estimating the probability of having the disease given the exposure and confounding variables. In many settings, the exposure will interact with the confounders and the confounders will interact with each other. Also, in many settings, the probability of having the disease is thought, based on subject matter knowledge, to be a monotone increasing function of the exposure and possibly of some of the confounders. We develop an efficient approach for estimating logistic regression models with interactions and monotonicity constraints, and apply this approach to estimating the population attributable fraction (PAF). Our approach produces substantially more accurate estimates of the PAF in some settings than the usual approach which uses logistic regression without monotonicity constraints.

Validation of an aggregate exposure model for substances in consumer products: a case study of diethyl phthalate in personal care products

PubMed Central

Delmaar, Christiaan; Bokkers, Bas; ter Burg, Wouter; Schuur, Gerlienke

2015-01-01

As personal care products (PCPs) are used in close contact with a person, they are a major source of consumer exposure to chemical substances contained in these products. The estimation of realistic consumer exposure to substances in PCPs is currently hampered by the lack of appropriate data and methods. To estimate aggregate exposure of consumers to substances contained in PCPs, a person-oriented consumer exposure model has been developed (the Probabilistic Aggregate Consumer Exposure Model, PACEM). The model simulates daily exposure in a population based on product use data collected from a survey among the Dutch population. The model is validated by comparing diethyl phthalate (DEP) dose estimates to dose estimates based on biomonitoring data. It was found that the model's estimates compared well with the estimates based on biomonitoring data. This suggests that the person-oriented PACEM model is a practical tool for assessing realistic aggregate exposures to substances in PCPs. In the future, PACEM will be extended with use pattern data on other product groups. This will allow for assessing aggregate exposure to substances in consumer products across different product groups. PMID:25352161

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions.

PubMed

Gan, Ryan W; Ford, Bonne; Lassman, William; Pfister, Gabriele; Vaidyanathan, Ambarish; Fischer, Emily; Volckens, John; Pierce, Jeffrey R; Magzamen, Sheryl

2017-03-01

Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM 2.5 ) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM 2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM 2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM 2.5 . A 10 μg/m 3 increase in GWR smoke PM 2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019-1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM 2.5 exposure method: a 10 μg/m 3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026-1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931-1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM 2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.

Reducing attenuation in exposure-response relationships by exposure modeling and grouping: the relationship between wood dust exposure and lung function.

PubMed

Teschke, Kay; Spierings, Judith; Marion, Stephen A; Demers, Paul A; Davies, Hugh W; Kennedy, Susan M

2004-12-01

In a study of wood dust exposure and lung function, we tested the effect on the exposure-response relationship of six different exposure metrics using the mean measured exposure of each subject versus the mean exposure based on various methods of grouping subjects, including job-based groups and groups based on an empirical model of the determinants of exposure. Multiple linear regression was used to examine the association between wood dust concentration and forced expiratory volume in 1s (FEV(1)), adjusting for age, sex, height, race, pediatric asthma, and smoking. Stronger point estimates of the exposure-response relationships were observed when exposures were based on increasing levels of aggregation, allowing the relationships to be found statistically significant in four of the six metrics. The strongest point estimates were found when exposures were based on the determinants of exposure model. Determinants of exposure modeling offers the potential for improvement in risk estimation equivalent to or beyond that from job-based exposure grouping.

Cumulative Retrospective Exposure Assessment (REA) as a predictor of amphibole asbestos lung burden: validation procedures and results for industrial hygiene and pathology estimates.

PubMed

Rasmuson, James O; Roggli, Victor L; Boelter, Fred W; Rasmuson, Eric J; Redinger, Charles F

2014-01-01

A detailed evaluation of the correlation and linearity of industrial hygiene retrospective exposure assessment (REA) for cumulative asbestos exposure with asbestos lung burden analysis (LBA) has not been previously performed, but both methods are utilized for case-control and cohort studies and other applications such as setting occupational exposure limits. (a) To correlate REA with asbestos LBA for a large number of cases from varied industries and exposure scenarios; (b) to evaluate the linearity, precision, and applicability of both industrial hygiene exposure reconstruction and LBA; and (c) to demonstrate validation methods for REA. A panel of four experienced industrial hygiene raters independently estimated the cumulative asbestos exposure for 363 cases with limited exposure details in which asbestos LBA had been independently determined. LBA for asbestos bodies was performed by a pathologist by both light microscopy and scanning electron microscopy (SEM) and free asbestos fibers by SEM. Precision, reliability, correlation and linearity were evaluated via intraclass correlation, regression analysis and analysis of covariance. Plaintiff's answers to interrogatories, work history sheets, work summaries or plaintiff's discovery depositions that were obtained in court cases involving asbestos were utilized by the pathologist to provide a summarized brief asbestos exposure and work history for each of the 363 cases. Linear relationships between REA and LBA were found when adjustment was made for asbestos fiber-type exposure differences. Significant correlation between REA and LBA was found with amphibole asbestos lung burden and mixed fiber-types, but not with chrysotile. The intraclass correlation coefficients (ICC) for the precision of the industrial hygiene rater cumulative asbestos exposure estimates and the precision of repeated laboratory analysis were found to be in the excellent range. The ICC estimates were performed independent of specific asbestos fiber-type. Both REA and pathology assessment are reliable and complementary predictive methods to characterize asbestos exposures. Correlation analysis between the two methods effectively validates both REA methodology and LBA procedures within the determined precision, particularly for cumulative amphibole asbestos exposures since chrysotile fibers, for the most part, are not retained in the lung for an extended period of time.

Exposure Estimation and Interpretation of Occupational Risk: Enhanced Information for the Occupational Risk Manager

PubMed Central

Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa

2015-01-01

The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve—the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice. PMID:26302336

Comparing exposure assessment methods for traffic-related air pollution in an adverse pregnancy outcome study.

PubMed

Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate

2011-07-01

Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly used exposure assessment methods. We identified 81,186 singleton births during 1997-2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO(2)), nitric oxide (NO), nitrogen oxides (NO(x)), ozone (O(3)), and particulate matter less than 2.5 (PM(2.5)) or less than 10 (PM(10))μm in aerodynamic diameter], both unadjusted and temporally adjusted land-use regression (LUR) model estimates (NO, NO(2), and NO(x)), CALINE4 line-source air dispersion model estimates (NO(x) and PM(2.5)), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO(2), and NO(x)) and modeled through CALINE4 (NO(x) and PM(2.5)) and LUR (NO(2) and NO(x)). Increased risk of preterm birth and very preterm birth were also positively associated with PM(10) and PM(2.5) air pollution measured at ambient stations. For LUR-modeled NO(2) and NO(x) exposures, elevated risks for all the outcomes were observed in Los Angeles only--the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. Copyright © 2011 Elsevier Inc. All rights reserved.

Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models.

PubMed

Hoffmann, Sabine; Laurier, Dominique; Rage, Estelle; Guihenneuc, Chantal; Ancelet, Sophie

2018-01-01

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies.

Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models

PubMed Central

Laurier, Dominique; Rage, Estelle

2018-01-01

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies. PMID:29408862

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies

NASA Astrophysics Data System (ADS)

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-01

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies.

PubMed

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-07

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

Exposure assessment of tetrafluoroethylene and ammonium perfluorooctanoate 1951-2002.

PubMed

Sleeuwenhoek, Anne; Cherrie, John W

2012-03-01

To develop a method to reconstruct exposure to tetrafluoroethylene (TFE) and ammonium perfluorooctanoate (APFO) in plants producing polytetrafluoroethylene (PTFE) in the absence of suitable objective measurements. These data were used to inform an epidemiological study being carried out to investigate possible risks in workers employed in the manufacture of PTFE and to study trends in exposure over time. For each plant, detailed descriptions of all occupational titles, including tasks and changes over time, were obtained during semi-structured interviews with key plant personnel. A semi-quantitative assessment method was used to assess inhalation exposure to TFE and inhalation plus dermal exposure to APFO. Temporal trends in exposure to TFE and APFO were investigated. In each plant the highest exposures for both TFE and APFO occurred in the polymerisation area. Due to the introduction of control measures, increasing process automation and other improvements, exposures generally decreased over time. In the polymerisation area, the annual decline in exposure to TFE varied by plant from 3.8 to 5.7% and for APFO from 2.2 to 5.5%. A simple method for assessing exposure was developed which used detailed process information and job descriptions to estimate average annual TFE and APFO exposure on an arbitrary semi-quantitative scale. These semi-quantitative estimates are sufficient to identify relative differences in exposure for the epidemiological study and should good data become available, they could be used to provide quantitative estimates for all plants across the whole period of operation. This journal is © The Royal Society of Chemistry 2012

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses.

PubMed

Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick

2016-01-05

Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Handler, bystander and reentry exposure to TCDD from application of Agent Orange by C-123 aircraft during the Vietnam War.

PubMed

Ross, John H; Hewitt, Andrew; Armitage, James; Solomon, Keith; Watkins, Deborah K; Ginevan, Michael E

2015-02-01

Using validated models and methods routinely employed by pesticide regulatory agencies, the absorbed dosages of Agent Orange (AO) herbicide contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) were estimated for mixer/loaders, applicators, and individuals in the vicinity of applications of AO by C-123 aircraft during the Vietnam War. Resulting dosages of TCDD were then transformed to estimates of adipose residues, and compared to population biomonitoring of known mixer/loaders and applicators as well as ground troops in Vietnam and civilians in the U.S. Results demonstrate that mixer/loaders and applicators had the greatest exposures and their measured residues of TCDD in adipose were consistent with the estimated exposures. Further, the potentially exposed ground troops, including those who could have been directly sprayed during aerial defoliation, had measured adipose residues that were consistent with those in civilian U.S. populations with no defined source of exposure exposures and both of those cohorts had orders of magnitude less exposure than the mixer/loaders or applicators. Despite the availability of validated exposure modeling methods for decades, the quantitative TCDD dose estimates presented here are the first of their kind for the Vietnam conflict. Copyright © 2014 Elsevier B.V. All rights reserved.

ALTERNATIVE APPROACH TO ESTIMATING CANCER ...

EPA Pesticide Factsheets

The alternative approach for estimating cancer potency from inhalation exposure to asbestos seeks to improve the methods developed by USEPA (1986). This efforts seeks to modify the the current approach for estimating cancer potency for lung cancer and mesothelioma to account for the current scientific consensus that cancer risk from asbestos depends both on mineral type and on particle size distribution. In brief, epidemiological exposure-response data for lung cancer and mesothelioma in asbestos workers are combined with estimates of the mineral type(s) and partical size distribution at each exposure location in order to estimate potency factors that are specific to a selected set of mineral type and size

Development of a method for personal, spatiotemporal exposure assessment.

PubMed

Adams, Colby; Riggs, Philip; Volckens, John

2009-07-01

This work describes the development and evaluation of a high resolution, space and time-referenced sampling method for personal exposure assessment to airborne particulate matter (PM). This method integrates continuous measures of personal PM levels with the corresponding location-activity (i.e. work/school, home, transit) of the subject. Monitoring equipment include a small, portable global positioning system (GPS) receiver, a miniature aerosol nephelometer, and an ambient temperature monitor to estimate the location, time, and magnitude of personal exposure to particulate matter air pollution. Precision and accuracy of each component, as well as the integrated method performance were tested in a combination of laboratory and field tests. Spatial data was apportioned into pre-determined location-activity categories (i.e. work/school, home, transit) with a simple, temporospatially-based algorithm. The apportioning algorithm was extremely effective with an overall accuracy of 99.6%. This method allows examination of an individual's estimated exposure through space and time, which may provide new insights into exposure-activity relationships not possible with traditional exposure assessment techniques (i.e., time-integrated, filter-based measurements). Furthermore, the method is applicable to any contaminant or stressor that can be measured on an individual with a direct-reading sensor.

PARTNERING TO IMPROVE HUMAN EXPOSURE METHODS

EPA Science Inventory

Methods development research is an application-driven scientific area that addresses programmatic needs. The goals are to reduce measurement uncertainties, address data gaps, and improve existing analytical procedures for estimating human exposures. Partnerships have been develop...

MEASUREMENT ERROR ESTIMATION AND CORRECTION METHODS TO MINIMIZE EXPOSURE MISCLASSIFICATION IN EPIDEMIOLOGICAL STUDIES: PROJECT SUMMARY

EPA Science Inventory

This project summary highlights recent findings from research undertaken to develop improved methods to assess potential human health risks related to drinking water disinfection byproduct (DBP) exposures.

Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth

EPA Science Inventory

OBJECTIVES: Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassificat ion and inconsistencies in risk estimates, particu...

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.

Aggregate exposure modelling of zinc pyrithione in rinse-off personal cleansing products using a person-orientated approach with market share refinement.

PubMed

Tozer, Sarah A; Kelly, Seamus; O'Mahony, Cian; Daly, E J; Nash, J F

2015-09-01

Realistic estimates of chemical aggregate exposure are needed to ensure consumer safety. As exposure estimates are a critical part of the equation used to calculate acceptable "safe levels" and conduct quantitative risk assessments, methods are needed to produce realistic exposure estimations. To this end, a probabilistic aggregate exposure model was developed to estimate consumer exposure from several rinse off personal cleansing products containing the anti-dandruff preservative zinc pyrithione. The model incorporates large habits and practices surveys, containing data on frequency of use, amount applied, co-use along with market share, and combines these data at the level of the individual based on subject demographics to better estimate exposure. The daily-applied exposure (i.e., amount applied to the skin) was 3.79 mg/kg/day for the 95th percentile consumer. The estimated internal dose for the 95th percentile exposure ranged from 0.01-1.29 μg/kg/day after accounting for retention following rinsing and dermal penetration of ZnPt. This probabilistic aggregate exposure model can be used in the human safety assessment of ingredients in multiple rinse-off technologies (e.g., shampoo, bar soap, body wash, and liquid hand soap). In addition, this model may be used in other situations where refined exposure assessment is required to support a chemical risk assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of dietary intake of flavouring substances within the procedure for their safety evaluation: advantages and limitations of estimates obtained by means of a per capita method.

PubMed

Arcella, D; Leclercq, C

2005-01-01

The procedure for the safety evaluation of flavourings adopted by the European Commission in order to establish a positive list of these substances is a stepwise approach which was developed by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) and amended by the Scientific Committee on Food. Within this procedure, a per capita amount based on industrial poundage data of flavourings, is calculated to estimate the dietary intake by means of the maximised survey-derived daily intake (MSDI) method. This paper reviews the MSDI method in order to check if it can provide conservative intake estimates as needed at the first steps of a stepwise procedure. Scientific papers and opinions dealing with the MSDI method were reviewed. Concentration levels reported by the industry were compared with estimates obtained with the MSDI method. It appeared that, in some cases, these estimates could be orders of magnitude (up to 5) lower than those calculated considering concentration levels provided by the industry and regular consumption of flavoured foods and beverages. A critical review of two studies which had been used to support the statement that MSDI is a conservative method for assessing exposure to flavourings among high consumers was performed. Special attention was given to the factors that affect exposure at high percentiles, such as brand loyalty and portion sizes. It is concluded that these studies may not be suitable to validate the MSDI method used to assess intakes of flavours by European consumers due to shortcomings in the assumptions made and in the data used. Exposure assessment is an essential component of risk assessment. The present paper suggests that the MSDI method is not sufficiently conservative. There is therefore a clear need for either using an alternative method to estimate exposure to flavourings in the procedure or for limiting intakes to the levels at which the safety was assessed.

Health survey of former workers in a Norwegian coke plant: Part. 1. Estimation of historical exposures

PubMed Central

Romundstad, P. R.; Ronneberg, A.; Leira, H. L.; Bye, T.

1998-01-01

OBJECTIVE: To estimate historical exposure levels at a coke plant for all agents considered to be of importance for epidemiological studies of mortality and cancer incidence. METHODS: Time weighted average exposure (8 h TWA) was estimated based on personal measurements for polycyclic aromatic hydrocarbons (PAHs) and carbonaceous particulates. Exposure to quartz was estimated relative to the concentration of carbonaceous particulates. These estimates were adjusted for the use of airstream helmets. Exposure to other agents were estimated qualitatively (asbestos, benzene, and arsenic) or semi-quantitatively (carbon monoxide (CO) and heat) based on measurements and other indicators of exposure. RESULTS: Exposure to PAHs was highest for those who worked at the top of the ovens (300 micrograms/m3) in the period from 1970-6. The estimated PAH exposure was reduced to an average of 65 micrograms/m3 after the introduction of exposure control measures in 1976. The estimates for carbonaceous particulates ranged from 1 to 16 mg/m3, with the highest exposure for workers at the top of the ovens and at the coke screening station. CONCLUSIONS: The exposure of greatest concern in this study is to PAHs, but exposures to carbonaceous particulates and CO may also be of importance. The major limitations of this study are the lack of personal measurements before 1975 and the total lack of measurements for some of the exposed categories of workers. Despite these limitations, we think that this assessment reflects the actual exposures for most of the former employees. The assessment thus provides a reasonable tool for the subsequent epidemiological study and for future epidemiological follow up studies at the coke plant.   PMID:9861184

Causal Methods for Observational Research: A Primer.

PubMed

Almasi-Hashiani, Amir; Nedjat, Saharnaz; Mansournia, Mohammad Ali

2018-04-01

The goal of many observational studies is to estimate the causal effect of an exposure on an outcome after adjustment for confounders, but there are still some serious errors in adjusting confounders in clinical journals. Standard regression modeling (e.g., ordinary logistic regression) fails to estimate the average effect of exposure in total population in the presence of interaction between exposure and covariates, and also cannot adjust for time-varying confounding appropriately. Moreover, stepwise algorithms of the selection of confounders based on P values may miss important confounders and lead to bias in effect estimates. Causal methods overcome these limitations. We illustrate three causal methods including inverse-probability-of-treatment-weighting (IPTW) and parametric g-formula, with an emphasis on a clever combination of these 2 methods: targeted maximum likelihood estimation (TMLE) which enjoys a double-robust property against bias. © 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Impact of Geocoding Methods on Associations between Long-term Exposure to Urban Air Pollution and Lung Function

PubMed Central

Jacquemin, Bénédicte; Lepeule, Johanna; Boudier, Anne; Arnould, Caroline; Benmerad, Meriem; Chappaz, Claire; Ferran, Joane; Kauffmann, Francine; Morelli, Xavier; Pin, Isabelle; Pison, Christophe; Rios, Isabelle; Temam, Sofia; Künzli, Nino; Slama, Rémy

2013-01-01

Background: Errors in address geocodes may affect estimates of the effects of air pollution on health. Objective: We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults. Methods: We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant’s address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects. Results: Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 μg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: –0.56, –6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: –0.14, –3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted –2.81 (95% CI: –0.26, –5.35) using NavTEQ, or 2.08 (95% CI –4.63, 0.47, p = 0.11) using Google Maps]. Conclusions: Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model. Citation: Jacquemin B, Lepeule J, Boudier A, Arnould C, Benmerad M, Chappaz C, Ferran J, Kauffmann F, Morelli X, Pin I, Pison C, Rios I, Temam S, Künzli N, Slama R, Siroux V. 2013. Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function. Environ Health Perspect 121:1054–1060; http://dx.doi.org/10.1289/ehp.1206016 PMID:23823697

A QUANTITATIVE APPROACH FOR ESTIMATING EXPOSURE TO PESTICIDES IN THE AGRICULTURAL HEALTH STUDY

EPA Science Inventory

We developed a quantitative method to estimate chemical-specific pesticide exposures in a large prospective cohort study of over 58,000 pesticide applicators in North Carolina and Iowa. An enrollment questionnaire was administered to applicators to collect basic time- and inten...

Airline Pilot Cosmic Radiation and Circadian Disruption Exposure Assessment from Logbooks and Company Records

PubMed Central

Grajewski, Barbara; Waters, Martha A.; Yong, Lee C.; Tseng, Chih-Yu; Zivkovich, Zachary; Cassinelli II, Rick T.

2011-01-01

Objectives: US commercial airline pilots, like all flight crew, are at increased risk for specific cancers, but the relation of these outcomes to specific air cabin exposures is unclear. Flight time or block (airborne plus taxi) time often substitutes for assessment of exposure to cosmic radiation. Our objectives were to develop methods to estimate exposures to cosmic radiation and circadian disruption for a study of chromosome aberrations in pilots and to describe workplace exposures for these pilots. Methods: Exposures were estimated for cosmic ionizing radiation and circadian disruption between August 1963 and March 2003 for 83 male pilots from a major US airline. Estimates were based on 523 387 individual flight segments in company records and pilot logbooks as well as summary records of hours flown from other sources. Exposure was estimated by calculation or imputation for all but 0.02% of the individual flight segments’ block time. Exposures were estimated from questionnaire data for a comparison group of 51 male university faculty. Results: Pilots flew a median of 7126 flight segments and 14 959 block hours for 27.8 years. In the final study year, a hypothetical pilot incurred an estimated median effective dose of 1.92 mSv (absorbed dose, 0.85 mGy) from cosmic radiation and crossed 362 time zones. This study pilot was possibly exposed to a moderate or large solar particle event a median of 6 times or once every 3.7 years of work. Work at the study airline and military flying were the two highest sources of pilot exposure for all metrics. An index of work during the standard sleep interval (SSI travel) also suggested potential chronic sleep disturbance in some pilots. For study airline flights, median segment radiation doses, time zones crossed, and SSI travel increased markedly from the 1990s to 2003 (Ptrend < 0.0001). Dose metrics were moderately correlated with records-based duration metrics (Spearman’s r = 0.61–0.69). Conclusions: The methods developed provided an exposure profile of this group of US airline pilots, many of whom have been exposed to increasing cosmic radiation and circadian disruption from the 1990s through 2003. This assessment is likely to decrease exposure misclassification in health studies. PMID:21610083

Assessing covariate balance when using the generalized propensity score with quantitative or continuous exposures.

PubMed

Austin, Peter C

2018-01-01

Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures (e.g., active treatment vs. control). The generalized propensity score is an extension of the propensity score for use with quantitative exposures (e.g., dose or quantity of medication, income, years of education). A crucial component of any propensity score analysis is that of balance assessment. This entails assessing the degree to which conditioning on the propensity score (via matching, weighting, or stratification) has balanced measured baseline covariates between exposure groups. Methods for balance assessment have been well described and are frequently implemented when using the propensity score with binary exposures. However, there is a paucity of information on how to assess baseline covariate balance when using the generalized propensity score. We describe how methods based on the standardized difference can be adapted for use with quantitative exposures when using the generalized propensity score. We also describe a method based on assessing the correlation between the quantitative exposure and each covariate in the sample when weighted using generalized propensity score -based weights. We conducted a series of Monte Carlo simulations to evaluate the performance of these methods. We also compared two different methods of estimating the generalized propensity score: ordinary least squared regression and the covariate balancing propensity score method. We illustrate the application of these methods using data on patients hospitalized with a heart attack with the quantitative exposure being creatinine level.

Task based exposure assessment in ergonomic epidemiology: a study of upper arm elevation in the jobs of machinists, car mechanics, and house painters

PubMed Central

Svendsen, S; Mathiassen, S; Bonde, J

2005-01-01

Aims: To explore the precision of task based estimates of upper arm elevation in three occupational groups, compared to direct measurements of job exposure. Methods: Male machinists (n = 26), car mechanics (n = 23), and house painters (n = 23) were studied. Whole day recordings of upper arm elevation were obtained for four consecutive working days, and associated task information was collected in diaries. For each individual, task based estimates of job exposure were calculated by weighting task exposures from a collective database by task proportions according to the diaries. These estimates were validated against directly measured job exposures using linear regression. The performance of the task based approach was expressed through the gain in precision of occupational group mean exposures that could be obtained by adding subjects with task based estimates to a group of subjects with measured job exposures in a "validation" design. Results: In all three occupations, tasks differed in mean exposure, and task proportions varied between individuals. Task based estimation proved inefficient, with squared correlation coefficients only occasionally exceeding 0.2 for the relation between task based and measured job exposures. Consequently, it was not possible to substantially improve the precision of an estimated group mean by including subjects whose job exposures were based on task information. Conclusions: Task based estimates of mechanical job exposure can be very imprecise, and only marginally better than estimates based on occupation. It is recommended that investigators in ergonomic epidemiology consider the prospects of task based exposure assessment carefully before placing resources at obtaining task information. Strategies disregarding tasks may be preferable in many cases. PMID:15613604

The associations between birth outcomes and satellite-estimated maternal PM2.5 exposure in Shanghai, China

NASA Astrophysics Data System (ADS)

Xiao, Q.; Liu, Y.; Strickland, M. J.; Chang, H. H.; Kan, H.

2017-12-01

Background: Satellite remote sensing data have been employed for air pollution exposure assessment, with the intent of better characterizing exposure spatio-temproal variations. However, non-random missingness in satellite data may lead to exposure error. Objectives: We explored the differences in health effect estimates due to different exposure metrics, with and without satellite data, when analyzing the associations between maternal PM2.5 exposure and birth outcomes. Methods: We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. Trimester-specific and total pregnancy exposures were estimated from satellite PM2.5 predictions with missingness, gap-filled satellite PM2.5 predictions with complete coverage and regional average PM2.5 measurements from monitoring stations. Linear regressions estimated associations between birth weight and maternal PM2.5 exposure. Logistic regressions estimated associations between preterm birth and the first and second trimester exposure. Discrete-time models estimated third trimester and total pregnancy associations with preterm birth. Effect modifications by maternal age and parental education levels were investigated. Results: we observed statistically significant associations between maternal PM2.5 exposure during all exposure windows and adverse birth outcomes. A 10 µg/m3 increase in pregnancy PM2.5 exposure was associated with a 12.85 g (95% CI: 18.44, 7.27) decrease in birth weight for term births, and a 27% (95% CI: 20%, 36%) increase in the risk of preterm birth. Greater effects were observed between first and third trimester exposure and birth weight, as well as between first trimester exposure and preterm birth. Mothers older than 35 years and without college education tended to have higher associations with preterm birth. Conclusions: Gap-filled satellite data derived PM2.5 exposure estimates resulted in reduced exposure error and more precise health effect estimates.

Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

PubMed

Wang, Wei; Griswold, Michael E

2016-11-30

The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

HUMAN EXPOSURE MODELING: CONCEPTS, METHODS, AND TOOLS

EPA Science Inventory

Understanding human exposure is critical when estimating the occurrence of deleterious effects that could follow contact with environmental contaminants. For many pollutants, the intensity, duration, frequency, route, and timing of exposure is highly variable, particularly whe...

New High Throughput Methods to Estimate Chemical ...

EPA Pesticide Factsheets

EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing and screening chemicals. A recent report by the National Research Council of the National Academies, Exposure Science in the 21st Century: A Vision and a Strategy (NRC 2012) laid out a number of applications in chemical evaluation of both toxicity and risk in critical need of quantitative exposure predictions, including screening and prioritization of chemicals for targeted toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability. Despite these significant needs, for the majority of chemicals (e.g. non-pesticide environmental compounds) there are no or limited estimates of exposure. For example, exposure estimates exist for only 7% of the ToxCast Phase II chemical list. In addition, the data required for generating exposure estimates for large numbers of chemicals is severely lacking (Egeghy et al. 2012). This SAP reviewed the use of EPA's ExpoCast model to rapidly estimate potential chemical exposures for prioritization and screening purposes. The focus was on bounded chemical exposure values for people and the environment for the Endocrine Disruptor Screening Program (EDSP) Universe of Chemicals. In addition to exposure, the SAP

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

Linkage of the National Health Interview Survey to air quality data.

PubMed

Parker, Jennifer D; Kravets, Nataliya; Woodruff, Tracey J

2008-02-01

This report describes the linkage between the National Health Interview Survey (NHIS) and air monitoring data from the U.S. Environmental Protection Agency (EPA). There have been few linkages of these data sources, partly because of restrictions on releasing geographic detail from NHIS on public-use files in order to protect participant confidentiality. Pollution exposures for NHIS respondents were calculated by averaging the annual average exposure estimates from EPA air monitors both within 5, 10, 15, and 20 miles of the respondent's block-group location (which is available on restricted NHIS data files) and by county of residence. The 1987-2005 linked data files--referred to as NHIS-EPAAnnualAir--were used to describe the percentage of NHIS respondents linked and the median exposures by linkage method, survey year, and pollutant. Using the 2005 NHIS-EPAAnnualAir data file, the percentage linked and median exposure were described by respondent characteristics, linkage method, and pollutant. Many decisions were made to define pollution exposures for NHIS respondents, including monitor selection, location assignment for NHIS respondents, and geographic linkage criteria. Geographic linkage criteria for assigning area-level exposure estimates affected the percentage and composition of respondents included in the resulting linked sample. Median exposure estimates, however, were similar among geographic linkage methods. NHIS-EPAAnnualAir data files for 1985 through 2005 are currently available to users in the NCHS Research Data Center.

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.

Empirical Bayes Gaussian likelihood estimation of exposure distributions from pooled samples in human biomonitoring.

PubMed

Li, Xiang; Kuk, Anthony Y C; Xu, Jinfeng

2014-12-10

Human biomonitoring of exposure to environmental chemicals is important. Individual monitoring is not viable because of low individual exposure level or insufficient volume of materials and the prohibitive cost of taking measurements from many subjects. Pooling of samples is an efficient and cost-effective way to collect data. Estimation is, however, complicated as individual values within each pool are not observed but are only known up to their average or weighted average. The distribution of such averages is intractable when the individual measurements are lognormally distributed, which is a common assumption. We propose to replace the intractable distribution of the pool averages by a Gaussian likelihood to obtain parameter estimates. If the pool size is large, this method produces statistically efficient estimates, but regardless of pool size, the method yields consistent estimates as the number of pools increases. An empirical Bayes (EB) Gaussian likelihood approach, as well as its Bayesian analog, is developed to pool information from various demographic groups by using a mixed-effect formulation. We also discuss methods to estimate the underlying mean-variance relationship and to select a good model for the means, which can be incorporated into the proposed EB or Bayes framework. By borrowing strength across groups, the EB estimator is more efficient than the individual group-specific estimator. Simulation results show that the EB Gaussian likelihood estimates outperform a previous method proposed for the National Health and Nutrition Examination Surveys with much smaller bias and better coverage in interval estimation, especially after correction of bias. Copyright © 2014 John Wiley & Sons, Ltd.

Using speeding detections and numbers of fatalities to estimate relative risk of a fatality for motorcyclists and car drivers.

PubMed

Huggins, Richard

2013-10-01

Precise estimation of the relative risk of motorcyclists being involved in a fatal accident compared to car drivers is difficult. Simple estimates based on the proportions of licenced drivers or riders that are killed in a fatal accident are biased as they do not take into account the exposure to risk. However, exposure is difficult to quantify. Here we adapt the ideas behind the well known induced exposure methods and use available summary data on speeding detections and fatalities for motorcycle riders and car drivers to estimate the relative risk of a fatality for motorcyclists compared to car drivers under mild assumptions. The method is applied to data on motorcycle riders and car drivers in Victoria, Australia in 2010 and a small simulation study is conducted. Copyright © 2013 Elsevier Ltd. All rights reserved.

Short daily exposure to hand-arm vibrations in Swedish car mechanics.

PubMed

Barregård, Lars

2003-01-01

The aim of the study was to examine the daily exposure times to hand-arm vibrations in Swedish car mechanics, to test a method for estimating the exposure time without observing the workers for whole days, and to use the results for predicting the prevalence of vibration-induced white fingers (VWF) by the ISO 5349-model. Six garages were surveyed. In each garage, 5-10 car mechanics were observed in random order every 30 seconds throughout working days. The daily exposure time for each mechanic was estimated from the fraction of the observations that the mechanic was exposed. A total of 51 mechanics were observed, most of them on two different working days, yielding estimates for 95 days. The median effective exposure time was 10 minutes per day (95% confidence interval 5-15 minutes, arithmetic mean 14 minutes, maximum 80 minutes), and most of the exposure time was attributable to fastening and loosening nuts. The within-worker and between-worker variability was high (total sigma2 0.99, geometric standard deviation of 2.7). Using the observed exposure time and data on vibration levels of the main tools in Swedish car mechanics (average weighted acceleration level of 3.5 m/s2), the model in ISO-standard 5349 would predict that only three percent of the car mechanics will suffer from VWF after 20 years of exposure. In contrast, a recent survey of VWF showed the prevalence to be 25 percent. The precision of the observation method was estimated and was found to be good for the group daily mean. On the individual level the precision was only acceptable if the daily exposure time was > or = 40 minutes. In conclusion, the daily exposure time was short and the vibration level was limited. Nevertheless, hand-arm vibrations cause VWF in a significant number of car mechanics. The method of observing workers intermittently seemed to work well.

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions

PubMed Central

Gan, Ryan W.; Ford, Bonne; Lassman, William; Pfister, Gabriele; Vaidyanathan, Ambarish; Fischer, Emily; Volckens, John; Pierce, Jeffrey R.; Magzamen, Sheryl

2017-01-01

Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM2.5) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM2.5. A 10 μg/m3 increase in GWR smoke PM2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019–1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM2.5 exposure method: a 10 μg/m3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026–1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931–1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study. PMID:28868515

Evaluation of an exposure assessment used in epidemiological studies of diesel exhaust and lung cancer in underground mines

PubMed Central

Crump, Kenny; Van Landingham, Cynthia

2012-01-01

NIOSH/NCI (National Institute of Occupational Safety and Health and National Cancer Institute) developed exposure estimates for respirable elemental carbon (REC) as a surrogate for exposure to diesel exhaust (DE) for different jobs in eight underground mines by year beginning in the 1940s—1960s when diesel equipment was first introduced into these mines. These estimates played a key role in subsequent epidemiological analyses of the potential relationship between exposure to DE and lung cancer conducted in these mines. We report here on a reanalysis of some of the data from this exposure assessment. Because samples of REC were limited primarily to 1998–2001, NIOSH/NCI used carbon monoxide (CO) as a surrogate for REC. In addition, because CO samples were limited, particularly in the earlier years, they used the ratio of diesel horsepower (HP) to the mine air exhaust rate as a surrogate for CO. There are considerable uncertainties connected with each of these surrogate-based steps. The estimates of HP appear to involve considerable uncertainty, although we had no data upon which to evaluate the magnitude of this uncertainty. A sizable percentage (45%) of the CO samples used in the HP to CO model was below the detection limit which required NIOSH/NCI to assign CO values to these samples. In their preferred REC estimates, NIOSH/NCI assumed a linear relation between C0 and REC, although they provided no credible support for that assumption. Their assumption of a stable relationship between HP and CO also is questionable, and our reanalysis found a statistically significant relationship in only one-half of the mines. We re-estimated yearly REC exposures mainly using NIOSH/NCI methods but with some important differences: (i) rather than simply assuming a linear relationship, we used data from the mines to estimate the CO—REC relationship; (ii) we used a different method for assigning values to nondetect CO measurements; and (iii) we took account of statistical uncertainty to estimate bounds for REC exposures. This exercise yielded significantly different exposure estimates than estimated by NIOSH/NCI. However, this analysis did not incorporate the full range of uncertainty in REC exposures because of additional uncertainties in the assumptions underlying the modeling and in the underlying data (e.g. HP and mine exhaust rates). Estimating historical exposures in a cohort is generally a very difficult undertaking. However, this should not prevent one from recognizing the uncertainty in the resulting estimates in any use made of them. PMID:22594934

Reconstruction and analysis of 137Cs fallout deposition patterns in the Marshall Islands.

PubMed

Whitcomb, Robert C

2002-03-01

Estimates of 137Cs deposition caused by fallout originating from nuclear weapons testing in the Marshall Islands have been estimated for several locations in the Marshall Islands. These retrospective estimates are based primarily on historical exposure rate and gummed film measurements. The methods used to reconstruct these deposition estimates are similar to those used in the National Cancer Institute study for reconstructing 131I deposition from the Nevada Test Site. Reconstructed cumulative deposition estimates are validated against contemporary measurements of 137Cs concentration in soil with account taken for estimated global fallout contributions. These validations show that the overall geometric bias in predicted-to-observed (P:O) ratios is 1.0 (indicating excellent agreement). The 5th to 95th percentile range of this distribution is 0.35-2.95. The P:O ratios for estimates using historical gummed film measurements tend to slightly overpredict more than estimates using exposure rate measurements. The deposition estimate methods, supported by the agreement between estimates and measurements, suggest that these methods can be used with confidence for other weapons testing fallout radionuclides.

A measurement and modeling study of temperature in living and fixed tissue during and after radiofrequency exposure.

PubMed

Bermingham, Jacqueline F; Chen, Yuen Y; McIntosh, Robert L; Wood, Andrew W

2014-04-01

Fluorescent intensity of the dye Rhodamine-B (Rho-B) decreases with increasing temperature. We show that in fresh rat brain tissue samples in a custom-made radiofrequency (RF) tissue exposure device, temperature rise due to RF radiation as measured by absorbed dye correlates well with temperature measured nearby by fiber optic probes. Estimates of rate of initial temperature rise (using both probe measurement and the dye method) accord well with estimates of local specific energy absorption rate (SAR). We also modeled the temperature characteristics of the exposure device using combined electromagnetic and finite-difference thermal modeling. Although there are some differences in the rate of cooling following cessation of RF exposure, there is reasonable agreement between modeling and both probe measurement and dye estimation of temperature. The dye method also permits measurement of regional temperature rise (due to RF). There is no clear evidence of local differential RF absorption, but further refinement of the method may be needed to fully clarify this issue. © 2014 Wiley Periodicals, Inc.

Mediation of the Relationship between Maternal Phthalate Exposure and Preterm Birth by Oxidative Stress with Repeated Measurements across Pregnancy.

PubMed

Ferguson, Kelly K; Chen, Yin-Hsiu; VanderWeele, Tyler J; McElrath, Thomas F; Meeker, John D; Mukherjee, Bhramar

2017-03-01

Mediation analysis is useful for understanding mechanisms and has been used minimally in the study of the environment and disease. We examined mediation of the association between phthalate exposure during pregnancy and preterm birth by oxidative stress. This nested case-control study of preterm birth ( n = 130 cases, 352 controls) included women who delivered in Boston, Massachusestts, from 2006 through 2008. Phthalate metabolites and 8-isoprostane, an oxidative stress biomarker, were measured in urine from three visits in pregnancy. We applied four counterfactual mediation methods: method 1, utilizing exposure and mediator averages; method 2, using averages but allowing for an exposure-mediator interaction; method 3, incorporating longitudinal measurements of the exposure and mediator; and method 4, using longitudinal measurements and allowing for an exposure-mediator interaction. We observed mediation of the associations between phthalate metabolites and all preterm birth by 8-isoprostane, with the greatest estimated proportion mediated observed for spontaneous preterm births specifically. Fully utilizing repeated measures of the exposure and mediator improved precision of indirect (i.e., mediated) effect estimates, and including an exposure-mediator interaction increased the estimated proportion mediated. For example, for mono(2-ethyl-carboxy-propyl) phthalate (MECPP), a metabolite of di(2-ethylhexyl) phthalate (DEHP), the percent of the total effect mediated by 8-isoprostane increased from 47% to 60% with inclusion of an exposure-mediator interaction term, in reference to a total adjusted odds ratio of 1.67 or 1.48, respectively. This demonstrates mediation of the phthalate-preterm birth relationship by oxidative stress, and the utility of complex regression models in capturing mediated associations when repeated measures of exposure and mediator are available and an exposure-mediator interaction may exist. Citation: Ferguson KK, Chen YH, VanderWeele TJ, McElrath TF, Meeker JD, Mukherjee B. 2017. Mediation of the relationship between maternal phthalate exposure and preterm birth by oxidative stress with repeated measurements across pregnancy. Environ Health Perspect 125:488-494; http://dx.doi.org/10.1289/EHP282.

CHARACTERIZATION OF RESIDENTIAL EXPOSURE TO CHLORPYRIFOS AND DIAZINON

EPA Science Inventory

Exposures to chlorpyrifos and diazinon in residential microenvironment in AZ were estimated using the indirect method of exposure calculation by combining measured concentrations in multiple media with time subjects spent indoors, dietary and non-dietary items they consumed, an...

Projected 1981 exposure estimates using iterative proportional fitting

DOT National Transportation Integrated Search

1985-10-01

1981 VMT estimates categorized by eight driver, vehicle, and environmental : variables are produced. These 1981 estimates are produced using analytical : methods developed in a previous report. The estimates are based on 1977 : NPTS data (the latest ...

Assessment of the point-source method for estimating dose rates to members of the public from exposure to patients with 131I thyroid treatment

DOE PAGES

Dewji, Shaheen Azim; Bellamy, Michael B.; Hertel, Nolan E.; ...

2015-09-01

The U.S. Nuclear Regulatory Commission (USNRC) initiated a contract with Oak Ridge National Laboratory (ORNL) to calculate radiation dose rates to members of the public that may result from exposure to patients recently administered iodine-131 ( 131I) as part of medical therapy. The main purpose was to compare dose rate estimates based on a point source and target with values derived from more realistic simulations that considered the time-dependent distribution of 131I in the patient and attenuation of emitted photons by the patient’s tissues. The external dose rate estimates were derived using Monte Carlo methods and two representations of themore » Phantom with Movable Arms and Legs, previously developed by ORNL and the USNRC, to model the patient and a nearby member of the public. Dose rates to tissues and effective dose rates were calculated for distances ranging from 10 to 300 cm between the phantoms and compared to estimates based on the point-source method, as well as to results of previous studies that estimated exposure from 131I patients. The point-source method overestimates dose rates to members of the public in very close proximity to an 131I patient but is a broadly accurate method of dose rate estimation at separation distances of 300 cm or more at times closer to administration.« less

ESTIMATION OF EXPOSURE CRITERIA VALUES FOR BILIARY POLYCYCLIC AROMATIC HYDROCARBON METABOLITE CONCENTRATIONS IN WHITE SUCKERS (CATOSTOMUS COMMERSONI)

EPA Science Inventory

A methodology was developed for deriving quantitative exposure criteria useful for comparing a site or a watershed to a reference condition and for defining the occurrence of extreme exposures. The prototype method used indicators of exposures to oil contamination and combustion ...

ESTIMATION OF EXPOSURE CRITERIA VALUES FOR BILIARY POLYCYCLIC AROMATIC HYDROCARBON METABOLITE CONCENTRATION IN WHITE SUCKERS (CATASTOMUS COMMERSONI)

EPA Science Inventory

A methodology was developed for deriving quantitative exposure criteria useful for comparing a site or a watershed to a reference condition and for defining the occurrence of extreme exposures. The prototype method used indicators of exposures to oil contamination and combustion ...

Quantifying Risk Over the Life Course – Latency, Age-Related Susceptibility, and Other Time-Varying Exposure Metrics

PubMed Central

Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna

2016-01-01

Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses’ Health Study. PMID:26750582

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 ...

Seasonal Effect on Ocular Sun Exposure and Conjunctival UV Autofluorescence

PubMed Central

Haworth, Kristina M.; Chandler, Heather L.

2016-01-01

Purpose To evaluate feasibility and repeatability of measures for ocular sun exposure and conjunctival ultraviolet autofluorescence (UVAF), and to test for relationships between the outcomes. Methods Fifty volunteers were seen for 2 visits 14±2 days apart. Ocular sun exposure was estimated over a two-week time period using questionnaires that quantified time outdoors and ocular protection habits. Conjunctival UVAF was imaged using a Nikon D7000 camera system equipped with appropriate flash and filter system; image analysis was done using ImageJ software. Repeatability estimates were made using Bland-Altman plots with mean differences and 95% limits of agreement calculated. Non-normally distributed data was transformed by either log10 or square root methods. Linear regression was conducted to evaluate relationships between measures. Results Mean (±SD) values for ocular sun exposure and conjunctival UVAF were 8.86 (±11.97) hours and 9.15 (±9.47) mm2, respectively. Repeatability was found to be acceptable for both ocular sun exposure and conjunctival UVAF. Univariate linear regression showed outdoor occupation to be a predictor of higher ocular sun exposure; outdoor occupation and winter season of collection both predicted higher total UVAF. Furthermore, increased portion of day spent outdoors while working was associated with increased total conjunctival UVAF. Conclusions We demonstrate feasibility and repeatability of estimating ocular sun exposure using a previously unreported method and for conjunctival UVAF in a group of subjects residing in Ohio. Seasonal temperature variation may have influenced time outdoors and ultimately calculation of ocular sun exposure. As winter season of collection and outdoor occupation both predicted higher total UVAF, our data suggests that ocular sun exposure is associated with conjunctival UVAF and possibly, that UVAF remains for at least several months following sun exposure. PMID:27820717

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

The future excess fraction of occupational cancer among those exposed to carcinogens at work in Australia in 2012.

PubMed

Carey, Renee N; Hutchings, Sally J; Rushton, Lesley; Driscoll, Timothy R; Reid, Alison; Glass, Deborah C; Darcey, Ellie; Si, Si; Peters, Susan; Benke, Geza; Fritschi, Lin

2017-04-01

Studies in other countries have generally found approximately 4% of current cancers to be attributable to past occupational exposures. This study aimed to estimate the future burden of cancer resulting from current occupational exposures in Australia. The future excess fraction method was used to estimate the future burden of occupational cancer (2012-2094) among the proportion of the Australian working population who were exposed to occupational carcinogens in 2012. Calculations were conducted for 19 cancer types and 53 cancer-exposure pairings, assuming historical trends and current patterns continued to 2094. The cohort of 14.6 million Australians of working age in 2012 will develop an estimated 4.8 million cancers during their lifetime, of which 68,500 (1.4%) are attributable to occupational exposure in those exposed in 2012. The majority of these will be lung cancers (n=26,000), leukaemias (n=8000), and malignant mesotheliomas (n=7500). A significant proportion of future cancers will result from occupational exposures. This estimate is lower than previous estimates in the literature; however, our estimate is not directly comparable to past estimates of the occupational cancer burden because they describe different quantities - future cancers in currently exposed versus current cancers due to past exposures. The results of this study allow us to determine which current occupational exposures are most important, and where to target exposure prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimated long-term outdoor air pollution concentrations in a cohort study

NASA Astrophysics Data System (ADS)

Beelen, Rob; Hoek, Gerard; Fischer, Paul; Brandt, Piet A. van den; Brunekreef, Bert

Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO 2), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO 2) was estimated. Exposure at each home address ( N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO 2, NO, BS, and SO 2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO 2, NO, BS and SO 2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.

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.

A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.

PubMed

Takeuchi, Yoshinori; Shinozaki, Tomohiro; Matsuyama, Yutaka

2018-01-08

Despite the frequent use of self-controlled methods in pharmacoepidemiological studies, the factors that may bias the estimates from these methods have not been adequately compared in real-world settings. Here, we comparatively examined the impact of a time-varying confounder and its interactions with time-invariant confounders, time trends in exposures and events, restrictions, and misspecification of risk period durations on the estimators from three self-controlled methods. This study analyzed self-controlled case series (SCCS), case-crossover (CCO) design, and sequence symmetry analysis (SSA) using simulated and actual electronic medical records datasets. We evaluated the performance of the three self-controlled methods in simulated cohorts for the following scenarios: 1) time-invariant confounding with interactions between the confounders, 2) time-invariant and time-varying confounding without interactions, 3) time-invariant and time-varying confounding with interactions among the confounders, 4) time trends in exposures and events, 5) restricted follow-up time based on event occurrence, and 6) patient restriction based on event history. The sensitivity of the estimators to misspecified risk period durations was also evaluated. As a case study, we applied these methods to evaluate the risk of macrolides on liver injury using electronic medical records. In the simulation analysis, time-varying confounding produced bias in the SCCS and CCO design estimates, which aggravated in the presence of interactions between the time-invariant and time-varying confounders. The SCCS estimates were biased by time trends in both exposures and events. Erroneously short risk periods introduced bias to the CCO design estimate, whereas erroneously long risk periods introduced bias to the estimates of all three methods. Restricting the follow-up time led to severe bias in the SSA estimates. The SCCS estimates were sensitive to patient restriction. The case study showed that although macrolide use was significantly associated with increased liver injury occurrence in all methods, the value of the estimates varied. The estimations of the three self-controlled methods depended on various underlying assumptions, and the violation of these assumptions may cause non-negligible bias in the resulting estimates. Pharmacoepidemiologists should select the appropriate self-controlled method based on how well the relevant key assumptions are satisfied with respect to the available data.

Estimating Pesticide Exposure from Dietary Intake and Organic Food Choices: The Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Beresford, Shirley A.A.; Fenske, Richard A.; Fitzpatrick, Annette L.; Lu, Chensheng; Nettleton, Jennifer A.; Kaufman, Joel D.

2015-01-01

Background Organophosphate pesticide (OP) exposure to the U.S. population is dominated by dietary intake. The magnitude of exposure from diet depends partly on personal decisions such as which foods to eat and whether to choose organic food. Most studies of OP exposure rely on urinary biomarkers, which are limited by short half-lives and often lack specificity to parent compounds. A reliable means of estimating long-term dietary exposure to individual OPs is needed to assess the potential relationship with adverse health effects. Objectives We assessed long-term dietary exposure to 14 OPs among 4,466 participants in the Multi-Ethnic Study of Atherosclerosis, and examined the influence of organic produce consumption on this exposure. Methods Individual-level exposure was estimated by combining information on typical intake of specific food items with average OP residue levels on those items. In an analysis restricted to a subset of participants who reported rarely or never eating organic produce (“conventional consumers”), we assessed urinary dialkylphosphate (DAP) levels across tertiles of estimated exposure (n = 480). In a second analysis, we compared DAP levels across subgroups with differing self-reported organic produce consumption habits (n = 240). Results Among conventional consumers, increasing tertile of estimated dietary OP exposure was associated with higher DAP concentrations (p < 0.05). DAP concentrations were also significantly lower in groups reporting more frequent consumption of organic produce (p < 0.02). Conclusions Long-term dietary exposure to OPs was estimated from dietary intake data, and estimates were consistent with DAP measurements. More frequent consumption of organic produce was associated with lower DAPs. Citation Curl CL, Beresford SA, Fenske RA, Fitzpatrick AL, Lu C, Nettleton JA, Kaufman JD. 2015. Estimating pesticide exposure from dietary intake and organic food choices: the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 123:475–483; http://dx.doi.org/10.1289/ehp.1408197 PMID:25650532

EXPOSURES AND INTERNAL DOSES OF ...

EPA Pesticide Factsheets

The National Center for Environmental Assessment (NCEA) has released a final report that presents and applies a method to estimate distributions of internal concentrations of trihalomethanes (THMs) in humans resulting from a residential drinking water exposure. The report presents simulations of oral, dermal and inhalation exposures and demonstrates the feasibility of linking the US EPA’s information Collection Rule database with other databases on external exposure factors and physiologically based pharmacokinetic modeling to refine population-based estimates of exposure. Review Draft - by 2010, develop scientifically sound data and approaches to assess and manage risks to human health posed by exposure to specific regulated waterborne pathogens and chemicals, including those addressed by the Arsenic, M/DBP and Six-Year Review Rules.

Towards Personal Exposures: How Technology Is Changing Air Pollution and Health Research.

PubMed

Larkin, A; Hystad, P

2017-12-01

We present a review of emerging technologies and how these can transform personal air pollution exposure assessment and subsequent health research. Estimating personal air pollution exposures is currently split broadly into methods for modeling exposures for large populations versus measuring exposures for small populations. Air pollution sensors, smartphones, and air pollution models capitalizing on big/new data sources offer tremendous opportunity for unifying these approaches and improving long-term personal exposure prediction at scales needed for population-based research. A multi-disciplinary approach is needed to combine these technologies to not only estimate personal exposures for epidemiological research but also determine drivers of these exposures and new prevention opportunities. While available technologies can revolutionize air pollution exposure research, ethical, privacy, logistical, and data science challenges must be met before widespread implementations occur. Available technologies and related advances in data science can improve long-term personal air pollution exposure estimates at scales needed for population-based research. This will advance our ability to evaluate the impacts of air pollution on human health and develop effective prevention strategies.

Comparison of Methods for Analyzing Left-Censored Occupational Exposure Data

PubMed Central

Huynh, Tran; Ramachandran, Gurumurthy; Banerjee, Sudipto; Monteiro, Joao; Stenzel, Mark; Sandler, Dale P.; Engel, Lawrence S.; Kwok, Richard K.; Blair, Aaron; Stewart, Patricia A.

2014-01-01

The National Institute for Environmental Health Sciences (NIEHS) is conducting an epidemiologic study (GuLF STUDY) to investigate the health of the workers and volunteers who participated from April to December of 2010 in the response and cleanup of the oil release after the Deepwater Horizon explosion in the Gulf of Mexico. The exposure assessment component of the study involves analyzing thousands of personal monitoring measurements that were collected during this effort. A substantial portion of these data has values reported by the analytic laboratories to be below the limits of detection (LOD). A simulation study was conducted to evaluate three established methods for analyzing data with censored observations to estimate the arithmetic mean (AM), geometric mean (GM), geometric standard deviation (GSD), and the 95th percentile (X0.95) of the exposure distribution: the maximum likelihood (ML) estimation, the β-substitution, and the Kaplan–Meier (K-M) methods. Each method was challenged with computer-generated exposure datasets drawn from lognormal and mixed lognormal distributions with sample sizes (N) varying from 5 to 100, GSDs ranging from 2 to 5, and censoring levels ranging from 10 to 90%, with single and multiple LODs. Using relative bias and relative root mean squared error (rMSE) as the evaluation metrics, the β-substitution method generally performed as well or better than the ML and K-M methods in most simulated lognormal and mixed lognormal distribution conditions. The ML method was suitable for large sample sizes (N ≥ 30) up to 80% censoring for lognormal distributions with small variability (GSD = 2–3). The K-M method generally provided accurate estimates of the AM when the censoring was <50% for lognormal and mixed distributions. The accuracy and precision of all methods decreased under high variability (GSD = 4 and 5) and small to moderate sample sizes (N < 20) but the β-substitution was still the best of the three methods. When using the ML method, practitioners are cautioned to be aware of different ways of estimating the AM as they could lead to biased interpretation. A limitation of the β-substitution method is the absence of a confidence interval for the estimate. More research is needed to develop methods that could improve the estimation accuracy for small sample sizes and high percent censored data and also provide uncertainty intervals. PMID:25261453

Developing and Evaluating New Methods for Assessing Concurrent Environmental Exposures

EPA Science Inventory

Summary of purpose and scope (no longer than 200 words): One limitation to current environmental health research is the focus on single contaminant exposures. Each exposure estimated in epidemiologic models accounts for a relatively small proportion of observed variance in health...

Burden of disease from inadequate water, sanitation and hygiene in low- and middle-income settings: a retrospective analysis of data from 145 countries

PubMed Central

Prüss-Ustün, Annette; Bartram, Jamie; Clasen, Thomas; Colford, John M; Cumming, Oliver; Curtis, Valerie; Bonjour, Sophie; Dangour, Alan D; De France, Jennifer; Fewtrell, Lorna; Freeman, Matthew C; Gordon, Bruce; Hunter, Paul R; Johnston, Richard B; Mathers, Colin; Mäusezahl, Daniel; Medlicott, Kate; Neira, Maria; Stocks, Meredith; Wolf, Jennyfer; Cairncross, Sandy

2014-01-01

Objective To estimate the burden of diarrhoeal diseases from exposure to inadequate water, sanitation and hand hygiene in low- and middle-income settings and provide an overview of the impact on other diseases. Methods For estimating the impact of water, sanitation and hygiene on diarrhoea, we selected exposure levels with both sufficient global exposure data and a matching exposure-risk relationship. Global exposure data were estimated for the year 2012, and risk estimates were taken from the most recent systematic analyses. We estimated attributable deaths and disability-adjusted life years (DALYs) by country, age and sex for inadequate water, sanitation and hand hygiene separately, and as a cluster of risk factors. Uncertainty estimates were computed on the basis of uncertainty surrounding exposure estimates and relative risks. Results In 2012, 502 000 diarrhoea deaths were estimated to be caused by inadequate drinking water and 280 000 deaths by inadequate sanitation. The most likely estimate of disease burden from inadequate hand hygiene amounts to 297 000 deaths. In total, 842 000 diarrhoea deaths are estimated to be caused by this cluster of risk factors, which amounts to 1.5% of the total disease burden and 58% of diarrhoeal diseases. In children under 5 years old, 361 000 deaths could be prevented, representing 5.5% of deaths in that age group. Conclusions This estimate confirms the importance of improving water and sanitation in low- and middle-income settings for the prevention of diarrhoeal disease burden. It also underscores the need for better data on exposure and risk reductions that can be achieved with provision of reliable piped water, community sewage with treatment and hand hygiene. PMID:24779548

Reconstruction and analysis of cesium-137 fallout deposition patterns in the Marshall Islands

NASA Astrophysics Data System (ADS)

Whitcomb, Robert Cleckley, Jr.

Estimates of 137Cs deposition due to fallout originating from nuclear weapons testing in the Marshall Islands have been made for several locations in the Marshall Islands. These retrospective estimates were based primarily on historical exposure rate and gummed film measurements. The methods used to reconstruct these deposition estimates are specific for six of the Pacific tests. These methods are also similar to those used in the National Cancer Institute study for reconstructing 131I deposition from the Nevada Test Site. Reconstructed cumulative deposition estimates are validated against contemporary measurements of 137Cs concentration in soil. This validation work also includes an accounting for estimated global fallout contributions. These validations show that the overall geometric bias in predicted-to-observed (P/O) ratios is 1.0 (indicating excellent agreement). The 5th and 95th percentile range of this distribution is 0.35--2.95. The P/O ratios for estimates using historical gummed film measurements tend to slightly over-predict more than estimates using exposure rate measurements. The methods produce reasonable estimates of deposition confirming that radioactive fallout occurred at atolls further south of the four northern atolls recognized by the Department of Energy as being affected by fallout. The deposition estimate methods, supported by the very good agreement between estimates and measurements, suggest that these methods can be used for other weapons testing fallout radionuclides with confidence.

Low-cost extrapolation method for maximal LTE radio base station exposure estimation: test and validation.

PubMed

Verloock, Leen; Joseph, Wout; Gati, Azeddine; Varsier, Nadège; Flach, Björn; Wiart, Joe; Martens, Luc

2013-06-01

An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on downlink band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2×2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders.

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities

PubMed Central

Helb, Danica A.; Tetteh, Kevin K. A.; Felgner, Philip L.; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R.; Beeson, James G.; Tappero, Jordan; Smith, David L.; Crompton, Peter D.; Rosenthal, Philip J.; Dorsey, Grant; Drakeley, Christopher J.; Greenhouse, Bryan

2015-01-01

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual’s recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86–0.93), whereas responses to six antigens accurately estimated an individual’s malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs. PMID:26216993

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities.

PubMed

Helb, Danica A; Tetteh, Kevin K A; Felgner, Philip L; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R; Beeson, James G; Tappero, Jordan; Smith, David L; Crompton, Peter D; Rosenthal, Philip J; Dorsey, Grant; Drakeley, Christopher J; Greenhouse, Bryan

2015-08-11

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual's recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86-0.93), whereas responses to six antigens accurately estimated an individual's malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs.

SU-F-P-19: Fetal Dose Estimate for a High-Dose Fluoroscopy Guided Intervention Using Modern Data Tools

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

Moirano, J

Purpose: An accurate dose estimate is necessary for effective patient management after a fetal exposure. In the case of a high-dose exposure, it is critical to use all resources available in order to make the most accurate assessment of the fetal dose. This work will demonstrate a methodology for accurate fetal dose estimation using tools that have recently become available in many clinics, and show examples of best practices for collecting data and performing the fetal dose calculation. Methods: A fetal dose estimate calculation was performed using modern data collection tools to determine parameters for the calculation. The reference pointmore » air kerma as displayed by the fluoroscopic system was checked for accuracy. A cumulative dose incidence map and DICOM header mining were used to determine the displayed reference point air kerma. Corrections for attenuation caused by the patient table and pad were measured and applied in order to determine the peak skin dose. The position and depth of the fetus was determined by ultrasound imaging and consultation with a radiologist. The data collected was used to determine a normalized uterus dose from Monte Carlo simulation data. Fetal dose values from this process were compared to other accepted calculation methods. Results: An accurate high-dose fetal dose estimate was made. Comparison to accepted legacy methods were were within 35% of estimated values. Conclusion: Modern data collection and reporting methods ease the process for estimation of fetal dose from interventional fluoroscopy exposures. Many aspects of the calculation can now be quantified rather than estimated, which should allow for a more accurate estimation of fetal dose.« less

Combining statistics from two national complex surveys to estimate injury rates per hour exposed and variance by activity in the USA.

PubMed

Lin, Tin-Chi; Marucci-Wellman, Helen R; Willetts, Joanna L; Brennan, Melanye J; Verma, Santosh K

2016-12-01

A common issue in descriptive injury epidemiology is that in order to calculate injury rates that account for the time spent in an activity, both injury cases and exposure time of specific activities need to be collected. In reality, few national surveys have this capacity. To address this issue, we combined statistics from two different national complex surveys as inputs for the numerator and denominator to estimate injury rate, accounting for the time spent in specific activities and included a procedure to estimate variance using the combined surveys. The 2010 National Health Interview Survey (NHIS) was used to quantify injuries, and the 2010 American Time Use Survey (ATUS) was used to quantify time of exposure to specific activities. The injury rate was estimated by dividing the average number of injuries (from NHIS) by average exposure hours (from ATUS), both measured for specific activities. The variance was calculated using the 'delta method', a general method for variance estimation with complex surveys. Among the five types of injuries examined, 'sport and exercise' had the highest rate (12.64 injuries per 100 000 h), followed by 'working around house/yard' (6.14), driving/riding a motor vehicle (2.98), working (1.45) and sleeping/resting/eating/drinking (0.23). The results show a ranking of injury rate by activity quite different from estimates using population as the denominator. Our approach produces an estimate of injury risk which includes activity exposure time and may more reliably reflect the underlying injury risks, offering an alternative method for injury surveillance and research. 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/.

Determining paediatric patient thickness from a single digital radiograph-a proof of principle.

PubMed

Worrall, Mark; Vinnicombe, Sarah; Sutton, David G

2018-04-05

This work presents a proof of principle for a method of estimating the thickness of an attenuator from a single radiograph using the image, the exposure factors with which it was acquired and a priori knowledge of the characteristics of the X-ray unit and detector used for the exposure. It is intended this could be developed into a clinical tool to assist with paediatric patient dose audit, for which a measurement of patient size is required. The proof of principle used measured pixel value and effective linear attenuation coefficient to estimate the thickness of a Solid Water attenuator. The kerma at the detector was estimated using a measurement of pixel value on the image and measured detector calibrations. The initial kerma was estimated using a lookup table of measured output values. The effective linear attenuation coefficient was measured for Solid Water at varying kV p . 11 test images of known and varying thicknesses of Solid Water were acquired at 60, 70 and 81 kV p . Estimates of attenuator thickness were made using the model and the results compared to the known thickness. Estimates of attenuator thickness made using the model differed from the known thickness by 3.8 mm (3.2%) on average, with a range of 0.5-10.8 mm (0.5-9%). A proof of principle is presented for a method of estimating the thickness of an attenuator using a single radiograph of the attenuator. The method has been shown to be accurate using a Solid Water attenuator, with a maximum difference between estimated and known attenuator thickness of 10.8 mm (9%). The method shows promise as a clinical tool for estimating abdominal paediatric patient thickness for paediatric patient dose audit, and is only contingent on the type of data routinely collected by Medical Physics departments. Advances in knowledge: A computational model has been created that is capable of accurately estimating the thickness of a uniform attenuator using only the radiographic image, the exposure factors with which it was acquired and a priori knowledge of the characteristics of the X-ray unit and detector used for the exposure.

Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

PubMed Central

Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

2015-01-01

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job’s estimate and the mean estimate for all jobs within the cluster. Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. PMID:25477475

Comparison of nickel release in solutions used for the identification of water-soluble nickel exposures and in synthetic lung fluids.

PubMed

Oller, Adriana R; Cappellini, Danielle; Henderson, Rayetta G; Bates, Hudson K

2009-04-01

Chemical speciation of workplace nickel exposures is critical because nickel-containing substances often differ in toxicological properties. Exposure matrices based on leaching methods have been used to ascertain which chemical forms of nickel are primarily associated with adverse respiratory effects after inhalation. Misjudgments in the relative proportion of each of the main fractions of nickel in workplace exposures could translate into possible misattributions of risk to the various forms of nickel. This preliminary study looked at the efficiency of the first step of the Zatka leaching method for accurately assessing the 'water-soluble' fraction of several substances present in nickel production operations, compared to leaching in synthetic lung fluid. The present results demonstrate that for nickel sulfate or chloride, the current Zatka solution is adequate to assess the 'water-soluble' fraction. However, when sparingly water-soluble compounds like nickel carbonates or water-insoluble substances like nickel subsulfide and fine metallic nickel powders are present, the first step of the Zatka method can greatly over estimate the amount of nickel that could be released in pure water. In contrast, the releases of nickel from nickel carbonate, nickel subsulfide, and nickel metal powders in pure water are consistent with their releases in synthetic lung fluid, indicating that deionized water is a better leaching solution to estimate the biologically relevant 'water-soluble' nickel fraction of workplace exposures. Exposure matrices relying mostly on the Zatka speciation method to estimate the main forms of nickel need to be re-evaluated to account for any possible misattributions of risk.

Quantifying Cancer Risk from Radiation.

PubMed

Keil, Alexander P; Richardson, David B

2017-12-06

Complex statistical models fitted to data from studies of atomic bomb survivors are used to estimate the human health effects of ionizing radiation exposures. We describe and illustrate an approach to estimate population risks from ionizing radiation exposure that relaxes many assumptions about radiation-related mortality. The approach draws on developments in methods for causal inference. The results offer a different way to quantify radiation's effects and show that conventional estimates of the population burden of excess cancer at high radiation doses are driven strongly by projecting outside the range of current data. Summary results obtained using the proposed approach are similar in magnitude to those obtained using conventional methods, although estimates of radiation-related excess cancers differ for many age, sex, and dose groups. At low doses relevant to typical exposures, the strength of evidence in data is surprisingly weak. Statements regarding human health effects at low doses rely strongly on the use of modeling assumptions. © 2017 Society for Risk Analysis.

Application of geostatistics to risk assessment.

PubMed

Thayer, William C; Griffith, Daniel A; Goodrum, Philip E; Diamond, Gary L; Hassett, James M

2003-10-01

Geostatistics offers two fundamental contributions to environmental contaminant exposure assessment: (1) a group of methods to quantitatively describe the spatial distribution of a pollutant and (2) the ability to improve estimates of the exposure point concentration by exploiting the geospatial information present in the data. The second contribution is particularly valuable when exposure estimates must be derived from small data sets, which is often the case in environmental risk assessment. This article addresses two topics related to the use of geostatistics in human and ecological risk assessments performed at hazardous waste sites: (1) the importance of assessing model assumptions when using geostatistics and (2) the use of geostatistics to improve estimates of the exposure point concentration (EPC) in the limited data scenario. The latter topic is approached here by comparing design-based estimators that are familiar to environmental risk assessors (e.g., Land's method) with geostatistics, a model-based estimator. In this report, we summarize the basics of spatial weighting of sample data, kriging, and geostatistical simulation. We then explore the two topics identified above in a case study, using soil lead concentration data from a Superfund site (a skeet and trap range). We also describe several areas where research is needed to advance the use of geostatistics in environmental risk assessment.

The Aggregate Exposure Pathway (AEP): A conceptual framework for advancing exposure science research and applications

EPA Science Inventory

Historically, risk assessment has relied upon toxicological data to obtain hazard-based reference levels, which are subsequently compared to exposure estimates to determine whether an unacceptable risk to public health may exist. Recent advances in analytical methods, biomarker ...

Ecological risk assessment in a large river-reservoir. 5: Aerial insectivorous wildlife

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

Baron, L.A.; Sample, B.E.; Suter, G.W. II

Risks to aerial insectivores (e.g., rough-winged swallows, little brown bats, and endangered gray bats) were assessed for the remedial investigation of the Clinch River/Poplar Creek (CR/PC) system. Adult mayflies and sediment were collected from three locations and analyzed for contaminants. Sediment-to-mayfly contaminant uptake factors were generated from these data and used to estimate contaminant concentrations in mayflies from 13 additional locations. Contaminants of potential ecological concern (COPECs) were identified by comparing exposure estimates generated using point estimates of parameter values to NOAELs. To incorporate the variation in exposure parameters and to provide a better estimate of the potential exposure, themore » exposure model was recalculated using Monte Carlo methods. The potential for adverse effects was estimated based on the comparison of exposure distribution and the LOAEL. The results of this assessment suggested that population-level effects to rough-winged swallows and little brown bats are considered unlikely. However, because gray bats are endangered, effects on individuals may be significant from foraging in limited subreaches of the CR/PC system. This assessment illustrates the advantage of an iterative approach to ecological risk assessments, using fewer conservative assumptions and more realistic modeling of exposure.« less

Occupational cancer in Britain

PubMed Central

Van Tongeren, Martie; Jimenez, Araceli S; Hutchings, Sally J; MacCalman, Laura; Rushton, Lesley; Cherrie, John W

2012-01-01

To estimate the current occupational cancer burden due to past exposures in Britain, estimates of the number of exposed workers at different levels are required, as well as risk estimates of cancer due to the exposures. This paper describes the methods and results for estimating the historical exposures. All occupational carcinogens or exposure circumstances classified by the International Agency for Research on Cancer as definite or probable human carcinogens and potentially to be found in British workplaces over the past 20–40 years were included in this study. Estimates of the number of people exposed by industrial sector were based predominantly on two sources of data, the CARcinogen EXposure (CAREX) database and the UK Labour Force Survey. Where possible, multiple and overlapping exposures were taken into account. Dose–response risk estimates were generally not available in the epidemiological literature for the cancer–exposure pairs in this study, and none of the sources available for obtaining the numbers exposed provided data by different levels of exposure. Industrial sectors were therefore assigned using expert judgement to ‘higher'- and ‘lower'-exposure groups based on the similarity of exposure to the population in the key epidemiological studies from which risk estimates had been selected. Estimates of historical exposure prevalence were obtained for 41 carcinogens or occupational circumstances. These include exposures to chemicals and metals, combustion products, other mixtures or groups of chemicals, mineral and biological dusts, physical agents and work patterns, as well as occupations and industries that have been associated with increased risk of cancer, but for which the causative agents are unknown. There were more than half a million workers exposed to each of six carcinogens (radon, solar radiation, crystalline silica, mineral oils, non-arsenical insecticides and 2,3,7,8-tetrachlorodibenzo-p-dioxin); other agents to which a large number of workers are exposed included benzene, diesel engine exhaust and environmental tobacco smoke. The study has highlighted several industrial sectors with large proportions of workers potentially exposed to multiple carcinogens. The relevant available data have been used to generate estimates of the prevalence of past exposure to occupational carcinogens to enable the occupational cancer burden in Britain to be estimated. These data are considered adequate for the present purpose, but new data on the prevalence and intensity of current occupational exposure to carcinogens should be collected to ensure that future policy decisions be based on reliable evidence. PMID:22710674

Quantifying risk over the life course - latency, age-related susceptibility, and other time-varying exposure metrics.

PubMed

Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna

2016-06-15

Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional, and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses' Health Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Reducing random measurement error in assessing postural load on the back in epidemiologic surveys.

PubMed

Burdorf, A

1995-02-01

The goal of this study was to design strategies to assess postural load on the back in occupational epidemiology by taking into account the reliability of measurement methods and the variability of exposure among the workers under study. Intermethod reliability studies were evaluated to estimate the systematic bias (accuracy) and random measurement error (precision) of various methods to assess postural load on the back. Intramethod reliability studies were reviewed to estimate random variability of back load over time. Intermethod surveys have shown that questionnaires have a moderate reliability for gross activities such as sitting, whereas duration of trunk flexion and rotation should be assessed by observation methods or inclinometers. Intramethod surveys indicate that exposure variability can markedly affect the reliability of estimates of back load if the estimates are based upon a single measurement over a certain time period. Equations have been presented to evaluate various study designs according to the reliability of the measurement method, the optimum allocation of the number of repeated measurements per subject, and the number of subjects in the study. Prior to a large epidemiologic study, an exposure-oriented survey should be conducted to evaluate the performance of measurement instruments and to estimate sources of variability for back load. The strategy for assessing back load can be optimized by balancing the number of workers under study and the number of repeated measurements per worker.

Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method

PubMed Central

2014-01-01

Background Personal exposure studies of air pollution generally use self-reported diaries to capture individuals’ time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants’ locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies. Methods Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant’s position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods. Results There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest ‘good’ agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time “Indoors Other” using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time “In Transit” was relatively consistent between the methods, the mean daily exposure to PM2.5 while “In Transit” was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary. Conclusions Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution. PMID:24885722

Who, What, When, Where? Determining the Health Implications of Wildfire Smoke Exposure

NASA Astrophysics Data System (ADS)

Ford, B.; Lassman, W.; Gan, R.; Burke, M.; Pfister, G.; Magzamen, S.; Fischer, E. V.; Volckens, J.; Pierce, J. R.

2016-12-01

Exposure to poor air quality is associated with negative impacts on human health. A large natural source of PM in the western U.S. is from wildland fires. Accurately attributing health endpoints to wildland-fire smoke requires a determination of the exposed population. This is a difficult endeavor because most current methods for monitoring air quality are not at high temporal and spatial resolutions. Therefore, there is a growing effort to include multiple datasets and create blended products of smoke exposure that can exploit the strengths of each dataset. In this work, we combine model (WRF-Chem) simulations, NASA satellite (MODIS) observations, and in-situ surface monitors to improve exposure estimates. We will also introduce a social-media dataset of self-reported smoke/haze/pollution to improve population-level exposure estimates for the summer of 2015. Finally, we use these detailed exposure estimates in different epidemiologic study designs to provide an in-depth understanding of the role wildfire exposure plays on health outcomes.

Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques

USGS Publications Warehouse

Richardson, Leslie; Loomis, John B.; Champ, Patricia A.

2013-01-01

Estimating the economic benefits of reduced health damages due to improvements in environmental quality continues to challenge economists. We review welfare measures associated with reduced wildfire smoke exposure, and a unique dataset from California’s Station Fire of 2009 allows for a comparison of cost of illness (COI) estimates with willingness to pay (WTP) measures. The WTP for one less symptom day is estimated to be $87 and $95, using the defensive behavior and contingent valuation methods, respectively. These WTP estimates are not statistically different but do differ from a $3 traditional daily COI estimate and $17 comprehensive daily COI estimate.

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

Cultural and Demographic Factors Influencing Noise Exposure Estimates from Use of Portable Listening Devices in an Urban Environment

ERIC Educational Resources Information Center

Fligor, Brian J.; Levey, Sandra; Levey, Tania

2014-01-01

Purpose: This study examined listening levels and duration of portable listening devices (PLDs) used by people with diversity of ethnicity, education, music genre, and PLD manufacturer. The goal was to estimate participants' PLD noise exposure and identify factors influencing user behavior. Method: This study measured listening levels of 160…

Technical Report on Ozone Exposure, Risk, and Impact Assessments for Vegetation

EPA Pesticide Factsheets

The report presents analyses of national ozone air quality, vegetation exposures and risk, and impact to economic benefits that incorporates improved methods for estimating ozone at unmonitored locations.

Use of dust fall filters as passive samplers for metal concentrations in air for communities near contaminated mine tailings

PubMed Central

Beamer, P.I.; Sugeng, A. J.; Kelly, M.D.; Lothrop, N.; Klimecki, W.; Wilkinson, S.T.; Loh, M.

2014-01-01

Mine tailings are a source of metal exposures in many rural communities. Multiple air samples are necessary to assess the extent of exposures and factors contributing to these exposures. However, air sampling equipment is costly and requires trained personnel to obtain measurements, limiting the number of samples that can be collected. Simple, low-cost methods are needed to allow for increased sample collection. The objective of our study was to assess if dust fall filters can serve as passive air samplers and be used to characterize potential exposures in a community near contaminated mine tailings. We placed filters in cylinders, concurrently with active indoor air samplers, in 10 occupied homes. We calculated an estimated flow rate by dividing the mass on each dust fall filter by the bulk air concentration and the sampling duration. The mean estimated flow rate for dust fall filters was significantly different during sampling periods with precipitation. The estimated flow rate was used to estimate metal concentration in the air of these homes, as well as in 31 additional homes in another rural community impacted by contaminated mine tailings. The estimated air concentrations had a significant linear association with the measured air concentrations for beryllium, manganese and arsenic (p<0.05), whose primary source in indoor air is resuspended soil from outdoors. In the second rural community, our estimated metal concentrations in air were comparable to active air sampling measurements taken previously. This passive air sampler is a simple low-cost method to assess potential exposures near contaminated mining sites. PMID:24469149

Exposure to TCDD from base perimeter application of Agent Orange in Vietnam.

PubMed

Ross, John H; Hewitt, Andrew; Armitage, James; Solomon, Keith; Watkins, Deborah K; Ginevan, Michael E

2015-04-01

Using recognized methods routinely employed by pesticide regulatory agencies, the exposures of military personnel that were mixer/loader/applicators (M/L/A) of Agent Orange (AO) for perimeter foliage at bases during the Vietnam War were estimated. From the fraction of TCDD in AO, absorbed dosage of the manufacturing contaminant was estimated. Dermal exposure estimated from spray drift to residents of the bases was calculated using internationally recognized software that accounted for proximity, foliar density of application site, droplet size and wind speed among other factors, and produced estimates of deposition. Those that directly handled AO generally had much higher exposures than those further from the areas of use. The differences in exposure potential varied by M/L/A activity, but were typically orders of magnitude greater than bystanders. However, even the most-exposed M/L/A involved in perimeter application had lifetime exposures comparable to persons living in the U.S. at the time, i.e., ~1.3 to 5 pg TCDD/kg bodyweight. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

PubMed

Wang, Ching-Yun; Song, Xiao

2016-11-01

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method.

PubMed

Nethery, Elizabeth; Mallach, Gary; Rainham, Daniel; Goldberg, Mark S; Wheeler, Amanda J

2014-05-08

Personal exposure studies of air pollution generally use self-reported diaries to capture individuals' time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants' locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies. Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant's position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods. There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest 'good' agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time "Indoors Other" using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time "In Transit" was relatively consistent between the methods, the mean daily exposure to PM2.5 while "In Transit" was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary. Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution.

Mortality Among Workers Exposed to Toluene Diisocyanate in the US Polyurethane Foam Industry: Update and Exposure-Response Analyses

PubMed Central

Pinkerton, Lynne E.; Yiin, James H.; Daniels, Robert D.; Fent, Kenneth W.

2017-01-01

Background Mortality among 4,545 toluene diisocyante (TDI)-exposed workers was updated through 2011. The primary outcome of interest was lung cancer. Methods Life table analyses, including internal analyses by exposure duration and cumulative TDI exposure, were conducted. Results Compared with the US population, all cause and all cancer mortality was increased. Lung cancer mortality was increased but was not associated with exposure duration or cumulative TDI exposure. In post hoc analyses, lung cancer mortality was associated with employment duration in finishing jobs, but not in finishing jobs involving cutting polyurethane foam. Conclusions Dermal exposure, in contrast to inhalational exposure, to TDI is expected to be greater in finishing jobs and may play a role in the observed increase in lung cancer mortality. Limitations include the lack of smoking data, uncertainty in the exposure estimates, and exposure estimates that reflected inhalational exposure only. PMID:27346061

The burden of occupationally-related cutaneous malignant melanoma in Britain due to solar radiation.

PubMed

Rushton, Lesley; J Hutchings, Sally

2017-02-14

Increasing evidence highlights the association of occupational exposure and cutaneous malignant melanoma (CMM). We estimated the burden of CMM and total skin cancer burden in Britain due to occupational solar radiation exposure. Attributable fractions (AF) and numbers were estimated for CMM mortality and incidence using risk estimates from the published literature and national data sources for proportions exposed. We extended existing methods to account for the exposed population age structure. The estimated total AF for CMM is 2.0% (95% CI: 1.4-2.7%), giving 48 (95% CI: 33-64) deaths in (2012) and 241 (95% CI: 168-325) registrations (in 2011) attributable to occupational exposure to solar radiation. Higher exposure and larger numbers exposed led to much higher numbers for men than women. Industries of concern are construction, agriculture, public administration and defence, and land transport. These results emphasise the urgent need to develop appropriate strategies to reduce this burden.

20171015 - Integrating Toxicity, Toxicokinetic, and Exposure Data for Risk-based Chemical Alternatives Assessment (ISES)

EPA Science Inventory

In order to predict the margin between the dose needed for adverse chemical effects and actual human exposure rates, data on hazard, exposure, and toxicokinetics are needed. In vitro methods, biomonitoring, and mathematical modeling have provided initial estimates for many extant...

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

Noise Exposure Estimates of Urban MP3 Player Users

ERIC Educational Resources Information Center

Levey, Sandra; Levey, Tania; Fligor, Brian J.

2011-01-01

Purpose: To examine the sound level and duration of use of personal listening devices (PLDs) by 189 college students, ages 18-53 years, as they entered a New York City college campus, to determine whether noise exposure from PLDs was in excess of recommended exposure limits and what factors might influence exposure. Method: Free-field equivalent…

Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling.

PubMed

Fischer, Heidi J; Vergara, Ximena P; Yost, Michael; Silva, Michael; Lombardi, David A; Kheifets, Leeka

2017-01-01

Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.

The burden of disease from indoor air pollution in developing countries: comparison of estimates.

PubMed

Smith, Kirk R; Mehta, Sumi

2003-08-01

Four different methods have been applied to estimate the burden of disease due to indoor air pollution from household solid fuel use in developing countries (LDCs). The largest number of estimates involves applying exposure-response information from urban ambient air pollution studies to estimate indoor exposure concentrations of particulate air pollution. Another approach is to construct child survival curves using the results of large-scale household surveys, as has been done for India. A third approach involves cross-national analyses of child survival and household fuel use. The fourth method, referred to as the 'fuel-based' approach, which is explored in more depth here, involves applying relative risk estimates from epidemiological studies that use exposure surrogates, such as fuel type, to estimates of household solid fuel use to determine population attributable fractions by disease and age group. With this method and conservative assumptions about relative risks, 4-5 percent of the global LDC totals for both deaths and DALYs (disability adjusted life years) from acute respiratory infections, chronic obstructive pulmonary disease, tuberculosis, asthma, lung cancer, ischaemic heart disease, and blindness can be attributed to solid fuel use in developing countries. Acute respiratory infections in children under five years of age are the largest single category of deaths (64%) and DALYs (81%) from indoor air pollution, apparently being responsible globally for about 1.2 million premature deaths annually in the early 1990s.

Toward risk reduction: predicting the future burden of occupational cancer.

PubMed

Hutchings, Sally; Rushton, Lesley

2011-05-01

Interventions to reduce cancers related to certain occupations should be evidence-based. The authors have developed a method for forecasting the future burden of occupational cancer to inform strategies for risk reduction. They project risk exposure periods, accounting for cancer latencies of up to 50 years, forward in time to estimate attributable fractions for a series of forecast target years given past and projected exposure trends and under targeted reduction scenarios. Adjustment factors for changes in exposed numbers and levels are applied in estimation intervals within the risk-exposure periods. The authors illustrate the methods by using a range of scenarios for reducing lung cancer due to occupational exposure to respirable crystalline silica. Attributable fractions for lung cancer due to respirable crystalline silica could be potentially reduced from 2.07% in 2010 to nearly 0% by 2060, depending on the timing and success of interventions. Focusing on achieving compliance with current exposure standards in small industries can be more effective than setting standards at a lower level. The method can be used to highlight high-risk carcinogens, industries, and occupations. It is adaptable for other countries and other exposure situations in the general environment and can be extended to include socioeconomic impact assessment.

Airline pilot cosmic radiation and circadian disruption exposure assessment from logbooks and company records.

PubMed

Grajewski, Barbara; Waters, Martha A; Yong, Lee C; Tseng, Chih-Yu; Zivkovich, Zachary; Cassinelli, Rick T

2011-06-01

US commercial airline pilots, like all flight crew, are at increased risk for specific cancers, but the relation of these outcomes to specific air cabin exposures is unclear. Flight time or block (airborne plus taxi) time often substitutes for assessment of exposure to cosmic radiation. Our objectives were to develop methods to estimate exposures to cosmic radiation and circadian disruption for a study of chromosome aberrations in pilots and to describe workplace exposures for these pilots. Exposures were estimated for cosmic ionizing radiation and circadian disruption between August 1963 and March 2003 for 83 male pilots from a major US airline. Estimates were based on 523 387 individual flight segments in company records and pilot logbooks as well as summary records of hours flown from other sources. Exposure was estimated by calculation or imputation for all but 0.02% of the individual flight segments' block time. Exposures were estimated from questionnaire data for a comparison group of 51 male university faculty. Pilots flew a median of 7126 flight segments and 14 959 block hours for 27.8 years. In the final study year, a hypothetical pilot incurred an estimated median effective dose of 1.92 mSv (absorbed dose, 0.85 mGy) from cosmic radiation and crossed 362 time zones. This study pilot was possibly exposed to a moderate or large solar particle event a median of 6 times or once every 3.7 years of work. Work at the study airline and military flying were the two highest sources of pilot exposure for all metrics. An index of work during the standard sleep interval (SSI travel) also suggested potential chronic sleep disturbance in some pilots. For study airline flights, median segment radiation doses, time zones crossed, and SSI travel increased markedly from the 1990s to 2003 (P(trend) < 0.0001). Dose metrics were moderately correlated with records-based duration metrics (Spearman's r = 0.61-0.69). The methods developed provided an exposure profile of this group of US airline pilots, many of whom have been exposed to increasing cosmic radiation and circadian disruption from the 1990s through 2003. This assessment is likely to decrease exposure misclassification in health studies.

a Comparison of Evaluations and Assessments Obtained Using Alternative Standards for Predicting the Hazards of Whole-Body Vibration and Repeated Shocks

NASA Astrophysics Data System (ADS)

Lewis, C. H.; Griffin, M. J.

1998-08-01

There are three current standards that might be used to assess the vibration and shock transmitted by a vehicle seat with respect to possible effects on human health: ISO 2631/1 (1985), BS 6841 (1987) and ISO 2631-1 (1997). Evaluations have been performed on the seat accelerations measured in nine different transport environments (bus, car, mobile crane, fork-lift truck, tank, ambulance, power boat, inflatable boat, mountain bike) in conditions that might be considered severe. For each environment, limiting daily exposure durations were estimated by comparing the frequency weighted root mean square (i.e., r.m.s.) accelerations and the vibration dose values (i.e.,VDV), calculated according to each standard with the relevant exposure limits, action level and health guidance caution zones. Very different estimates of the limiting daily exposure duration can be obtained using the methods described in the three standards. Differences were observed due to variations in the shapes of the frequency weightings, the phase responses of the frequency weighting filters, the method of combining multi-axis vibration, the averaging method, and the assessment method. With the evaluated motions, differences in the shapes of the weighting filters results in up to about 31% difference in r.m.s. acceleration between the “old” and the “new” ISO standard and up to about 14% difference between BS 6841 and the “new” ISO 2631. There were correspondingly greater differences in the estimates of safe daily exposure durations. With three of the more severe motions there was a difference of more than 250% between estimated safe daily exposure durations based on r.m.s. acceleration and those based on fourth power vibration dose values. The vibration dose values provided the more cautious assessments of the limiting daily exposure duration.

Retrospective dose assessment for the population living in areas of local fallout from the Semipalatinsk nuclear test site Part I: External exposure.

PubMed

Gordeev, Konstantin; Shinkarev, Sergey; Ilyin, Leonid; Bouville, André; Hoshi, Masaharu; Luckyanov, Nickolas; Simon, Steven L

2006-02-01

A short analysis of all 111 atmospheric events conducted at the Semipalatinsk Test Site (STS) in 1949-1962 with regard to significant off-site exposure (more than 5 mSv of the effective dose during the first year after the explosion) has been made. The analytical method used to assess external exposure to the residents living in settlements near the STS is described. This method makes use of the archival data on the radiological conditions, including the measurements of exposure rate. Special attention was given to the residents of Dolon and Kanonerka villages exposed mainly as a result of the first test, detonated on August 29, 1949. For the residents of those settlements born in 1935, the dose estimates calculated according to the analytical method, are compared to those derived from the thermoluminescence measurements in bricks and electron paramagnetic resonance measurements in teeth. The methods described in this paper were used for external dose assessment for the cohort members at an initial stage of an ongoing epidemiological study conducted by the U.S. National Cancer Institute in the Republic of Kazakhstan. Recently revised methods and estimates of external exposure for that cohort are given in another paper (Simon et al.) in this conference.

LIMITATIONS ON THE USES OF MULTIMEDIA EXPOSURE MEASUREMENTS FOR MULTIPATHWAY EXPOSURE ASSESSMENT - PART I: HANDLING OBSERVATIONS BELOW DETECTION LIMITS

EPA Science Inventory

Multimedia data from two probability-based exposure studies were investigated in terms of how censoring of non-detects affected estimation of population parameters and associations. Appropriate methods for handling censored below-detection-limit (BDL) values in this context were...

Risk-Based High-Throughput Chemical Screening and Prioritization using Exposure Models and in Vitro Bioactivity Assays.

PubMed

Shin, Hyeong-Moo; Ernstoff, Alexi; Arnot, Jon A; Wetmore, Barbara A; Csiszar, Susan A; Fantke, Peter; Zhang, Xianming; McKone, Thomas E; Jolliet, Olivier; Bennett, Deborah H

2015-06-02

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.

Use of history science methods in exposure assessment for occupational health studies

PubMed Central

Johansen, K; Tinnerberg, H; Lynge, E

2005-01-01

Aims: To show the power of history science methods for exposure assessment in occupational health studies, using the dry cleaning industry in Denmark around 1970 as the example. Methods: Exposure data and other information on exposure status were searched for in unconventional data sources such as the Danish National Archives, the Danish Royal Library, archives of Statistics Denmark, the National Institute of Occupational Health, Denmark, and the Danish Labor Inspection Agency. Individual census forms were retrieved from the Danish National Archives. Results: It was estimated that in total 3267 persons worked in the dry cleaning industry in Denmark in 1970. They typically worked in small shops with an average size of 3.5 persons. Of these, 2645 persons were considered exposed to solvents as they were dry cleaners or worked very close to the dry cleaning process, while 622 persons were office workers, drivers, etc in shops with 10 or more persons. It was estimated that tetrachloroethylene constituted 85% of the dry cleaning solvent used, and that a shop would normally have two machines using 4.6 tons of tetrachloroethylene annually. Conclusion: The history science methods, including retrieval of material from the Danish National Archives and a thorough search in the Royal Library for publications on dry cleaning, turned out to be a very fruitful approach for collection of exposure data on dry cleaning work in Denmark. The history science methods proved to be a useful supplement to the exposure assessment methods normally applied in epidemiological studies. PMID:15961618

Analytical methods in multivariate highway safety exposure data estimation

DOT National Transportation Integrated Search

1984-01-01

Three general analytical techniques which may be of use in : extending, enhancing, and combining highway accident exposure data are : discussed. The techniques are log-linear modelling, iterative propor : tional fitting and the expectation maximizati...

Cumulative organophosphate pesticide exposure and risk assessment among pregnant women living in an agricultural community: a case study from the CHAMACOS cohort.

PubMed Central

Castorina, Rosemary; Bradman, Asa; McKone, Thomas E; Barr, Dana B; Harnly, Martha E; Eskenazi, Brenda

2003-01-01

Approximately 230,000 kg of organophosphate (OP) pesticides are applied annually in California's Salinas Valley. These activities have raised concerns about exposures to area residents. We collected three spot urine samples from pregnant women (between 1999 and 2001) enrolled in CHAMACOS (Center for the Health Assessment of Mothers and Children of Salinas), a longitudinal birth cohort study, and analyzed them for six dialkyl phosphate metabolites. We used urine from 446 pregnant women to estimate OP pesticide doses with two deterministic steady-state modeling methods: method 1, which assumed the metabolites were attributable entirely to a single diethyl or dimethyl OP pesticide; and method 2, which adapted U.S. Environmental Protection Agency (U.S. EPA) draft guidelines for cumulative risk assessment to estimate dose from a mixture of OP pesticides that share a common mechanism of toxicity. We used pesticide use reporting data for the Salinas Valley to approximate the mixture to which the women were exposed. Based on average OP pesticide dose estimates that assumed exposure to a single OP pesticide (method 1), between 0% and 36.1% of study participants' doses failed to attain a margin of exposure (MOE) of 100 relative to the U.S. EPA oral benchmark dose(10) (BMD(10)), depending on the assumption made about the parent compound. These BMD(10) values are doses expected to produce a 10% reduction in brain cholinesterase activity compared with background response in rats. Given the participants' average cumulative OP pesticide dose estimates (method 2) and regardless of the index chemical selected, we found that 14.8% of the doses failed to attain an MOE of 100 relative to the BMD(10) of the selected index. An uncertainty analysis of the pesticide mixture parameter, which is extrapolated from pesticide application data for the study area and not directly quantified for each individual, suggests that this point estimate could range from 1 to 34%. In future analyses, we will use pesticide-specific urinary metabolites, when available, to evaluate cumulative OP pesticide exposures. PMID:14527844

Influence of mobile phone traffic on base station exposure of the general public.

PubMed

Joseph, Wout; Verloock, Leen

2010-11-01

The influence of mobile phone traffic on temporal radiofrequency exposure due to base stations during 7 d is compared for five different sites with Erlang data (representing average mobile phone traffic intensity during a period of time). The time periods of high exposure and high traffic during a day are compared and good agreement is obtained. The minimal required measurement periods to obtain accurate estimates for maximal and average long-period exposure (7 d) are determined. It is shown that these periods may be very long, indicating the necessity of new methodologies to estimate maximal and average exposure from short-period measurement data. Therefore, a new method to calculate the fields at a time instant from fields at another time instant using normalized Erlang values is proposed. This enables the estimation of maximal and average exposure during a week from short-period measurements using only Erlang data and avoids the necessity of long measurement times.

Investigation on circular asymmetry of geographical distribution in cancer mortality of Hiroshima atomic bomb survivors based on risk maps: analysis of spatial survival data.

PubMed

Tonda, Tetsuji; Satoh, Kenichi; Otani, Keiko; Sato, Yuya; Maruyama, Hirofumi; Kawakami, Hideshi; Tashiro, Satoshi; Hoshi, Masaharu; Ohtaki, Megu

2012-05-01

While there is a considerable number of studies on the relationship between the risk of disease or death and direct exposure from the atomic bomb in Hiroshima, the risk for indirect exposure caused by residual radioactivity has not yet been fully evaluated. One of the reasons is that risk assessments have utilized estimated radiation doses, but that it is difficult to estimate indirect exposure. To evaluate risks for other causes, including indirect radiation exposure, as well as direct exposure, a statistical method is described here that evaluates risk with respect to individual location at the time of atomic bomb exposure instead of radiation dose. In addition, it is also considered to split the risks into separate risks due to direct exposure and other causes using radiation dose. The proposed method is applied to a cohort study of Hiroshima atomic bomb survivors. The resultant contour map suggests that the region west to the hypocenter has a higher risk compared to other areas. This in turn suggests that there exists an impact on risk that cannot be explained by direct exposure.

[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.

Comprehensive European dietary exposure model (CEDEM) for food additives.

PubMed

Tennant, David R

2016-05-01

European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

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

Kernel Density Estimation as a Measure of Environmental Exposure Related to Insulin Resistance in Breast Cancer Survivors.

PubMed

Jankowska, Marta M; Natarajan, Loki; Godbole, Suneeta; Meseck, Kristin; Sears, Dorothy D; Patterson, Ruth E; Kerr, Jacqueline

2017-07-01

Background: Environmental factors may influence breast cancer; however, most studies have measured environmental exposure in neighborhoods around home residences (static exposure). We hypothesize that tracking environmental exposures over time and space (dynamic exposure) is key to assessing total exposure. This study compares breast cancer survivors' exposure to walkable and recreation-promoting environments using dynamic Global Positioning System (GPS) and static home-based measures of exposure in relation to insulin resistance. Methods: GPS data from 249 breast cancer survivors living in San Diego County were collected for one week along with fasting blood draw. Exposure to recreation spaces and walkability was measured for each woman's home address within an 800 m buffer (static), and using a kernel density weight of GPS tracks (dynamic). Participants' exposure estimates were related to insulin resistance (using the homeostatic model assessment of insulin resistance, HOMA-IR) controlled by age and body mass index (BMI) in linear regression models. Results: The dynamic measurement method resulted in greater variability in built environment exposure values than did the static method. Regression results showed no association between HOMA-IR and home-based, static measures of walkability and recreation area exposure. GPS-based dynamic measures of both walkability and recreation area were significantly associated with lower HOMA-IR ( P < 0.05). Conclusions: Dynamic exposure measurements may provide important evidence for community- and individual-level interventions that can address cancer risk inequities arising from environments wherein breast cancer survivors live and engage. Impact: This is the first study to compare associations of dynamic versus static built environment exposure measures with insulin outcomes in breast cancer survivors. Cancer Epidemiol Biomarkers Prev; 26(7); 1078-84. ©2017 AACR . ©2017 American Association for Cancer Research.

Bayesian distributed lag interaction models to identify perinatal windows of vulnerability in children's health.

PubMed

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

2017-07-01

Epidemiological research supports an association between maternal exposure to air pollution during pregnancy and adverse children's health outcomes. Advances in exposure assessment and statistics allow for estimation of both critical windows of vulnerability and exposure effect heterogeneity. Simultaneous estimation of windows of vulnerability and effect heterogeneity can be accomplished by fitting a distributed lag model (DLM) stratified by subgroup. However, this can provide an incomplete picture of how effects vary across subgroups because it does not allow for subgroups to have the same window but different within-window effects or to have different windows but the same within-window effect. Because the timing of some developmental processes are common across subpopulations of infants while for others the timing differs across subgroups, both scenarios are important to consider when evaluating health risks of prenatal exposures. We propose a new approach that partitions the DLM into a constrained functional predictor that estimates windows of vulnerability and a scalar effect representing the within-window effect directly. The proposed method allows for heterogeneity in only the window, only the within-window effect, or both. In a simulation study we show that a model assuming a shared component across groups results in lower bias and mean squared error for the estimated windows and effects when that component is in fact constant across groups. We apply the proposed method to estimate windows of vulnerability in the association between prenatal exposures to fine particulate matter and each of birth weight and asthma incidence, and estimate how these associations vary by sex and maternal obesity status in a Boston-area prospective pre-birth cohort study. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Lung cancer incidence attributable to residential radon exposure in Alberta in 2012

PubMed Central

Grundy, Anne; Brand, Kevin; Khandwala, Farah; Poirier, Abbey; Tamminen, Sierra; Friedenreich, Christine M.; Brenner, Darren R.

2017-01-01

Background: Radon is carcinogenic, and exposure to radon has been shown to increase the risk of lung cancer. The objective of this study was to quantify the proportion and number of lung cancer cases in Alberta in 2012 that could be attributed to residential radon exposure. Methods: We estimated the population attributable risk of lung cancer for residential radon using radon exposure data from the Cross-Canada Survey of Radon Concentrations in Homes from 2009-2011 and data on all-cause and lung cancer mortality from Statistics Canada from 2008-2012. We used cancer incidence data from the Alberta Cancer Registry for 2012 to estimate the total number of lung cancers attributable to residential radon exposure. Estimates were also stratified by sex and smoking status. Results: The mean geometric residential radon level in Alberta in 2011 was 71.0 Bq/m3 (geometric standard deviation 2.14). Overall, an estimated 16.6% (95% confidence interval 9.4%-29.8%) of lung cancers were attributable to radon exposure, corresponding to 324 excess attributable cancer cases. The estimated population attributable risk of lung cancer due to radon exposure was higher among those who had never smoked (24.8%) than among ever smokers (15.6%). However, since only about 10% of cases of lung cancer occur in nonsmokers, the estimated total number of excess cases was higher for ever smokers (274) than for never smokers (48). Interpretation: With about 17% of lung cancer cases in Alberta in 2012 attributable to residential radon exposure, exposure reduction has the potential to substantially reduce Alberta's lung cancer burden. As such, home radon testing and remediation techniques represent important cancer prevention strategies. PMID:28663187

Advances in Inhalation Dosimetry Models and Methods for Occupational Risk Assessment and Exposure Limit Derivation

PubMed Central

Kuempel, Eileen D.; Sweeney, Lisa M.; Morris, John B.; Jarabek, Annie M.

2015-01-01

The purpose of this article is to provide an overview and practical guide to occupational health professionals concerning the derivation and use of dose estimates in risk assessment for development of occupational exposure limits (OELs) for inhaled substances. Dosimetry is the study and practice of measuring or estimating the internal dose of a substance in individuals or a population. Dosimetry thus provides an essential link to understanding the relationship between an external exposure and a biological response. Use of dosimetry principles and tools can improve the accuracy of risk assessment, and reduce the uncertainty, by providing reliable estimates of the internal dose at the target tissue. This is accomplished through specific measurement data or predictive models, when available, or the use of basic dosimetry principles for broad classes of materials. Accurate dose estimation is essential not only for dose-response assessment, but also for interspecies extrapolation and for risk characterization at given exposures. Inhalation dosimetry is the focus of this paper since it is a major route of exposure in the workplace. Practical examples of dose estimation and OEL derivation are provided for inhaled gases and particulates. PMID:26551218

Dermal exposure to chromium in the grinding of stainless and acid-proof steel.

PubMed

Mäkinen, Milja; Linnainmaa, Markku

2004-04-01

The aim of the study was to measure the dermal exposure levels of chromium dust during grinding of stainless and acid-proof steel parts. The potential dermal exposure of the body was measured with a patch sampling method and the actual exposure of hands with a hand-wash method. Simultaneously, personal air samples were also collected. The range of body and hand exposure to chromium dust was 4.04-3406 and 0.72-79.7 mg/h, respectively. Dust was distributed quite evenly to different body parts. Workers using hand-held grinding tools were more exposed than those using band grinders. It was judged that the sampling methods applied in this study gave a realistic estimation of exposure levels, because of the uniform distribution of contamination during grinding. Respiratory exposure was high compared to Finnish occupational exposure limit values.

Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

PubMed Central

2014-01-01

Background Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies. PMID:24410940

Estimating the Attack Rate of Pregnancy-Associated Listeriosis during a Large Outbreak

PubMed Central

Imanishi, Maho; Routh, Janell A.; Klaber, Marigny; Gu, Weidong; Vanselow, Michelle S.; Jackson, Kelly A.; Sullivan-Chang, Loretta; Heinrichs, Gretchen; Jain, Neena; Albanese, Bernadette; Callaghan, William M.; Mahon, Barbara E.; Silk, Benjamin J.

2015-01-01

Background. In 2011, a multistate outbreak of listeriosis linked to contaminated cantaloupes raised concerns that many pregnant women might have been exposed to Listeria monocytogenes. Listeriosis during pregnancy can cause fetal death, premature delivery, and neonatal sepsis and meningitis. Little information is available to guide healthcare providers who care for asymptomatic pregnant women with suspected L. monocytogenes exposure. Methods. We tracked pregnancy-associated listeriosis cases using reportable diseases surveillance and enhanced surveillance for fetal death using vital records and inpatient fetal deaths data in Colorado. We surveyed 1,060 pregnant women about symptoms and exposures. We developed three methods to estimate how many pregnant women in Colorado ate the implicated cantaloupes, and we calculated attack rates. Results. One laboratory-confirmed case of listeriosis was associated with pregnancy. The fetal death rate did not increase significantly compared to preoutbreak periods. Approximately 6,500–12,000 pregnant women in Colorado might have eaten the contaminated cantaloupes, an attack rate of ~1 per 10,000 exposed pregnant women. Conclusions. Despite many exposures, the risk of pregnancy-associated listeriosis was low. Our methods for estimating attack rates may help during future outbreaks and product recalls. Our findings offer relevant considerations for management of asymptomatic pregnant women with possible L. monocytogenes exposure. PMID:25784782

Computional algorithm for lifetime exposure to antimicrobials in pigs using register data-The LEA algorithm.

PubMed

Birkegård, Anna Camilla; Andersen, Vibe Dalhoff; Halasa, Tariq; Jensen, Vibeke Frøkjær; Toft, Nils; Vigre, Håkan

2017-10-01

Accurate and detailed data on antimicrobial exposure in pig production are essential when studying the association between antimicrobial exposure and antimicrobial resistance. Due to difficulties in obtaining primary data on antimicrobial exposure in a large number of farms, there is a need for a robust and valid method to estimate the exposure using register data. An approach that estimates the antimicrobial exposure in every rearing period during the lifetime of a pig using register data was developed into a computational algorithm. In this approach data from national registers on antimicrobial purchases, movements of pigs and farm demographics registered at farm level are used. The algorithm traces batches of pigs retrospectively from slaughter to the farm(s) that housed the pigs during their finisher, weaner, and piglet period. Subsequently, the algorithm estimates the antimicrobial exposure as the number of Animal Defined Daily Doses for treatment of one kg pig in each of the rearing periods. Thus, the antimicrobial purchase data at farm level are translated into antimicrobial exposure estimates at batch level. A batch of pigs is defined here as pigs sent to slaughter at the same day from the same farm. In this study we present, validate, and optimise a computational algorithm that calculate the lifetime exposure of antimicrobials for slaughter pigs. The algorithm was evaluated by comparing the computed estimates to data on antimicrobial usage from farm records in 15 farm units. We found a good positive correlation between the two estimates. The algorithm was run for Danish slaughter pigs sent to slaughter in January to March 2015 from farms with more than 200 finishers to estimate the proportion of farms that it was applicable for. In the final process, the algorithm was successfully run for batches of pigs originating from 3026 farms with finisher units (77% of the initial population). This number can be increased if more accurate register data can be obtained. The algorithm provides a systematic and repeatable approach to estimating the antimicrobial exposure throughout the rearing period, independent of rearing site for finisher batches, as a lifetime exposure measurement. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function.

PubMed

Jacquemin, Bénédicte; Lepeule, Johanna; Boudier, Anne; Arnould, Caroline; Benmerad, Meriem; Chappaz, Claire; Ferran, Joane; Kauffmann, Francine; Morelli, Xavier; Pin, Isabelle; Pison, Christophe; Rios, Isabelle; Temam, Sofia; Künzli, Nino; Slama, Rémy; Siroux, Valérie

2013-09-01

Errors in address geocodes may affect estimates of the effects of air pollution on health. We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults. We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant's address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects. Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 μg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: -0.56, -6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: -0.14, -3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted -2.81 (95% CI: -0.26, -5.35) using NavTEQ, or 2.08 (95% CI -4.63, 0.47, p = 0.11) using Google Maps]. Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model.

Children's exposure assessment: a review of factors influencing Children's exposure, and the data available to characterize and assess that exposure.

PubMed Central

Cohen Hubal, E A; Sheldon, L S; Burke, J M; McCurdy, T R; Berry, M R; Rigas, M L; Zartarian, V G; Freeman, N C

2000-01-01

We review the factors influencing children's exposure to environmental contaminants and the data available to characterize and assess that exposure. Children's activity pattern data requirements are demonstrated in the context of the algorithms used to estimate exposure by inhalation, dermal contact, and ingestion. Currently, data on children's exposures and activities are insufficient to adequately assess multimedia exposures to environmental contaminants. As a result, regulators use a series of default assumptions and exposure factors when conducting exposure assessments. Data to reduce uncertainty in the assumptions and exposure estimates are needed to ensure chemicals are regulated appropriately to protect children's health. To improve the database, advancement in the following general areas of research is required: identification of appropriate age/developmental benchmarks for categorizing children in exposure assessment; development and improvement of methods for monitoring children's exposures and activities; collection of activity pattern data for children (especially young children) required to assess exposure by all routes; collection of data on concentrations of environmental contaminants, biomarkers, and transfer coefficients that can be used as inputs to aggregate exposure models. PMID:10856019

The Diesel Exhaust in Miners Study: I. Overview of the Exposure Assessment Process

PubMed Central

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

2010-01-01

This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998–2001, the average measured REC exposure level by facility ranged from 40 to 384 μg m−3 for the underground workers and from 2 to 6 μg m−3 for the surface workers. For one prevalent underground job, ‘miner operator’, the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998–2001 value. A comparison of the historical CO estimates from the time trend models with 1976–1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data. PMID:20876233

The diesel exhaust in miners study: I. Overview of the exposure assessment process.

PubMed

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

2010-10-01

This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998-2001, the average measured REC exposure level by facility ranged from 40 to 384 μg m⁻³ for the underground workers and from 2 to 6 μg m⁻³ for the surface workers. For one prevalent underground job, 'miner operator', the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998-2001 value. A comparison of the historical CO estimates from the time trend models with 1976-1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data.

Use of history science methods in exposure assessment for occupational health studies.

PubMed

Johansen, K; Tinnerberg, H; Lynge, E

2005-07-01

To show the power of history science methods for exposure assessment in occupational health studies, using the dry cleaning industry in Denmark around 1970 as the example. Exposure data and other information on exposure status were searched for in unconventional data sources such as the Danish National Archives, the Danish Royal Library, archives of Statistics Denmark, the National Institute of Occupational Health, Denmark, and the Danish Labor Inspection Agency. Individual census forms were retrieved from the Danish National Archives. It was estimated that in total 3267 persons worked in the dry cleaning industry in Denmark in 1970. They typically worked in small shops with an average size of 3.5 persons. Of these, 2645 persons were considered exposed to solvents as they were dry cleaners or worked very close to the dry cleaning process, while 622 persons were office workers, drivers, etc in shops with 10 or more persons. It was estimated that tetrachloroethylene constituted 85% of the dry cleaning solvent used, and that a shop would normally have two machines using 4.6 tons of tetrachloroethylene annually. The history science methods, including retrieval of material from the Danish National Archives and a thorough search in the Royal Library for publications on dry cleaning, turned out to be a very fruitful approach for collection of exposure data on dry cleaning work in Denmark. The history science methods proved to be a useful supplement to the exposure assessment methods normally applied in epidemiological studies.

Seasonal Effect on Ocular Sun Exposure and Conjunctival UV Autofluorescence.

PubMed

Haworth, Kristina M; Chandler, Heather L

2017-02-01

To evaluate feasibility and repeatability of measures for ocular sun exposure and conjunctival ultraviolet autofluorescence (UVAF), and to test for relationships between the outcomes. Fifty volunteers were seen for two visits 14 ± 2 days apart. Ocular sun exposure was estimated over a 2-week time period using questionnaires that quantified time outdoors and ocular protection habits. Conjunctival UVAF was imaged using a Nikon D7000 camera system equipped with appropriate flash and filter system; image analysis was done using ImageJ software. Repeatability estimates were made using Bland-Altman plots with mean differences and 95% limits of agreement calculated. Non-normally distributed data was transformed by either log10 or square root methods. Linear regression was conducted to evaluate relationships between measures. Mean (±SD) values for ocular sun exposure and conjunctival UVAF were 8.86 (±11.97) hours and 9.15 (±9.47) mm, respectively. Repeatability was found to be acceptable for both ocular sun exposure and conjunctival UVAF. Univariate linear regression showed outdoor occupation to be a predictor of higher ocular sun exposure; outdoor occupation and winter season of collection both predicted higher total UVAF. Furthermore, increased portion of day spent outdoors while working was associated with increased total conjunctival UVAF. We demonstrate feasibility and repeatability of estimating ocular sun exposure using a previously unreported method and for conjunctival UVAF in a group of subjects residing in Ohio. Seasonal temperature variation may have influenced time outdoors and ultimately calculation of ocular sun exposure. As winter season of collection and outdoor occupation both predicted higher total UVAF, our data suggests that ocular sun exposure is associated with conjunctival UVAF and, possibly, that UVAF remains for at least several months after sun exposure.

Advective and diffusive dermal processes for estimating terrestrial amphibian pesticide exposure

EPA Science Inventory

Background/Question/Methods Dermal exposure presents a potentially significant but understudied route for pesticide uptake in terrestrial amphibians. Historically, evaluation of pesticide risk to both amphibians and reptiles has been achieved by comparing ingestion and inhalat...

A Human Mixture Risk Assessment for Neurodevelopmental Toxicity Associated with Polybrominated Diphenyl Ethers Used as Flame Retardants

PubMed Central

Martin, Olwenn V.; Evans, Richard M.; Faust, Michael

2017-01-01

Background: The European Food Safety Authority recently concluded that the exposure of small children (1–3 y old) to brominated diphenyl ether (BDE)-99 may exceed acceptable levels defined in relation to neurodevelopmental toxicity in rodents. The flame retardant BDE-209 may release BDE-99 and other lower brominated BDEs through biotic and abiotic degradation, and all age groups are exposed not only to BDE-209 and -99 but also to a cocktail of BDE congeners with evidence of neurodevelopmental toxicity. The possible risks from combined exposures to these substances have not been evaluated. Objectives: We performed a congener-specific mixture risk assessment (MRA) of human exposure to combinations of BDE-209 and other BDEs based on estimated exposures via diet and dust intake and on measured levels in biologic samples. Methods: We employed the Hazard Index (HI) method by using BDE congener-specific reference doses for neurodevelopmental toxicity. Results: Our HI analysis suggests that combined exposures to polybrominated diphenyl ethers (PBDEs) may exceed acceptable levels in breastfeeding infants (0–3 mo old) and in small children (1–3 y old), even for moderate (vs. high) exposure scenarios. Our estimates also suggest that acceptable levels of combined PBDEs may be exceeded in adults whose diets are high in fish. Small children had the highest combined exposures, with some estimated body burdens that were similar to body burdens associated with developmental neurotoxicity in rodents. Conclusions: Our estimates corroborate reports from several recent epidemiological studies of associations between PBDE exposures and neurobehavioral outcomes, and they support the inclusion of BDE-209 in the persistent organic pollutant (POP) convention as well as the need for strategies to reduce exposures to PBDE mixtures, including maximum residue limits for PBDEs in food and measures for limiting the release of PBDEs from consumer waste. https://doi.org/10.1289/EHP826 PMID:28886598

Product Deformulation to Inform High-throughput Exposure ...

EPA Pesticide Factsheets

The health risks posed by the thousands of chemicals in our environment depends on both chemical hazard and exposure. However, relatively few chemicals have estimates of exposure intake, limiting the understanding of risks. We have previously developed a heuristics-based exposure estimation method that depends on simple factors such as the presence or absence of chemicals in consumer products to estimate exposure for thousands of chemicals. Although this method was predictive when compared with human biomonitoring data, limited data are available on the chemical constituents within most articles of commerce. We aim to broaden the number of products with constituent chemical information and refine exposure models by quantifying constituent concentration. A selection of five samples each from 20 diverse consumer product categories (e.g., lotion, clothing, carpet) were analyzed using solvent extraction followed by gas chromatograph (GC) x GC Time of Flight Mass Spectrometry (GCxGC-TOF/MS), which is suited for forensic investigation of complex matrices. In an examination of five plastic children’s toys, a total of 306 unique compounds were identified across all toys, including 102 Tox21 chemicals such as diethyl phthalate and bisphenol AF. As many as 114 and as few as 56 chemicals were identified in each toy. Across the five toys, a range of 0 to 40 unique peaks remain unidentified. Interestingly, bisphenol A (BPA) was identified in a children’s toy marked

Development of a Sampler for Total Aerosol Deposition in the Human Respiratory Tract

PubMed Central

Koehler, Kirsten A.; Clark, Phillip; Volckens, John

2009-01-01

Studies that seek to associate reduced human health with exposure to occupational and environmental aerosols are often hampered by limitations in the exposure assessment process. One limitation involves the measured exposure metric itself. Current methods for personal exposure assessment are designed to estimate the aspiration of aerosol into the human body. Since a large proportion of inhaled aerosol is subsequently exhaled, a portion of the aspirated aerosol will not contribute to the dose. This leads to variable exposure misclassification (for heterogenous exposures) and increased uncertainty in health effect associations. Alternatively, a metric for respiratory deposition would provide a more physiologically relevant estimate of risk. To address this challenge, we have developed a method to estimate the deposition of aerosol in the human respiratory tract using a sampler engineered from polyurethane foam. Using a semi-empirical model based on inertial, gravitational, and diffusional particle deposition, a foam was engineered to mimic aerosol total deposition in the human respiratory tract. The sampler is comprised of commercially available foam with fiber diameter = 49.5 μm (equivalent to industry standard 100 PPI foam) of 8 cm thickness operating at a face velocity of 1.3 m s−1. Additionally, the foam sampler yields a relatively low-pressure drop, independent of aerosol loading, providing uniform particle collection efficiency over time. PMID:19638392

Particle Pollution Estimation Based on Image Analysis

PubMed Central

Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

2016-01-01

Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757

Particle Pollution Estimation Based on Image Analysis.

PubMed

Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

2016-01-01

Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction.

Theoretical estimates of exposure timescales of protein binding sites on DNA regulated by nucleosome kinetics.

PubMed

Parmar, Jyotsana J; Das, Dibyendu; Padinhateeri, Ranjith

2016-02-29

It is being increasingly realized that nucleosome organization on DNA crucially regulates DNA-protein interactions and the resulting gene expression. While the spatial character of the nucleosome positioning on DNA has been experimentally and theoretically studied extensively, the temporal character is poorly understood. Accounting for ATPase activity and DNA-sequence effects on nucleosome kinetics, we develop a theoretical method to estimate the time of continuous exposure of binding sites of non-histone proteins (e.g. transcription factors and TATA binding proteins) along any genome. Applying the method to Saccharomyces cerevisiae, we show that the exposure timescales are determined by cooperative dynamics of multiple nucleosomes, and their behavior is often different from expectations based on static nucleosome occupancy. Examining exposure times in the promoters of GAL1 and PHO5, we show that our theoretical predictions are consistent with known experiments. We apply our method genome-wide and discover huge gene-to-gene variability of mean exposure times of TATA boxes and patches adjacent to TSS (+1 nucleosome region); the resulting timescale distributions have non-exponential tails. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Model-based ultrasound temperature visualization during and following HIFU exposure.

PubMed

Ye, Guoliang; Smith, Penny Probert; Noble, J Alison

2010-02-01

This paper describes the application of signal processing techniques to improve the robustness of ultrasound feedback for displaying changes in temperature distribution in treatment using high-intensity focused ultrasound (HIFU), especially at the low signal-to-noise ratios that might be expected in in vivo abdominal treatment. Temperature estimation is based on the local displacements in ultrasound images taken during HIFU treatment, and a method to improve robustness to outliers is introduced. The main contribution of the paper is in the application of a Kalman filter, a statistical signal processing technique, which uses a simple analytical temperature model of heat dispersion to improve the temperature estimation from the ultrasound measurements during and after HIFU exposure. To reduce the sensitivity of the method to previous assumptions on the material homogeneity and signal-to-noise ratio, an adaptive form is introduced. The method is illustrated using data from HIFU exposure of ex vivo bovine liver. A particular advantage of the stability it introduces is that the temperature can be visualized not only in the intervals between HIFU exposure but also, for some configurations, during the exposure itself. 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Lipid Adjustment for Chemical Exposures: Accounting for Concomitant Variables

PubMed Central

Li, Daniel; Longnecker, Matthew P.; Dunson, David B.

2013-01-01

Background Some environmental chemical exposures are lipophilic and need to be adjusted by serum lipid levels before data analyses. There are currently various strategies that attempt to account for this problem, but all have their drawbacks. To address such concerns, we propose a new method that uses Box-Cox transformations and a simple Bayesian hierarchical model to adjust for lipophilic chemical exposures. Methods We compared our Box-Cox method to existing methods. We ran simulation studies in which increasing levels of lipid-adjusted chemical exposure did and did not increase the odds of having a disease, and we looked at both single-exposure and multiple-exposures cases. We also analyzed an epidemiology dataset that examined the effects of various chemical exposures on the risk of birth defects. Results Compared with existing methods, our Box-Cox method produced unbiased estimates, good coverage, similar power, and lower type-I error rates. This was the case in both single- and multiple-exposure simulation studies. Results from analysis of the birth-defect data differed from results using existing methods. Conclusion Our Box-Cox method is a novel and intuitive way to account for the lipophilic nature of certain chemical exposures. It addresses some of the problems with existing methods, is easily extendable to multiple exposures, and can be used in any analyses that involve concomitant variables. PMID:24051893

A tiered asthma hazard characterization and exposure assessment approach for evaluation of consumer product ingredients.

PubMed

Maier, Andrew; Vincent, Melissa J; Parker, Ann; Gadagbui, Bernard K; Jayjock, Michael

2015-12-01

Asthma is a complex syndrome with significant consequences for those affected. The number of individuals affected is growing, although the reasons for the increase are uncertain. Ensuring the effective management of potential exposures follows from substantial evidence that exposure to some chemicals can increase the likelihood of asthma responses. We have developed a safety assessment approach tailored to the screening of asthma risks from residential consumer product ingredients as a proactive risk management tool. Several key features of the proposed approach advance the assessment resources often used for asthma issues. First, a quantitative health benchmark for asthma or related endpoints (irritation and sensitization) is provided that extends qualitative hazard classification methods. Second, a parallel structure is employed to include dose-response methods for asthma endpoints and methods for scenario specific exposure estimation. The two parallel tracks are integrated in a risk characterization step. Third, a tiered assessment structure is provided to accommodate different amounts of data for both the dose-response assessment (i.e., use of existing benchmarks, hazard banding, or the threshold of toxicological concern) and exposure estimation (i.e., use of empirical data, model estimates, or exposure categories). Tools building from traditional methods and resources have been adapted to address specific issues pertinent to asthma toxicology (e.g., mode-of-action and dose-response features) and the nature of residential consumer product use scenarios (e.g., product use patterns and exposure durations). A case study for acetic acid as used in various sentinel products and residential cleaning scenarios was developed to test the safety assessment methodology. In particular, the results were used to refine and verify relationships among tiered approaches such that each lower data tier in the approach provides a similar or greater margin of safety for a given scenario. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[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.

Speckle-field propagation in 'frozen' turbulence: brightness function approach

NASA Astrophysics Data System (ADS)

Dudorov, Vadim V.; Vorontsov, Mikhail A.; Kolosov, Valeriy V.

2006-08-01

Speckle-field long- and short-exposure spatial correlation characteristics for target-in-the-loop (TIL) laser beam propagation and scattering in atmospheric turbulence are analyzed through the use of two different approaches: the conventional Monte Carlo (MC) technique and the recently developed brightness function (BF) method. Both the MC and the BF methods are applied to analysis of speckle-field characteristics averaged over target surface roughness realizations under conditions of 'frozen' turbulence. This corresponds to TIL applications where speckle-field fluctuations associated with target surface roughness realization updates occur within a time scale that can be significantly shorter than the characteristic atmospheric turbulence time. Computational efficiency and accuracy of both methods are compared on the basis of a known analytical solution for the long-exposure mutual correlation function. It is shown that in the TIL propagation scenarios considered the BF method provides improved accuracy and requires significantly less computational time than the conventional MC technique. For TIL geometry with a Gaussian outgoing beam and Lambertian target surface, both analytical and numerical estimations for the speckle-field long-exposure correlation length are obtained. Short-exposure speckle-field correlation characteristics corresponding to propagation in 'frozen' turbulence are estimated using the BF method. It is shown that atmospheric turbulence-induced static refractive index inhomogeneities do not significantly affect the characteristic correlation length of the speckle field, whereas long-exposure spatial correlation characteristics are strongly dependent on turbulence strength.

Speckle-field propagation in 'frozen' turbulence: brightness function approach.

PubMed

Dudorov, Vadim V; Vorontsov, Mikhail A; Kolosov, Valeriy V

2006-08-01

Speckle-field long- and short-exposure spatial correlation characteristics for target-in-the-loop (TIL) laser beam propagation and scattering in atmospheric turbulence are analyzed through the use of two different approaches: the conventional Monte Carlo (MC) technique and the recently developed brightness function (BF) method. Both the MC and the BF methods are applied to analysis of speckle-field characteristics averaged over target surface roughness realizations under conditions of 'frozen' turbulence. This corresponds to TIL applications where speckle-field fluctuations associated with target surface roughness realization updates occur within a time scale that can be significantly shorter than the characteristic atmospheric turbulence time. Computational efficiency and accuracy of both methods are compared on the basis of a known analytical solution for the long-exposure mutual correlation function. It is shown that in the TIL propagation scenarios considered the BF method provides improved accuracy and requires significantly less computational time than the conventional MC technique. For TIL geometry with a Gaussian outgoing beam and Lambertian target surface, both analytical and numerical estimations for the speckle-field long-exposure correlation length are obtained. Short-exposure speckle-field correlation characteristics corresponding to propagation in 'frozen' turbulence are estimated using the BF method. It is shown that atmospheric turbulence-induced static refractive index inhomogeneities do not significantly affect the characteristic correlation length of the speckle field, whereas long-exposure spatial correlation characteristics are strongly dependent on turbulence strength.

UTILIZATION OF THE WAVEFRONT SENSOR AND SHORT-EXPOSURE IMAGES FOR SIMULTANEOUS ESTIMATION OF QUASI-STATIC ABERRATION AND EXOPLANET INTENSITY

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

Frazin, Richard A., E-mail: rfrazin@umich.edu

2013-04-10

Heretofore, the literature on exoplanet detection with coronagraphic telescope systems has paid little attention to the information content of short exposures and methods of utilizing the measurements of adaptive optics wavefront sensors. This paper provides a framework for the incorporation of the wavefront sensor measurements in the context of observing modes in which the science camera takes millisecond exposures. In this formulation, the wavefront sensor measurements provide a means to jointly estimate the static speckle and the planetary signal. The ability to estimate planetary intensities in as little as a few seconds has the potential to greatly improve the efficiencymore » of exoplanet search surveys. For simplicity, the mathematical development assumes a simple optical system with an idealized Lyot coronagraph. Unlike currently used methods, in which increasing the observation time beyond a certain threshold is useless, this method produces estimates whose error covariances decrease more quickly than inversely proportional to the observation time. This is due to the fact that the estimates of the quasi-static aberrations are informed by a new random (but approximately known) wavefront every millisecond. The method can be extended to include angular (due to diurnal field rotation) and spectral diversity. Numerical experiments are performed with wavefront data from the AEOS Adaptive Optics System sensing at 850 nm. These experiments assume a science camera wavelength {lambda} of 1.1 {mu}, that the measured wavefronts are exact, and a Gaussian approximation of shot-noise. The effects of detector read-out noise and other issues are left to future investigations. A number of static aberrations are introduced, including one with a spatial frequency exactly corresponding the planet location, which was at a distance of Almost-Equal-To 3{lambda}/D from the star. Using only 4 s of simulated observation time, a planetary intensity, of Almost-Equal-To 1 photon ms{sup -1}, and a stellar intensity of Almost-Equal-To 10{sup 5} photons ms{sup -1} (contrast ratio 10{sup 5}), the short-exposure estimation method recovers the amplitudes' static aberrations with 1% accuracy, and the planet brightness with 20% accuracy.« less

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Risk-based high-throughput chemical screening and prioritization using exposure models and in vitro bioactivity assays

DOE PAGES

Shin, Hyeong -Moo; Ernstoff, Alexi; Arnot, Jon A.; ...

2015-05-01

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate dailymore » intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.« less

Use of a crop and job specific exposure matrix for retrospective assessment of long-term exposure in studies of chronic neurotoxic effects of agrichemicals

PubMed Central

London, L.; Myers, J. E.

1998-01-01

RATIONALE: Job exposure matrices (JEMs) are widely used in occupational epidemiology, particularly when biological or environmental monitoring data are scanty. However, as with most exposure estimates, JEMs may be vulnerable to misclassification. OBJECTIVES: To estimate the long term exposure of farm workers based on a JEM developed for use in a study of the neurotoxic effects of organophosphates and to evaluate the repeatability and validity of the JEM. METHODS: A JEM was constructed with secondary data from industry and expert opinion of the estimate of agrichemical exposure within every possible job activity in the JEM to weight job days for exposure to organophosphates. Cumulative lifetime and average intensity exposure of organophosphate exposure were calculated for 163 pesticide applicators and 84 controls. Repeat questionnaires were given to 29 participants three months later to test repeatability of measurements. The ability of JEM based exposure to predict a known marker of organophosphate exposure was used to validate the JEM. RESULTS: Cumulative lifetime exposure as measured in kg organophosphate exposure, was significantly associated with erythrocyte cholinesterase concentrations (partial r2 = 5%; p < 0.01), controlled for a range of confounders. Repeatability in a subsample of 29 workers of the estimates of cumulative (Pearson's r = 0.67; 95% confidence interval (95% CI) 0.41 to 0.83), and average lifetime intensity of exposure (Pearson's r = 0.60 95% CI 0.31 to 0.79) was adequate. CONCLUSION: The JEM seems promising for farming settings, particularly in developing countries where data on chemical application and biological monitoring are unavailable.   PMID:9624271

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

Haloacetic acids in drinking water and risk for stillbirth

PubMed Central

King, W; Dodds, L; Allen, A; Armson, B; Fell, D; Nimrod, C

2005-01-01

Aims: To investigate the effects of haloacetic acid (HAA) compounds in drinking water on stillbirth risk. Methods: A population based case-control study was conducted in Nova Scotia and Eastern Ontario, Canada. Estimates of daily exposure to total and specific HAAs were based on household water samples and questionnaire information on water consumption at home and work. Results: The analysis included 112 stillbirth cases and 398 live birth controls. In analysis without adjustment for total THM exposure, a relative risk greater than 2 was observed for an intermediate exposure category for total HAA and dichloroacetic acid measures. After adjustment for total THM exposure, the risk estimates for intermediate exposure categories were diminished, the relative risk associated with the highest category was in the direction of a protective effect, and all confidence intervals included the null value. Conclusions: No association was observed between HAA exposures and stillbirth risk after controlling for THM exposures. PMID:15657195

Estimating Effects with Rare Outcomes and High Dimensional Covariates: Knowledge is Power

PubMed Central

Ahern, Jennifer; Galea, Sandro; van der Laan, Mark

2016-01-01

Many of the secondary outcomes in observational studies and randomized trials are rare. Methods for estimating causal effects and associations with rare outcomes, however, are limited, and this represents a missed opportunity for investigation. In this article, we construct a new targeted minimum loss-based estimator (TMLE) for the effect or association of an exposure on a rare outcome. We focus on the causal risk difference and statistical models incorporating bounds on the conditional mean of the outcome, given the exposure and measured confounders. By construction, the proposed estimator constrains the predicted outcomes to respect this model knowledge. Theoretically, this bounding provides stability and power to estimate the exposure effect. In finite sample simulations, the proposed estimator performed as well, if not better, than alternative estimators, including a propensity score matching estimator, inverse probability of treatment weighted (IPTW) estimator, augmented-IPTW and the standard TMLE algorithm. The new estimator yielded consistent estimates if either the conditional mean outcome or the propensity score was consistently estimated. As a substitution estimator, TMLE guaranteed the point estimates were within the parameter range. We applied the estimator to investigate the association between permissive neighborhood drunkenness norms and alcohol use disorder. Our results highlight the potential for double robust, semiparametric efficient estimation with rare events and high dimensional covariates. PMID:28529839

Radon-induced lung cancer deaths may be overestimated due to failure to account for confounding by exposure to diesel engine exhaust in BEIR VI miner studies

PubMed Central

MacNaughton, Piers; Laurent, Jose Cedeno; Allen, Joseph G.

2017-01-01

Background EPA reported that radon is the second leading cause of lung cancer in the United States, killing 21,100 people per year. EPA relies on the BEIR VI models, based on an evaluation of radon exposure and lung cancer risk in studies of miners. But these models did not account for co-exposure to diesel exhaust, a known human carcinogen recently classified by IARC. It is probable then that a portion of the lung cancer deaths in the miner cohorts are originally attributable to the exposure to diesel rather than radon. Objective To re-evaluate EPA’s radon attributable lung cancer estimates accounting for diesel exposure information in the miner cohorts. Methods We used estimates of historical diesel concentrations, combined with diesel exposure-response functions, to estimate the risks of lung cancer attributable to diesel engine exhaust (DEE) exposure in the miner studies. We re-calculated the fatal lung cancer risk attributable to radon after accounting for risk from diesel and re-estimated the number of U.S. deaths associated with radon in the U.S. using EPA’s methodology. Results Considering the probable confounding with DEE exposure and using the same estimate of baseline mortality from 1989–91 that the EPA currently uses in their calculations, we estimate that radon-induced lung cancer deaths per year are 15,600 (95% CI: 14,300, 17,000)– 19,300 (95% CI: 18,800, 20,000) in the U.S. population, a reduction of 9%–26%. The death estimates would be 12,900–15,900 using 2014 baseline vital statistics. Conclusions We recommend further research on re-evaluating the health effects of exposure to radon that accounts for new information on diesel exhaust carcinogenicity in BEIR VI models, up-to-date vital statistics and new epidemiological evidence from residential studies. PMID:28886109

A Comparison of the β-Substitution Method and a Bayesian Method for Analyzing Left-Censored Data

PubMed Central

Huynh, Tran; Quick, Harrison; Ramachandran, Gurumurthy; Banerjee, Sudipto; Stenzel, Mark; Sandler, Dale P.; Engel, Lawrence S.; Kwok, Richard K.; Blair, Aaron; Stewart, Patricia A.

2016-01-01

Classical statistical methods for analyzing exposure data with values below the detection limits are well described in the occupational hygiene literature, but an evaluation of a Bayesian approach for handling such data is currently lacking. Here, we first describe a Bayesian framework for analyzing censored data. We then present the results of a simulation study conducted to compare the β-substitution method with a Bayesian method for exposure datasets drawn from lognormal distributions and mixed lognormal distributions with varying sample sizes, geometric standard deviations (GSDs), and censoring for single and multiple limits of detection. For each set of factors, estimates for the arithmetic mean (AM), geometric mean, GSD, and the 95th percentile (X0.95) of the exposure distribution were obtained. We evaluated the performance of each method using relative bias, the root mean squared error (rMSE), and coverage (the proportion of the computed 95% uncertainty intervals containing the true value). The Bayesian method using non-informative priors and the β-substitution method were generally comparable in bias and rMSE when estimating the AM and GM. For the GSD and the 95th percentile, the Bayesian method with non-informative priors was more biased and had a higher rMSE than the β-substitution method, but use of more informative priors generally improved the Bayesian method’s performance, making both the bias and the rMSE more comparable to the β-substitution method. An advantage of the Bayesian method is that it provided estimates of uncertainty for these parameters of interest and good coverage, whereas the β-substitution method only provided estimates of uncertainty for the AM, and coverage was not as consistent. Selection of one or the other method depends on the needs of the practitioner, the availability of prior information, and the distribution characteristics of the measurement data. We suggest the use of Bayesian methods if the practitioner has the computational resources and prior information, as the method would generally provide accurate estimates and also provides the distributions of all of the parameters, which could be useful for making decisions in some applications. PMID:26209598

Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models.

PubMed

Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M

2017-12-01

The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.

New High Throughput Methods to Estimate Chemical Exposure

EPA Science Inventory

EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing an...

Gaussian Quadrature is an efficient method for the back-transformation in estimating the usual intake distribution when assessing dietary exposure.

PubMed

Dekkers, A L M; Slob, W

2012-10-01

In dietary exposure assessment, statistical methods exist for estimating the usual intake distribution from daily intake data. These methods transform the dietary intake data to normal observations, eliminate the within-person variance, and then back-transform the data to the original scale. We propose Gaussian Quadrature (GQ), a numerical integration method, as an efficient way of back-transformation. We compare GQ with six published methods. One method uses a log-transformation, while the other methods, including GQ, use a Box-Cox transformation. This study shows that, for various parameter choices, the methods with a Box-Cox transformation estimate the theoretical usual intake distributions quite well, although one method, a Taylor approximation, is less accurate. Two applications--on folate intake and fruit consumption--confirmed these results. In one extreme case, some methods, including GQ, could not be applied for low percentiles. We solved this problem by modifying GQ. One method is based on the assumption that the daily intakes are log-normally distributed. Even if this condition is not fulfilled, the log-transformation performs well as long as the within-individual variance is small compared to the mean. We conclude that the modified GQ is an efficient, fast and accurate method for estimating the usual intake distribution. Copyright © 2012 Elsevier Ltd. All rights reserved.

Valuing the Economic Costs of Allergic Rhinitis, Acute Bronchitis, and Asthma from Exposure to Indoor Dampness and Mold in the US

PubMed Central

2016-01-01

Two foundational methods for estimating the total economic burden of disease are cost of illness (COI) and willingness to pay (WTP). WTP measures the full cost to society, but WTP estimates are difficult to compute and rarely available. COI methods are more often used but less likely to reflect full costs. This paper attempts to estimate the full economic cost (2014$) of illnesses resulting from exposure to dampness and mold using COI methods and WTP where the data is available. A limited sensitivity analysis of alternative methods and assumptions demonstrates a wide potential range of estimates. In the final estimates, the total annual cost to society attributable to dampness and mold is estimated to be $3.7 (2.3–4.7) billion for allergic rhinitis, $1.9 (1.1–2.3) billion for acute bronchitis, $15.1 (9.4–20.6) billion for asthma morbidity, and $1.7 (0.4–4.5) billion for asthma mortality. The corresponding costs from all causes, not limited to dampness and mold, using the same approach would be $24.8 billion for allergic rhinitis, $13.5 billion for acute bronchitis, $94.5 billion for asthma morbidity, and $10.8 billion for asthma mortality. PMID:27313630

A simple method for assessing occupational exposure via the one-way random effects model.

PubMed

Krishnamoorthy, K; Mathew, Thomas; Peng, Jie

2016-11-01

A one-way random effects model is postulated for the log-transformed shift-long personal exposure measurements, where the random effect in the model represents an effect due to the worker. Simple closed-form confidence intervals are proposed for the relevant parameters of interest using the method of variance estimates recovery (MOVER). The performance of the confidence bounds is evaluated and compared with those based on the generalized confidence interval approach. Comparison studies indicate that the proposed MOVER confidence bounds are better than the generalized confidence bounds for the overall mean exposure and an upper percentile of the exposure distribution. The proposed methods are illustrated using a few examples involving industrial hygiene data.

Cumulative asbestos exposure for US automobile mechanics involved in brake repair (circa 1950s-2000).

PubMed

Finley, Brent L; Richter, Richard O; Mowat, Fionna S; Mlynarek, Steve; Paustenbach, Dennis J; Warmerdam, John M; Sheehan, Patrick J

2007-11-01

We analyzed cumulative lifetime exposure to chrysotile asbestos experienced by brake mechanics in the US during the period 1950-2000. Using Monte Carlo methods, cumulative exposures were calculated using the distribution of 8-h time-weighted average exposure concentrations for brake mechanics and the distribution of job tenure data for automobile mechanics. The median estimated cumulative exposures for these mechanics, as predicted by three probabilistic models, ranged from 0.16 to 0.41 fibers per cubic centimeter (f/cm(3)) year for facilities with no dust-control procedures (1970s), and from 0.010 to 0.012 f/cm(3) year for those employing engineering controls (1980s). Upper-bound (95%) estimates for the 1970s and 1980s were 1.96 to 2.79 and 0.07-0.10 f/cm(3) year, respectively. These estimates for US brake mechanics are consistent with, but generally slightly lower than, those reported for European mechanics. The values are all substantially lower than the cumulative exposure of 4.5 f/cm(3) year associated with occupational exposure to 0.1 f/cm(3) of asbestos for 45 years that is currently permitted under the current occupational exposure limits in the US. Cumulative exposures were usually about 100- to 1,000-fold less than those of other occupational groups with asbestos exposure for similar time periods. The cumulative lifetime exposure estimates presented here, combined with the negative epidemiology data for brake mechanics, could be used to refine the risk assessments for chrysotile-exposed populations.

An original imputation technique of missing data for assessing exposure of newborns to perchlorate in drinking water.

PubMed

Caron, Alexandre; Clement, Guillaume; Heyman, Christophe; Aernout, Eva; Chazard, Emmanuel; Le Tertre, Alain

2015-01-01

Incompleteness of epidemiological databases is a major drawback when it comes to analyzing data. We conceived an epidemiological study to assess the association between newborn thyroid function and the exposure to perchlorates found in the tap water of the mother's home. Only 9% of newborn's exposure to perchlorate was known. The aim of our study was to design, test and evaluate an original method for imputing perchlorate exposure of newborns based on their maternity of birth. In a first database, an exhaustive collection of newborn's thyroid function measured during a systematic neonatal screening was collected. In this database the municipality of residence of the newborn's mother was only available for 2012. Between 2004 and 2011, the closest data available was the municipality of the maternity of birth. Exposure was assessed using a second database which contained the perchlorate levels for each municipality. We computed the catchment area of every maternity ward based on the French nationwide exhaustive database of inpatient stay. Municipality, and consequently perchlorate exposure, was imputed by a weighted draw in the catchment area. Missing values for remaining covariates were imputed by chained equation. A linear mixture model was computed on each imputed dataset. We compared odds ratios (ORs) and 95% confidence intervals (95% CI) estimated on real versus imputed 2012 data. The same model was then carried out for the whole imputed database. The ORs estimated on 36,695 observations by our multiple imputation method are comparable to the real 2012 data. On the 394,979 observations of the whole database, the ORs remain stable but the 95% CI tighten considerably. The model estimates computed on imputed data are similar to those calculated on real data. The main advantage of multiple imputation is to provide unbiased estimate of the ORs while maintaining their variances. Thus, our method will be used to increase the statistical power of future studies by including all 394,979 newborns.

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

Comparison of geostatistical interpolation and remote sensing techniques for estimating long-term exposure to ambient PM2.5 concentrations across the continental United States.

PubMed

Lee, Seung-Jae; Serre, Marc L; van Donkelaar, Aaron; Martin, Randall V; Burnett, Richard T; Jerrett, Michael

2012-12-01

A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data. We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation. We developed a space-time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals. The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates. We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.

PM2.5 exposure and birth outcomes: Use of satellite- and monitor-based data

PubMed Central

Hyder, Ayaz; Lee, Hyung Joo; Ebisu, Keita; Koutrakis, Petros; Belanger, Kathleen; Bell, Michelle Lee

2014-01-01

Background Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment. Methods We used birth certificate data for births in Connecticut and Massachusetts, U.S. (2000-2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled using 2 methods – denoted satellite (1) and satellite (2) – before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (LBW <2500g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks). Results Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per inter-quartile range (2.41 μg/m3)-increase in PM2.5 was -6g (95% confidence interval = -8 to -5), -16g (-21 to -11) and -19g (-23 to -15), using the monitor, satellite (1) and satellite (2) methods, respectively. Adjusted odds ratios, based on the same 3 exposure methods, for term LBW were 1.01 (0.98 to 1.04), 1.06 (0.97 to 1.16), and 1.08 (1.01 to 1.16); for SGA, 1.03 (1.01 to 1.04), 1.06 (1.03 to 1.10) and 1.08 (1.04 to 1.11); and for preterm birth, 1.00 (0.99 to 1.02), 0.98 (0.94 to 1.03) and 0.99 (0.95 to 1.03). Conclusions Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information. PMID:24240652

Measuring visual exposure to smoking behaviours: a viewshed analysis of smoking at outdoor bars and cafés across a capital city’s downtown area

PubMed Central

2014-01-01

Background The influence of visual exposure to health-related behaviours, such as smoking, is increasingly acknowledged in the public health literature. Social contagion or normalisation is thought to operate through the visibility of those behaviours. There has been a lack of systematic and comprehensive approaches to quantifying visual exposure to these behaviours over a relatively large geographic area. We describe the novel application of a geographic tool, viewshed analysis, to estimate visual exposure to smoking outside bars/cafés across a downtown area. Methods Smoking was observed for different times and days of the week at 14 outdoor areas of bars/cafés throughout downtown Wellington, New Zealand. We used these data to extrapolate to other bars/cafés with outdoor seating. We then conducted viewshed analyses to estimate visual exposure to smoking at bars/cafés for all public outdoor spaces. Results We observed a smoking point prevalence of 16%. Visibility analyses indicated that estimated visible smoking was highest in the evenings (7-8 pm), where the average values across Wednesday and Friday ranged from zero up to 92 visible smokers (mean = 1.44). Estimated visible smoking at midday ranged from zero to 13 (mean = 0.27). Values were also higher at the end of the week compared with midweek in the evening. Maps indicate that streets with high levels of retail shops and hospitality areas had high values of estimated visible smokers, particularly in the evening where numbers were consistently above 50. Conclusions This paper highlights a useful method for measuring the extent of visual exposure to smoking behaviours across relatively large areas using a geospatial approach. Applying this method in other locations would require consideration of place-specific characteristics which impact on visibility and could be improved through more sophisticated extrapolation of observational data across the study area. The findings of this and similar research could ultimately support the expansion of smokefree public spaces. PMID:24708883

A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods

NASA Astrophysics Data System (ADS)

Choi, Giehae; Bell, Michelle L.; Lee, Jong-Tae

2017-04-01

The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.

Environmental Inequality in Exposures to Airborne Particulate Matter Components in the United States

PubMed Central

Ebisu, Keita

2012-01-01

Background: Growing evidence indicates that toxicity of fine particulate matter ≤ 2.5 μm in diameter (PM2.5) differs by chemical component. Exposure to components may differ by population. Objectives: We investigated whether exposures to PM2.5 components differ by race/ethnicity, age, and socioeconomic status (SES). Methods: Long-term exposures (2000 through 2006) were estimated for 215 U.S. census tracts for PM2.5 and for 14 PM2.5 components. Population-weighted exposures were combined to generate overall estimated exposures by race/ethnicity, education, poverty status, employment, age, and earnings. We compared population characteristics for tracts with and without PM2.5 component monitors. Results: Larger disparities in estimated exposures were observed for components than for PM2.5 total mass. For race/ethnicity, whites generally had the lowest exposures. Non-Hispanic blacks had higher exposures than did whites for 13 of the 14 components. Hispanics generally had the highest exposures (e.g., 152% higher than whites for chlorine, 94% higher for aluminum). Young persons (0–19 years of age) had levels as high as or higher than other ages for all exposures except sulfate. Persons with lower SES had higher estimated exposures, with some exceptions. For example, a 10% increase in the proportion unemployed was associated with a 20.0% increase in vanadium and an 18.3% increase in elemental carbon. Census tracts with monitors had more non-Hispanic blacks, lower education and earnings, and higher unemployment and poverty than did tracts without monitors. Conclusions: Exposures to PM2.5 components differed by race/ethnicity, age, and SES. If some components are more toxic than others, certain populations are likely to suffer higher health burdens. Demographics differed between populations covered and not covered by monitors. PMID:22889745

Estimating human exposure to perfluoroalkyl acids via solid food and drinks: Implementation and comparison of different dietary assessment methods.

PubMed

Papadopoulou, Eleni; Poothong, Somrutai; Koekkoek, Jacco; Lucattini, Luisa; Padilla-Sánchez, Juan Antonio; Haugen, Margaretha; Herzke, Dorte; Valdersnes, Stig; Maage, Amund; Cousins, Ian T; Leonards, Pim E G; Småstuen Haug, Line

2017-10-01

Diet is a major source of human exposure to hazardous environmental chemicals, including many perfluoroalkyl acids (PFAAs). Several assessment methods of dietary exposure to PFAAs have been used previously, but there is a lack of comparisons between methods. To assess human exposure to PFAAs through diet by different methods and compare the results. We studied the dietary exposure to PFAAs in 61 Norwegian adults (74% women, average age: 42 years) using three methods: i) by measuring daily PFAA intakes through a 1-day duplicate diet study (separately in solid and liquid foods), ii) by estimating intake after combining food contamination with food consumption data, as assessed by 2-day weighted food diaries and iii) by a Food Frequency Questionnaire (FFQ). We used existing food contamination data mainly from samples purchased in Norway and if not available, data from food purchased in other European countries were used. Duplicate diet samples (n=122) were analysed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to quantify 15 PFAAs (11 perfluoroalkyl carboxylates and 4 perfluoroalkyl sulfonates). Differences and correlations between measured and estimated intakes were assessed. The most abundant PFAAs in the duplicate diet samples were PFOA, PFOS and PFHxS and the median total intakes were 5.6ng/day, 11ng/day and 0.78ng/day, respectively. PFOS and PFOA concentrations were higher in solid than liquid samples. PFOS was the main contributor to the contamination in the solid samples (median concentration 14pg/g food), while it was PFOA in the liquid samples (median concentrations: 0.72pg/g food). High intakes of fats, oils, and eggs were statistically significantly related to high intakes of PFOS and PFOA from solid foods. High intake of milk and consumption of alcoholic beverages, as well as food in paper container were related to high PFOA intakes from liquid foods. PFOA intakes derived from food diary and FFQ were significantly higher than those derived from duplicate diet, but intakes of PFOS derived from food diary and FFQ were significantly lower than those derived from duplicate diet. We found a positive and statistically significant correlation between the PFOS intakes derived from duplicate diet with those using the food diary (rho=0.26, p-value=0.041), but not with the FFQ. Additionally, PFOA intakes derived by duplicate diet were significantly correlated with estimated intakes from liquid food derived from the food diary (rho=0.34, p=0.008) and estimated intakes from the FFQ (rho=0.25, p-value=0.055). We provide evidence that a food diary or a FFQ-based method can provide comparable intake estimates to PFOS and PFOA intakes derived from a duplicate diet study. These less burdensome methods are valuable and reliable tools to assess dietary exposure to PFASs in human studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of commuters' daily exposure to flash flooding over the roads of the Gard region, France

NASA Astrophysics Data System (ADS)

Debionne, Samuel; Ruin, Isabelle; Shabou, Saif; Lutoff, Céline; Creutin, Jean-Dominique

2016-10-01

Flash floods are responsible for a majority of natural disaster fatalities in the USA and Europe and most of them are vehicle-related. If human exposure to flood is generally assessed through the number of inhabitants per buildings located in flood prone zone, it is clear that this number varies dramatically throughout the day as people move from place to place to follow their daily program of activities. Knowing the number of motorists exposed on flood prone road sections or the factors determining their exposure would allow providing a more realistic evaluation of the degree of exposure. In order to bridge this gap and provide emergency managers with methods to assess the risk level for motorists, this paper describes two methods, a simple rough-and-ready estimate and a traffic attribution method, and applies both of them on datasets of the Gard département, an administrative region of Southern France with about 700 000 inhabitants over 5875 km2. The first method to obtain an overall estimation of motorists flood exposure is to combine (i) the regional density of roads and rivers to derive a count of potential road cuts and (ii) the average daily kilometers driven by commuters of the study area to derive the number of people passing these potential cuts. If useful as a first approximation, this method fails to capture the spatial heterogeneities introduced by the geometry of river and road networks and the distribution of commuters' itineraries. To address this point, this paper (i) uses a pre-established detailed identification of road cuts (Naulin et al., 2013) and (ii) applies a well-known traffic attribution method to existing and freely available census datasets. Both methods indicate that commuters' exposure is much larger than the number of commuters itself, illustrating the risk amplification effect of mobility. Comparing the results from both methods shows that (i) the road network geometry plays a significant role in reducing the risk of river-road dangerous intersections and (ii) not all commuters are equally exposed. Evidently commuters who have longer routes are more exposed, but residents of rural municipalities as well as professionals with highly qualified jobs are also more exposed. Finally, these exposure assessment methods applied to the Gard area allows locating road sections where commuters' exposure to flood is high. It also sets the first step toward the implementation of a modeling platform able to combine the estimation of daily travel patterns exposure and behavioral response of motorists to road flooding, a critical input for emergency services and services in charge of the management of road networks in flash flood prone areas.

Quantitative risk assessment of durable glass fibers.

PubMed

Fayerweather, William E; Eastes, Walter; Cereghini, Francesco; Hadley, John G

2002-06-01

This article presents a quantitative risk assessment for the theoretical lifetime cancer risk from the manufacture and use of relatively durable synthetic glass fibers. More specifically, we estimate levels of exposure to respirable fibers or fiberlike structures of E-glass and C-glass that, assuming a working lifetime exposure, pose a theoretical lifetime cancer risk of not more than 1 per 100,000. For comparability with other risk assessments we define these levels as nonsignificant exposures. Nonsignificant exposure levels are estimated from (a) the Institute of Occupational Medicine (IOM) chronic rat inhalation bioassay of durable E-glass microfibers, and (b) the Research Consulting Company (RCC) chronic inhalation bioassay of durable refractory ceramic fibers (RCF). Best estimates of nonsignificant E-glass exposure exceed 0.05-0.13 fibers (or shards) per cubic centimeter (cm3) when calculated from the multistage nonthreshold model. Best estimates of nonsignificant C-glass exposure exceed 0.27-0.6 fibers/cm3. Estimates of nonsignificant exposure increase markedly for E- and C-glass when non-linear models are applied and rapidly exceed 1 fiber/cm3. Controlling durable fiber exposures to an 8-h time-weighted average of 0.05 fibers/cm3 will assure that the additional theoretical lifetime risk from working lifetime exposures to these durable fibers or shards is kept below the 1 per 100,000 level. Measured airborne exposures to respirable, durable glass fibers (or shards) in glass fiber manufacturing and fabrication operations were compared with the nonsignificant exposure estimates described. Sampling results for B-sized respirable E-glass fibers at facilities that manufacture or fabricate small-diameter continuous-filament products, from those that manufacture respirable E-glass shards from PERG (process to efficiently recycle glass), from milled fiber operations, and from respirable C-glass shards from Flakeglass operations indicate very low median exposures of 0, 0.0002, 0.007, 0.008, and 0.0025 fibers (or shards)/cm3, respectively using the NIOSH 7400 Method ("B" rules). Durable glass fiber exposures for various applications must be well characterized to ensure that they are kept below nonsignificant levels (e.g., 0.05 fibers/cm3) as defined in this risk assessment.

Improving estimates of air pollution exposure through ubiquitous sensing technologies.

PubMed

de Nazelle, Audrey; Seto, Edmund; Donaire-Gonzalez, David; Mendez, Michelle; Matamala, Jaume; Nieuwenhuijsen, Mark J; Jerrett, Michael

2013-05-01

Traditional methods of exposure assessment in epidemiological studies often fail to integrate important information on activity patterns, which may lead to bias, loss of statistical power, or both in health effects estimates. Novel sensing technologies integrated with mobile phones offer potential to reduce exposure measurement error. We sought to demonstrate the usability and relevance of the CalFit smartphone technology to track person-level time, geographic location, and physical activity patterns for improved air pollution exposure assessment. We deployed CalFit-equipped smartphones in a free-living population of 36 subjects in Barcelona, Spain. Information obtained on physical activity and geographic location was linked to space-time air pollution mapping. We found that information from CalFit could substantially alter exposure estimates. For instance, on average travel activities accounted for 6% of people's time and 24% of their daily inhaled NO2. Due to the large number of mobile phone users, this technology potentially provides an unobtrusive means of enhancing epidemiologic exposure data at low cost. Copyright © 2013 Elsevier Ltd. All rights reserved.

Estimating the attack rate of pregnancy-associated listeriosis during a large outbreak.

PubMed

Imanishi, Maho; Routh, Janell A; Klaber, Marigny; Gu, Weidong; Vanselow, Michelle S; Jackson, Kelly A; Sullivan-Chang, Loretta; Heinrichs, Gretchen; Jain, Neena; Albanese, Bernadette; Callaghan, William M; Mahon, Barbara E; Silk, Benjamin J

2015-01-01

In 2011, a multistate outbreak of listeriosis linked to contaminated cantaloupes raised concerns that many pregnant women might have been exposed to Listeria monocytogenes. Listeriosis during pregnancy can cause fetal death, premature delivery, and neonatal sepsis and meningitis. Little information is available to guide healthcare providers who care for asymptomatic pregnant women with suspected L. monocytogenes exposure. We tracked pregnancy-associated listeriosis cases using reportable diseases surveillance and enhanced surveillance for fetal death using vital records and inpatient fetal deaths data in Colorado. We surveyed 1,060 pregnant women about symptoms and exposures. We developed three methods to estimate how many pregnant women in Colorado ate the implicated cantaloupes, and we calculated attack rates. One laboratory-confirmed case of listeriosis was associated with pregnancy. The fetal death rate did not increase significantly compared to preoutbreak periods. Approximately 6,500-12,000 pregnant women in Colorado might have eaten the contaminated cantaloupes, an attack rate of ~1 per 10,000 exposed pregnant women. Despite many exposures, the risk of pregnancy-associated listeriosis was low. Our methods for estimating attack rates may help during future outbreaks and product recalls. Our findings offer relevant considerations for management of asymptomatic pregnant women with possible L. monocytogenes exposure.

Potential-scour assessments and estimates of scour depth using different techniques at selected bridge sites in Missouri

USGS Publications Warehouse

Huizinga, Richard J.; Rydlund, Jr., Paul H.

2004-01-01

The evaluation of scour at bridges throughout the state of Missouri has been ongoing since 1991 in a cooperative effort by the U.S. Geological Survey and Missouri Department of Transportation. A variety of assessment methods have been used to identify bridges susceptible to scour and to estimate scour depths. A potential-scour assessment (Level 1) was used at 3,082 bridges to identify bridges that might be susceptible to scour. A rapid estimation method (Level 1+) was used to estimate contraction, pier, and abutment scour depths at 1,396 bridge sites to identify bridges that might be scour critical. A detailed hydraulic assessment (Level 2) was used to compute contraction, pier, and abutment scour depths at 398 bridges to determine which bridges are scour critical and would require further monitoring or application of scour countermeasures. The rapid estimation method (Level 1+) was designed to be a conservative estimator of scour depths compared to depths computed by a detailed hydraulic assessment (Level 2). Detailed hydraulic assessments were performed at 316 bridges that also had received a rapid estimation assessment, providing a broad data base to compare the two scour assessment methods. The scour depths computed by each of the two methods were compared for bridges that had similar discharges. For Missouri, the rapid estimation method (Level 1+) did not provide a reasonable conservative estimate of the detailed hydraulic assessment (Level 2) scour depths for contraction scour, but the discrepancy was the result of using different values for variables that were common to both of the assessment methods. The rapid estimation method (Level 1+) was a reasonable conservative estimator of the detailed hydraulic assessment (Level 2) scour depths for pier scour if the pier width is used for piers without footing exposure and the footing width is used for piers with footing exposure. Detailed hydraulic assessment (Level 2) scour depths were conservatively estimated by the rapid estimation method (Level 1+) for abutment scour, but there was substantial variability in the estimates and several substantial underestimations.

Fully automatic bone age estimation from left hand MR images.

PubMed

Stern, Darko; Ebner, Thomas; Bischof, Horst; Grassegger, Sabine; Ehammer, Thomas; Urschler, Martin

2014-01-01

There has recently been an increased demand in bone age estimation (BAE) of living individuals and human remains in legal medicine applications. A severe drawback of established BAE techniques based on X-ray images is radiation exposure, since many countries prohibit scanning involving ionizing radiation without diagnostic reasons. We propose a completely automated method for BAE based on volumetric hand MRI images. On our database of 56 male caucasian subjects between 13 and 19 years, we are able to estimate the subjects age with a mean difference of 0.85 ± 0.58 years compared to the chronological age, which is in line with radiologist results using established radiographic methods. We see this work as a promising first step towards a novel MRI based bone age estimation system, with the key benefits of lacking exposure to ionizing radiation and higher accuracy due to exploitation of volumetric data.

Estimating Adolescent Risk for Hearing Loss Based on Data From a Large School-Based Survey

PubMed Central

Verschuure, Hans; van der Ploeg, Catharina P. B.; Brug, Johannes; Raat, Hein

2010-01-01

Objectives. We estimated whether and to what extent a group of adolescents were at risk of developing permanent hearing loss as a result of voluntary exposure to high-volume music, and we assessed whether such exposure was associated with hearing-related symptoms. Methods. In 2007, 1512 adolescents (aged 12–19 years) in Dutch secondary schools completed questionnaires about their music-listening behavior and whether they experienced hearing-related symptoms after listening to high-volume music. We used their self-reported data in conjunction with published average sound levels of music players, discotheques, and pop concerts to estimate their noise exposure, and we compared that exposure to our own “loosened” (i.e., less strict) version of current European safety standards for occupational noise exposure. Results. About half of the adolescents exceeded safety standards for occupational noise exposure. About one third of the respondents exceeded safety standards solely as a result of listening to MP3 players. Hearing symptoms that occurred after using an MP3 player or going to a discotheque were associated with exposure to high-volume music. Conclusions. Adolescents often exceeded current occupational safety standards for noise exposure, highlighting the need for specific safety standards for leisure-time noise exposure. PMID:20395587

Efficiency of International Classification of Diseases, Ninth Revision, Billing Code Searches to Identify Emergency Department Visits for Blood or Body Fluid Exposures through a Statewide Multicenter Database

PubMed Central

Rosen, Lisa M.; Liu, Tao; Merchant, Roland C.

2016-01-01

BACKGROUND Blood and body fluid exposures are frequently evaluated in emergency departments (EDs). However, efficient and effective methods for estimating their incidence are not yet established. OBJECTIVE Evaluate the efficiency and accuracy of estimating statewide ED visits for blood or body fluid exposures using International Classification of Diseases, Ninth Revision (ICD-9), code searches. DESIGN Secondary analysis of a database of ED visits for blood or body fluid exposure. SETTING EDs of 11 civilian hospitals throughout Rhode Island from January 1, 1995, through June 30, 2001. PATIENTS Patients presenting to the ED for possible blood or body fluid exposure were included, as determined by prespecified ICD-9 codes. METHODS Positive predictive values (PPVs) were estimated to determine the ability of 10 ICD-9 codes to distinguish ED visits for blood or body fluid exposure from ED visits that were not for blood or body fluid exposure. Recursive partitioning was used to identify an optimal subset of ICD-9 codes for this purpose. Random-effects logistic regression modeling was used to examine variations in ICD-9 coding practices and styles across hospitals. Cluster analysis was used to assess whether the choice of ICD-9 codes was similar across hospitals. RESULTS The PPV for the original 10 ICD-9 codes was 74.4% (95% confidence interval [CI], 73.2%–75.7%), whereas the recursive partitioning analysis identified a subset of 5 ICD-9 codes with a PPV of 89.9% (95% CI, 88.9%–90.8%) and a misclassification rate of 10.1%. The ability, efficiency, and use of the ICD-9 codes to distinguish types of ED visits varied across hospitals. CONCLUSIONS Although an accurate subset of ICD-9 codes could be identified, variations across hospitals related to hospital coding style, efficiency, and accuracy greatly affected estimates of the number of ED visits for blood or body fluid exposure. PMID:22561713

A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

NASA Astrophysics Data System (ADS)

Xu, Jinghai; An, Jiwen; Nie, Gaozong

2016-04-01

Improving earthquake disaster loss estimation speed and accuracy is one of the key factors in effective earthquake response and rescue. The presentation of exposure data by applying a dasymetric map approach has good potential for addressing this issue. With the support of 30'' × 30'' areal exposure data (population and building data in China), this paper presents a new earthquake disaster loss estimation method for emergency response situations. This method has two phases: a pre-earthquake phase and a co-earthquake phase. In the pre-earthquake phase, we pre-calculate the earthquake loss related to different seismic intensities and store them in a 30'' × 30'' grid format, which has several stages: determining the earthquake loss calculation factor, gridding damage probability matrices, calculating building damage and calculating human losses. Then, in the co-earthquake phase, there are two stages of estimating loss: generating a theoretical isoseismal map to depict the spatial distribution of the seismic intensity field; then, using the seismic intensity field to extract statistics of losses from the pre-calculated estimation data. Thus, the final loss estimation results are obtained. The method is validated by four actual earthquakes that occurred in China. The method not only significantly improves the speed and accuracy of loss estimation but also provides the spatial distribution of the losses, which will be effective in aiding earthquake emergency response and rescue. Additionally, related pre-calculated earthquake loss estimation data in China could serve to provide disaster risk analysis before earthquakes occur. Currently, the pre-calculated loss estimation data and the two-phase estimation method are used by the China Earthquake Administration.

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

PubMed

Friesen, Melissa C; Shortreed, Susan M; Wheeler, David C; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S; Baris, Dalsu; Karagas, Margaret R; Schwenn, Molly; Johnson, Alison; Armenti, Karla R; Silverman, Debra T; Yu, Kai

2015-05-01

Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

First tier modeling of consumer dermal exposure to substances in consumer articles under REACH: a quantitative evaluation of the ECETOC TRA for consumers tool.

PubMed

Delmaar, J E; Bokkers, B G H; ter Burg, W; van Engelen, J G M

2013-02-01

The demonstration of safe use of chemicals in consumer products, as required under REACH, is proposed to follow a tiered process. In the first tier, simple conservative methods and assumptions should be made to quickly verify whether risks for a particular use are expected. The ECETOC TRA Consumer Exposure Tool was developed to assist in first tier risk assessments for substances in consumer products. The ECETOC TRA is not a prioritization tool, but is meant as a first screening. Therefore, the exposure assessment needs to cover all products/articles in a specific category. For the assessment of the dermal exposure for substances in articles, ECETOC TRA uses the concept of a 'contact layer', a hypothetical layer that limits the exposure to a substance contained in the product. For each product/article category, ECETOC TRA proposes default values for the thickness of this contact layer. As relevant experimental exposure data is currently lacking, default values are based on expert judgment alone. In this paper it is verified whether this concept meets the requirement of being a conservative exposure evaluation method. This is done by confronting the ECETOC TRA expert judgment based predictions with a mechanistic emission model, based on the well established theory of diffusion of substances in materials. Diffusion models have been applied and tested in many applications of emission modeling. Experimentally determined input data for a number of material and substance combinations are available. The estimated emissions provide information on the range of emissions that could occur in reality. First tier tools such as ECETOC TRA tool are required to cover all products/articles in a category and to provide estimates that are at least as high as is expected on the basis of current scientific knowledge. Since this was not the case, it is concluded that the ECETOC TRA does not provide a proper conservative estimation method for the dermal exposure to articles. An alternative method was proposed. Copyright © 2012 Elsevier Inc. All rights reserved.

Methods for Quantification of Exposure to Cigarette Smoking and Environmental Tobacco Smoke: Focus on Developmental Toxicology

PubMed Central

Florescu, Ana; Ferrence, Roberta; Einarson, Tom; Selby, Peter; Soldin, Offie; Koren, Gideon

2013-01-01

Active and passive smoking have been associated with an array of adverse effects on health. The development of valid and accurate scales of measurement for exposures associated with health risks constitutes an active area of research. Tobacco smoke exposure still lacks an ideal method of measurement. A valid estimation of the risks associated with tobacco exposure depends on accurate measurement. However, some groups of people are more reluctant than others to disclose their smoking status and exposure to tobacco. This is particularly true for pregnant women and parents of young children, whose smoking is often regarded as socially unacceptable. For others, recall of tobacco exposure may also prove difficult. Because relying on self-report and the various biases it introduces may lead to inaccurate measures of nicotine exposure, more objective solutions have been suggested. Biomarkers constitute the most commonly used objective method of ascertaining nicotine exposure. Of those available, cotinine has gained supremacy as the biomarker of choice. Traditionally, cotinine has been measured in blood, saliva, and urine. Cotinine collection and analysis from these sources has posed some difficulties, which have motivated the search for a more consistent and reliable source of this biomarker. Hair analysis is a novel, noninvasive technique used to detect the presence of drugs and metabolites in the hair shaft. Because cotinine accumulates in hair during hair growth, it is a unique measure of long-term, cumulative exposure to tobacco smoke. Although hair analysis of cotinine holds great promise, a detailed evaluation of its potential as a biomarker of nicotine exposure, is needed. No studies have been published that address this issue. Because the levels of cotinine in the body are dependent on nicotine metabolism, which in turn is affected by factors such as age and pregnancy, the characterization of hair cotinine should be population specific. This review aims at defining the sensitivity, specificity, and clinical utilization of different methods used to estimate exposure to cigarette smoking and environmental tobacco smoke. PMID:19125149

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

Shin, Hyeong -Moo; Ernstoff, Alexi; Arnot, Jon A.

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate dailymore » intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.« less

Evaluation of Quantitative Exposure Assessment Method for Nanomaterials in Mixed Dust Environments: Application in Tire Manufacturing Facilities.

PubMed

Kreider, Marisa L; Cyrs, William D; Tosiano, Melissa A; Panko, Julie M

2015-11-01

Current recommendations for nanomaterial-specific exposure assessment require adaptation in order to be applied to complicated manufacturing settings, where a variety of particle types may contribute to the potential exposure. The purpose of this work was to evaluate a method that would allow for exposure assessment of nanostructured materials by chemical composition and size in a mixed dust setting, using carbon black (CB) and amorphous silica (AS) from tire manufacturing as an example. This method combined air sampling with a low pressure cascade impactor with analysis of elemental composition by size to quantitatively assess potential exposures in the workplace. This method was first pilot-tested in one tire manufacturing facility; air samples were collected with a Dekati Low Pressure Impactor (DLPI) during mixing where either CB or AS were used as the primary filler. Air samples were analyzed via scanning transmission electron microscopy (STEM) coupled with energy dispersive spectroscopy (EDS) to identify what fraction of particles were CB, AS, or 'other'. From this pilot study, it was determined that ~95% of all nanoscale particles were identified as CB or AS. Subsequent samples were collected with the Dekati Electrical Low Pressure Impactor (ELPI) at two tire manufacturing facilities and analyzed using the same methodology to quantify exposure to these materials. This analysis confirmed that CB and AS were the predominant nanoscale particle types in the mixing area at both facilities. Air concentrations of CB and AS ranged from ~8900 to 77600 and 400 to 22200 particles cm(-3), respectively. This method offers the potential to provide quantitative estimates of worker exposure to nanoparticles of specific materials in a mixed dust environment. With pending development of occupational exposure limits for nanomaterials, this methodology will allow occupational health and safety practitioners to estimate worker exposures to specific materials, even in scenarios where many particle types are present. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Supraorbital Keyhole Craniotomy for Basilar Artery Aneurysms: Accounting for the "Cliff" Effect.

PubMed

Stamates, Melissa M; Wong, Andrew K; Bhansali, Anita; Wong, Ricky H

2017-04-01

Treatment of basilar artery aneurysms is challenging. While endovascular techniques have dominated, there still remain circumstances where open surgical clipping is required or preferred. Minimally invasive "keyhole" approaches are being used more frequently to provide the durability of surgical clipping with a lower morbidity profile; however, careful patient selection is required. The supraorbital "keyhole" approach has been described for the treatment of basilar artery aneurysms, but careful assessment of the basilar exposure is necessary to ensure proper visualization of the aneurysm and ability to obtain proximal vascular control. Various methods of estimating the basilar artery exposure in this approach have been described, including the anterior skull base line and the posterior clinoid line, but both are unreliable and inaccurate. To propose a new method, the orbital roof-dorsum line, to simply and accurately predict the basilar artery exposure. CT angiograms for 20 consecutive unique patients were analyzed to obtain the anterior skull base line, posterior clinoid line, and the orbital roof-dorsum line. CT angiograms were then loaded onto a Stealth neuronavigation system (Medtronic, Minneapolis, Minnesota) to obtain "true" visualization lengths. A case illustration is presented. Pairwise comparison tests demonstrated that both the anterior skull base and the posterior clinoid estimation lines differed significantly from the "true"  value ( P < .0001). Our orbital roof-dorsum estimation provided results that accurately predicted the "true" value ( P = .71). The orbital roof-dorsum line provides a simple and reliable method of estimating basilar artery exposure and should be used whenever considering patients for surgical clipping by this approach. Copyright © 2017 by the Congress of Neurological Surgeons

Bladder cancer incidence among workers exposed to o-toluidine, aniline and nitrobenzene at a rubber chemical manufacturing plant

PubMed Central

Carreón, Tania; Hein, Misty J; Hanley, Kevin W; Viet, Susan M; Ruder, Avima M

2015-01-01

Background An earlier investigation found increased bladder cancer incidence among workers at a rubber chemical manufacturing plant that used o-toluidine, aniline and nitrobenzene. The cohort was expanded to include additional workers (n=1875) and updated through 2007 to assess bladder cancer with improved exposure characterisation. Methods Work histories were updated and exposure categories and ranks were developed for o-toluidine, aniline and nitrobenzene combined. Incident cancers were identified by linkage to six state cancer registries. Residency in time-dependent cancer registry catchment areas was determined. SIR and standardised rate ratios for bladder cancer were calculated by exposure category and cumulative rank quartiles for different lag periods. Cox regression was used to model bladder cancer incidence with estimated cumulative rank, adjusting for confounders. Indirect methods were used to control for smoking. Results Excess bladder cancer was observed compared to the New York State population (SIR=2.87, 95% CI 2.02 to 3.96), with higher elevations among workers definitely exposed (moderate/high) (SIR=3.90, 95% CI 2.57 to 5.68), and in the highest cumulative rank quartile (SIR=6.13, 95% CI 2.80 to 11.6, 10-year lag). Bladder cancer rates increased significantly with estimated cumulative rank (10-year lag). Smoking only accounted for an estimated 8% elevation in bladder cancer incidence. Conclusions Bladder cancer incidence remains elevated in this cohort and significantly associated with estimated cumulative exposure. Results are consistent with earlier findings in this and other cohorts. Despite other concurrent chemical exposures, we consider o-toluidine most likely responsible for the bladder cancer incidence elevation and recommend a re-examination of occupational exposure limits. PMID:24368697

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

Arsenic in groundwater in Bangladesh: A geostatistical and epidemiological framework for evaluating health effects and potential remedies

NASA Astrophysics Data System (ADS)

Yu, Winston H.; Harvey, Charles M.; Harvey, Charles F.

2003-06-01

This paper examines the health crisis in Bangladesh due to dissolved arsenic in groundwater. First, we use geostatistical methods to construct a map of arsenic concentrations that divides Bangladesh into regions and estimate vertical concentration trends in these regions. Then, we use census data to estimate exposure distributions in the regions; we use epidemiological data from West Bengal and Taiwan to estimate dose response functions for arsenicosis and arsenic-induced cancers; and we combine the regional exposure distributions and the dose response models to estimate the health effects of groundwater arsenic in Bangladesh. We predict that long-term exposure to present arsenic concentrations will result in approximately 1,200,000 cases of hyperpigmentation, 600,000 cases of keratosis, 125,000 cases of skin cancer, and 3000 fatalities per year from internal cancers. Although these estimates are very uncertain, the method provides a framework for incorporating better data as it becomes available. Moreover, we examine the remedy of drilling deeper wells in selected regions of Bangladesh. By replacing 31% of the wells in the country with deeper wells the health effects of drinking groundwater arsenic could be reduced by approximately 70% provided that arsenic concentrations in deep wells remain relatively low.

Methodologies for the quantitative estimation of toxicant dose to cigarette smokers using physical, chemical and bioanalytical data.

PubMed

St Charles, Frank Kelley; McAughey, John; Shepperd, Christopher J

2013-06-01

Methodologies have been developed, described and demonstrated that convert mouth exposure estimates of cigarette smoke constituents to dose by accounting for smoke spilled from the mouth prior to inhalation (mouth-spill (MS)) and the respiratory retention (RR) during the inhalation cycle. The methodologies are applicable to just about any chemical compound in cigarette smoke that can be measured analytically and can be used with ambulatory population studies. Conversion of exposure to dose improves the relevancy for risk assessment paradigms. Except for urinary nicotine plus metabolites, biomarkers generally do not provide quantitative exposure or dose estimates. In addition, many smoke constituents have no reliable biomarkers. We describe methods to estimate the RR of chemical compounds in smoke based on their vapor pressure (VP) and to estimate the MS for a given subject. Data from two clinical studies were used to demonstrate dose estimation for 13 compounds, of which only 3 have urinary biomarkers. Compounds with VP > 10(-5) Pa generally have RRs of 88% or greater, which do not vary appreciably with inhalation volume (IV). Compounds with VP < 10(-7) Pa generally have RRs dependent on IV and lung exposure time. For MS, mean subject values from both studies were slightly greater than 30%. For constituents with urinary biomarkers, correlations with the calculated dose were significantly improved over correlations with mouth exposure. Of toxicological importance is that the dose correlations provide an estimate of the metabolic conversion of a constituent to its respective biomarker.

Use of direct versus indirect preparation data for assessing risk associated with airborne exposures at asbestos-contaminated sites.

PubMed

Goldade, Mary Patricia; O'Brien, Wendy Pott

2014-01-01

At asbestos-contaminated sites, exposure assessment requires measurement of airborne asbestos concentrations; however, the choice of preparation steps employed in the analysis has been debated vigorously among members of the asbestos exposure and risk assessment communities for many years. This study finds that the choice of preparation technique used in estimating airborne amphibole asbestos exposures for risk assessment is generally not a significant source of uncertainty. Conventionally, the indirect preparation method has been less preferred by some because it is purported to result in false elevations in airborne asbestos concentrations, when compared to direct analysis of air filters. However, airborne asbestos sampling in non-occupational settings is challenging because non-asbestos particles can interfere with the asbestos measurements, sometimes necessitating analysis via indirect preparation. To evaluate whether exposure concentrations derived from direct versus indirect preparation techniques differed significantly, paired measurements of airborne Libby-type amphibole, prepared using both techniques, were compared. For the evaluation, 31 paired direct and indirect preparations originating from the same air filters were analyzed for Libby-type amphibole using transmission electron microscopy. On average, the total Libby-type amphibole airborne exposure concentration was 3.3 times higher for indirect preparation analysis than for its paired direct preparation analysis (standard deviation = 4.1), a difference which is not statistically significant (p = 0.12, two-tailed, Wilcoxon signed rank test). The results suggest that the magnitude of the difference may be larger for shorter particles. Overall, neither preparation technique (direct or indirect) preferentially generates more precise and unbiased data for airborne Libby-type amphibole concentration estimates. The indirect preparation method is reasonable for estimating Libby-type amphibole exposure and may be necessary given the challenges of sampling in environmental settings. Relative to the larger context of uncertainties inherent in the risk assessment process, uncertainties associated with the use of airborne Libby-type amphibole exposure measurements derived from indirect preparation analysis are low. Use of exposure measurements generated by either direct or indirect preparation analyses is reasonable to estimate Libby-type Amphibole exposures in a risk assessment.

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

U.S. dietary exposures to heterocyclic amines.

PubMed

Bogen, K T; Keating, G A

2001-01-01

Heterocyclic amines (HAs) formed in fried, broiled or grilled meats are potent mutagens that increase rates of colon, mammary, prostate and other cancers in bioassay rodents. Studies of how human dietary HA exposures may affect cancer risks have so far relied on fairly crudely defined HA-exposure categories. Recently, an integrated, quantitative approach to HA-exposure assessment (HAEA) was developed to estimate compound-specific intakes for particular individuals based on corresponding HA-concentration estimates that reflect their meat-type, intake-rate, cooking-method and meat-doneness preferences. This method was applied in the present study to U.S. national Continuing Survey of Food Intakes by Individuals (CSFII) data on meats consumed and cooking methods used by >25,000 people, after adjusting for underreported energy intake and conditional on meat-doneness preferences estimated from additional survey data. The U.S. population average lifetime time-weighted average of total HAs consumed was estimated to be approximately 9 ng/kg/day, with 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) estimated to comprise about two thirds of this intake. Pan-fried meats were the largest source of HA in the diet and chicken the largest source of HAs among different meat types. Estimated total HA intakes by male vs. female children were generally similar, with those by (0- to 15-year-old) children approximately 25% greater than those by (16+-year-old) adults. Race-, age- and sex-specific mean HA intakes were estimated to be greatest for African American males, who were estimated to consume approximately 2- and approximately 3-fold more PhIP than white males at ages <16 and 30+ years, respectively, after considering a relatively greater preference for more well-done items among African Americans based on national survey data. This difference in PhIP intakes may at least partly explain why prostate cancer (PC) kills approximately 2-fold more African American than white men, in view of experimental data indicating that PhIP mutates prostate DNA and causes prostate tumors in rats.

In Silico Estimation of Skin Concentration Following the Dermal Exposure to Chemicals.

PubMed

Hatanaka, Tomomi; Yoshida, Shun; Kadhum, Wesam R; Todo, Hiroaki; Sugibayashi, Kenji

2015-12-01

To develop an in silico method based on Fick's law of diffusion to estimate the skin concentration following dermal exposure to chemicals with a wide range of lipophilicity. Permeation experiments of various chemicals were performed through rat and porcine skin. Permeation parameters, namely, permeability coefficient and partition coefficient, were obtained by the fitting of data to two-layered and one-layered diffusion models for whole and stripped skin. The mean skin concentration of chemicals during steady-state permeation was calculated using the permeation parameters and compared with the observed values. All permeation profiles could be described by the diffusion models. The estimated skin concentrations of chemicals using permeation parameters were close to the observed levels and most data fell within the 95% confidence interval for complete prediction. The permeability coefficient and partition coefficient for stripped skin were almost constant, being independent of the permeant's lipophilicity. Skin concentration following dermal exposure to various chemicals can be accurately estimated based on Fick's law of diffusion. This method should become a useful tool to assess the efficacy of topically applied drugs and cosmetic ingredients, as well as the risk of chemicals likely to cause skin disorders and diseases.

An Integrated Web-Based Assessment Tool for Assessing Pesticide Exposure and Risks

EPA Science Inventory

Background/Question/Methods We have created an integrated web-based tool designed to estimate exposure doses and ecological risks under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Endangered Species Act. This involved combining a number of disparat...

Advancing Models and Data for Characterizing Exposures to Chemicals in Consumer Products

EPA Science Inventory

EPA’s Office of Research and Development (ORD) is leading several efforts to develop data and methods for estimating population chemical exposures related to the use of consumer products. New curated chemical, ingredient, and product use information are being collected fro...

Comparison of hurricane exposure methods and associations with county fetal death rates, adjusting for environmental quality

EPA Science Inventory

Adverse effects of hurricanes are increasing as coastal populations grow and events become more severe. Hurricane exposure during pregnancy can influence fetal death rates through mechanisms related to healthcare, infrastructure disruption, nutrition, and injury. Estimation of hu...

Negative control exposure studies in the presence of measurement error: implications for attempted effect estimate calibration

PubMed Central

Sanderson, Eleanor; Macdonald-Wallis, Corrie; Davey Smith, George

2018-01-01

Abstract Background Negative control exposure studies are increasingly being used in epidemiological studies to strengthen causal inference regarding an exposure-outcome association when unobserved confounding is thought to be present. Negative control exposure studies contrast the magnitude of association of the negative control, which has no causal effect on the outcome but is associated with the unmeasured confounders in the same way as the exposure, with the magnitude of the association of the exposure with the outcome. A markedly larger effect of the exposure on the outcome than the negative control on the outcome strengthens inference that the exposure has a causal effect on the outcome. Methods We investigate the effect of measurement error in the exposure and negative control variables on the results obtained from a negative control exposure study. We do this in models with continuous and binary exposure and negative control variables using analysis of the bias of the estimated coefficients and Monte Carlo simulations. Results Our results show that measurement error in either the exposure or negative control variables can bias the estimated results from the negative control exposure study. Conclusions Measurement error is common in the variables used in epidemiological studies; these results show that negative control exposure studies cannot be used to precisely determine the size of the effect of the exposure variable, or adequately adjust for unobserved confounding; however, they can be used as part of a body of evidence to aid inference as to whether a causal effect of the exposure on the outcome is present. PMID:29088358

Measuring visual exposure to smoking behaviours: a viewshed analysis of smoking at outdoor bars and cafés across a capital city's downtown area.

PubMed

Pearson, Amber L; Nutsford, Daniel; Thomson, George

2014-04-06

The influence of visual exposure to health-related behaviours, such as smoking, is increasingly acknowledged in the public health literature. Social contagion or normalisation is thought to operate through the visibility of those behaviours. There has been a lack of systematic and comprehensive approaches to quantifying visual exposure to these behaviours over a relatively large geographic area. We describe the novel application of a geographic tool, viewshed analysis, to estimate visual exposure to smoking outside bars/cafés across a downtown area. Smoking was observed for different times and days of the week at 14 outdoor areas of bars/cafés throughout downtown Wellington, New Zealand. We used these data to extrapolate to other bars/cafés with outdoor seating. We then conducted viewshed analyses to estimate visual exposure to smoking at bars/cafés for all public outdoor spaces. We observed a smoking point prevalence of 16%. Visibility analyses indicated that estimated visible smoking was highest in the evenings (7-8 pm), where the average values across Wednesday and Friday ranged from zero up to 92 visible smokers (mean=1.44). Estimated visible smoking at midday ranged from zero to 13 (mean=0.27). Values were also higher at the end of the week compared with midweek in the evening. Maps indicate that streets with high levels of retail shops and hospitality areas had high values of estimated visible smokers, particularly in the evening where numbers were consistently above 50. This paper highlights a useful method for measuring the extent of visual exposure to smoking behaviours across relatively large areas using a geospatial approach. Applying this method in other locations would require consideration of place-specific characteristics which impact on visibility and could be improved through more sophisticated extrapolation of observational data across the study area. The findings of this and similar research could ultimately support the expansion of smokefree public spaces.

Extending the Distributed Lag Model framework to handle chemical mixtures.

PubMed

Bello, Ghalib A; Arora, Manish; Austin, Christine; Horton, Megan K; Wright, Robert O; Gennings, Chris

2017-07-01

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessing and reporting uncertainties in dietary exposure analysis: Mapping of uncertainties in a tiered approach.

PubMed

Kettler, Susanne; Kennedy, Marc; McNamara, Cronan; Oberdörfer, Regina; O'Mahony, Cian; Schnabel, Jürgen; Smith, Benjamin; Sprong, Corinne; Faludi, Roland; Tennant, David

2015-08-01

Uncertainty analysis is an important component of dietary exposure assessments in order to understand correctly the strength and limits of its results. Often, standard screening procedures are applied in a first step which results in conservative estimates. If through those screening procedures a potential exceedance of health-based guidance values is indicated, within the tiered approach more refined models are applied. However, the sources and types of uncertainties in deterministic and probabilistic models can vary or differ. A key objective of this work has been the mapping of different sources and types of uncertainties to better understand how to best use uncertainty analysis to generate more realistic comprehension of dietary exposure. In dietary exposure assessments, uncertainties can be introduced by knowledge gaps about the exposure scenario, parameter and the model itself. With this mapping, general and model-independent uncertainties have been identified and described, as well as those which can be introduced and influenced by the specific model during the tiered approach. This analysis identifies that there are general uncertainties common to point estimates (screening or deterministic methods) and probabilistic exposure assessment methods. To provide further clarity, general sources of uncertainty affecting many dietary exposure assessments should be separated from model-specific uncertainties. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Reduced exposure evaluation of an Electrically Heated Cigarette Smoking System. Part 8: Nicotine bridging--estimating smoke constituent exposure by their relationships to both nicotine levels in mainstream cigarette smoke and in smokers.

PubMed

Urban, H-Jörg; Tricker, Anthony R; Leyden, Donald E; Forte, Natasa; Zenzen, Volker; Feuersenger, Astrid; Assink, Mareike; Kallischnigg, Gerd; Schorp, Matthias K

2012-11-01

A modeling approach termed 'nicotine bridging' is presented to estimate exposure to mainstream smoke constituents. The method is based on: (1) determination of harmful and potentially harmful constituents (HPHC) and in vitro toxicity parameter-to-nicotine regressions obtained using multiple machine-smoking protocols, (2) nicotine uptake distributions determined from 24-h excretion of nicotine metabolites in a clinical study, and (3) modeled HPHC uptake distributions using steps 1 and 2. An example of 'nicotine bridging' is provided, using a subset of the data reported in Part 2 of this supplement (Zenzen et al., 2012) for two conventional lit-end cigarettes (CC) and the Electrically Heated Cigarette Smoking System (EHCSS) series-K6 cigarette. The bridging method provides justified extrapolations of HPHC exposure distributions that cannot be obtained for smoke constituents due to the lack of specific biomarkers of exposure to cigarette smoke constituents in clinical evaluations. Using this modeling approach, exposure reduction is evident when the HPHC exposure distribution curves between the MRTP and the CC users are substantially separated with little or no overlap between the distribution curves. Copyright © 2012 Elsevier Inc. All rights reserved.

The human early-life exposome (HELIX): project rationale and design.

PubMed

Vrijheid, Martine; Slama, Rémy; Robinson, Oliver; Chatzi, Leda; Coen, Muireann; van den Hazel, Peter; Thomsen, Cathrine; Wright, John; Athersuch, Toby J; Avellana, Narcis; Basagaña, Xavier; Brochot, Celine; Bucchini, Luca; Bustamante, Mariona; Carracedo, Angel; Casas, Maribel; Estivill, Xavier; Fairley, Lesley; van Gent, Diana; Gonzalez, Juan R; Granum, Berit; Gražulevičienė, Regina; Gutzkow, Kristine B; Julvez, Jordi; Keun, Hector C; Kogevinas, Manolis; McEachan, Rosemary R C; Meltzer, Helle Margrete; Sabidó, Eduard; Schwarze, Per E; Siroux, Valérie; Sunyer, Jordi; Want, Elizabeth J; Zeman, Florence; Nieuwenhuijsen, Mark J

2014-06-01

Developmental periods in early life may be particularly vulnerable to impacts of environmental exposures. Human research on this topic has generally focused on single exposure-health effect relationships. The "exposome" concept encompasses the totality of exposures from conception onward, complementing the genome. The Human Early-Life Exposome (HELIX) project is a new collaborative research project that aims to implement novel exposure assessment and biomarker methods to characterize early-life exposure to multiple environmental factors and associate these with omics biomarkers and child health outcomes, thus characterizing the "early-life exposome." Here we describe the general design of the project. In six existing birth cohort studies in Europe, HELIX will estimate prenatal and postnatal exposure to a broad range of chemical and physical exposures. Exposure models will be developed for the full cohorts totaling 32,000 mother-child pairs, and biomarkers will be measured in a subset of 1,200 mother-child pairs. Nested repeat-sampling panel studies (n = 150) will collect data on biomarker variability, use smartphones to assess mobility and physical activity, and perform personal exposure monitoring. Omics techniques will determine molecular profiles (metabolome, proteome, transcriptome, epigenome) associated with exposures. Statistical methods for multiple exposures will provide exposure-response estimates for fetal and child growth, obesity, neurodevelopment, and respiratory outcomes. A health impact assessment exercise will evaluate risks and benefits of combined exposures. HELIX is one of the first attempts to describe the early-life exposome of European populations and unravel its relation to omics markers and health in childhood. As proof of concept, it will form an important first step toward the life-course exposome.

Occupational Exposures and Lung Cancer Risk among Minnesota Taconite Mining Workers

PubMed Central

Allen, Elizabeth M; Alexander, Bruce H; MacLehose, Richard F; Nelson, Heather H; Ryan, Andrew D; Ramachandran, Gurumurthy; Mandel, Jeffrey H

2015-01-01

Objective To examine the association between employment duration, elongate mineral particle (EMP) exposure, and silica exposure and the risk of lung cancer in the taconite mining industry. Methods We conducted a nested case control study of lung cancer within a cohort of Minnesota taconite iron mining workers employed by any of the mining companies in operation in 1983. Lung cancer cases were identified by vital records and cancer registry data through 2010. Two age-matched controls were selected from risk sets of cohort members alive and lung cancer free at the time of case diagnosis. Calendar time-specific exposure estimates were made for every job and were used to estimate workers’ cumulative exposures. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. We evaluated total lung cancer risk and risk of histological subtype by total work duration and by cumulative EMP and silica exposure by quartile of the exposure distribution. Results A total of 1,706 cases and 3,381 controls were included in the analysis. After adjusting for work in hematite mining, asbestos exposure, and sex, the OR for total duration of employment was 0.99 (95% CI: 0.96–1.01). The ORs for quartile 4 versus 1 of EMP and silica exposure were 0.82 (95% CI: 0.57–1.19) and 0.97 (95% CI: 0.70–1.35) respectively. The risk of each histological subtype of lung cancer did not change with increasing exposure. Conclusions This study suggests that the estimated taconite mining exposures do not increase the risk for the development of lung cancer. PMID:25977445

PM2.5 exposure and birth outcomes: use of satellite- and monitor-based data.

PubMed

Hyder, Ayaz; Lee, Hyung Joo; Ebisu, Keita; Koutrakis, Petros; Belanger, Kathleen; Bell, Michelle Lee

2014-01-01

Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment. We used birth certificate data for births in Connecticut and Massachusetts, United States (2000-2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled by using two methods-denoted satellite (1) and satellite (2)-before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (<2500 g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks). Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per interquartile range (2.41 μg/m) increase in PM2.5 was -6 g (95% confidence interval = -8 to -5), -16 g (-21 to -11), and -19 g (-23 to -15), using the monitor, satellite (1), and satellite (2) methods, respectively. Adjusted odds ratios, based on the same three exposure methods, for term low birth weight were 1.01 (0.98-1.04), 1.06 (0.97-1.16), and 1.08 (1.01-1.16); for SGA, 1.03 (1.01-1.04), 1.06 (1.03-1.10), and 1.08 (1.04-1.11); and for preterm birth, 1.00 (0.99-1.02), 0.98 (0.94-1.03), and 0.99 (0.95-1.03). Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information.

Improved exposure estimation in soil screening and cleanup criteria for volatile organic chemicals.

PubMed

DeVaull, George E

2017-09-01

Soil cleanup criteria define acceptable concentrations of organic chemical constituents for exposed humans. These criteria sum the estimated soil exposure over multiple pathways. Assumptions for ingestion, dermal contact, and dust exposure generally presume a chemical persists in surface soils at a constant concentration level for the entire exposure duration. For volatile chemicals, this is an unrealistic assumption. A calculation method is presented for surficial soil criteria that include volatile depletion of chemical for these uptake pathways. The depletion estimates compare favorably with measured concentration profiles and with field measurements of soil concentration. Corresponding volatilization estimates compare favorably with measured data for a wide range of volatile and semivolatile chemicals, including instances with and without the presence of a mixed-chemical residual phase. Selected examples show application of the revised factors in estimating screening levels for benzene in surficial soils. Integr Environ Assess Manag 2017;13:861-869. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Assessment of exposure to EMF in a Danish case-control study of childhood cancer.

PubMed

Jensen, J K; Olsen, J H; Folkersen, E

1994-01-01

In Denmark it is permitted to draw overhead lines across residential areas. In connection with a Danish case-control study we developed a method for estimating the historical values of magnetic fields at residences. The study included 1,707 cases with childhood cancer and 4,788 matched population controls. A total of 16,082 different addresses had been occupied by the families from the time of conception until the date of diagnosis. The values of the extreme, maximum, middle and minimum 50 Hz magnetic field strengths originating from a 50-400 kV high-voltage installation were estimated for each of the dwellings included in a potential exposure area. 30 children were exposed to an average level of magnetic fields of 0.1 microT or more. The evaluated Danish method of exposure assessment was compared with the method for residential wiring codes developed by Wertheimer and Leeper /1/. We concluded that the US wiring codes are inappropriate for use in connection with the Danish electricity transmission system.

Prenatal Air Pollution Exposure and Ultrasound Measures of Fetal Growth in Los Angeles, California

PubMed Central

Ritz, Beate; Qiu, Jiaheng; Lee, Pei-Chen; Lurmann, Fred; Penfold, Bryan; Weiss, Robert Erin; McConnell, Rob; Arora, Chander; Hobel, Calvin; Wilhelm, Michelle

2014-01-01

Background Few previous studies examined the impact of prenatal air pollution exposures on fetal development based on ultrasound measures during pregnancy. Methods In a prospective birth cohort of more than 500 women followed during 1993-1996 in Los Angeles, California, we examined how air pollution impacts fetal growth during pregnancy. Exposure to traffic related air pollution was estimated using CALINE4 air dispersion modeling for nitrogen oxides (NOx) and a land use regression (LUR) model for nitrogen monoxide (NO), nitrogen dioxide (NO2) and NOx. Exposures to carbon monoxide (CO), NO2, ozone (O3) and particles <10 μm in aerodynamic diameter (PM10) were estimated using government monitoring data. We employed a linear mixed effects model to estimate changes in fetal size at approximately 19, 29 and 37 weeks gestation based on ultrasound. Results Exposure to traffic-derived air pollution during 29 to 37 weeks was negatively associated with biparietal diameter at 37 weeks gestation. For each interquartile range (IQR) increase in LUR-based estimates of NO, NO2 and NOx, or freeway CALINE4 NOx we estimated a reduction in biparietal diameter of 0.2-0.3 mm. For women residing within 5 km of a monitoring station, we estimated biparietal diameter reductions of 0.9-1.0 mm per IQR increase in CO and NO2. Effect estimates were robust to adjustment for a number of potential confounders. We did not observe consistent patterns for other growth endpoints we examined. Conclusions Prenatal exposure to traffic-derived pollution was negatively associated with fetal head size measured as biparietal diameter in late pregnancy. PMID:24517884

The moving-window Bayesian maximum entropy framework: estimation of PM(2.5) yearly average concentration across the contiguous United States.

PubMed

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L

2012-09-01

Geostatistical methods are widely used in estimating long-term exposures for epidemiological studies on air pollution, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and the uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian maximum entropy (BME) method and applied this framework to estimate fine particulate matter (PM(2.5)) yearly average concentrations over the contiguous US. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingness in the air-monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM(2.5) data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM(2.5). Moreover, the MWBME method further reduces the MSE by 8.4-43.7%, with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM(2.5) across large geographical domains with expected spatial non-stationarity.

Bayesian effect estimation accounting for adjustment uncertainty.

PubMed

Wang, Chi; Parmigiani, Giovanni; Dominici, Francesca

2012-09-01

Model-based estimation of the effect of an exposure on an outcome is generally sensitive to the choice of which confounding factors are included in the model. We propose a new approach, which we call Bayesian adjustment for confounding (BAC), to estimate the effect of an exposure of interest on the outcome, while accounting for the uncertainty in the choice of confounders. Our approach is based on specifying two models: (1) the outcome as a function of the exposure and the potential confounders (the outcome model); and (2) the exposure as a function of the potential confounders (the exposure model). We consider Bayesian variable selection on both models and link the two by introducing a dependence parameter, ω, denoting the prior odds of including a predictor in the outcome model, given that the same predictor is in the exposure model. In the absence of dependence (ω= 1), BAC reduces to traditional Bayesian model averaging (BMA). In simulation studies, we show that BAC, with ω > 1, estimates the exposure effect with smaller bias than traditional BMA, and improved coverage. We, then, compare BAC, a recent approach of Crainiceanu, Dominici, and Parmigiani (2008, Biometrika 95, 635-651), and traditional BMA in a time series data set of hospital admissions, air pollution levels, and weather variables in Nassau, NY for the period 1999-2005. Using each approach, we estimate the short-term effects of on emergency admissions for cardiovascular diseases, accounting for confounding. This application illustrates the potentially significant pitfalls of misusing variable selection methods in the context of adjustment uncertainty. © 2012, The International Biometric Society.

High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization

EPA Science Inventory

Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present method...

USING DOSE ADDITION TO ESTIMATE CUMULATIVE RISKS FROM EXPOSURES TO MULTIPLE CHEMICALS

EPA Science Inventory

The Food Quality Protection Act (FQPA) of 1996 requires the EPA to consider the cumulative risk from exposure to multiple chemicals that have a common mechanism of toxicity. Three methods, hazard index (HI), point-of-departure index (PODI), and toxicity equivalence factor (TEF), ...

EXPOSURES AND INTERNAL DOSES OF TRIHALOMETHANES IN HUMANS: MULTI-ROUTE CONTRIBUTIONS FROM DRINKING WATER (FINAL)

EPA Science Inventory

The National Center for Environmental Assessment (NCEA) has released a final report that presents and applies a method to estimate distributions of internal concentrations of trihalomethanes (THMs) in humans resulting from a residential drinking water exposure. The report presen...

DEVELOPMENT AND EVALUATION OF AN AGGREGATE SURFACE SAMPLING METHOD FOR USE IN ASSESSING DERMAL EXPOSURES OF YOUNG CHILDREN

EPA Science Inventory

In the macroactivity approach, dermal exposure is estimated using empirically-derived transfer coefficients to aggregate the mass transfer associated with a series of contacts with a contaminated medium. The macroactivity approach affords the possibility of developing screenin...

Estimate of safe human exposure levels for lunar dust based on comparative benchmark dose modeling.

PubMed

James, John T; Lam, Chiu-Wing; Santana, Patricia A; Scully, Robert R

2013-04-01

Brief exposures of Apollo astronauts to lunar dust occasionally elicited upper respiratory irritation; however, no limits were ever set for prolonged exposure to lunar dust. The United States and other space faring nations intend to return to the moon for extensive exploration within a few decades. In the meantime, habitats for that exploration, whether mobile or fixed, must be designed to limit human exposure to lunar dust to safe levels. Herein we estimate safe exposure limits for lunar dust collected during the Apollo 14 mission. We instilled three respirable-sized (∼2 μ mass median diameter) lunar dusts (two ground and one unground) and two standard dusts of widely different toxicities (quartz and TiO₂) into the respiratory system of rats. Rats in groups of six were given 0, 1, 2.5 or 7.5 mg of the test dust in a saline-Survanta® vehicle, and biochemical and cellular biomarkers of toxicity in lung lavage fluid were assayed 1 week and one month after instillation. By comparing the dose--response curves of sensitive biomarkers, we estimated safe exposure levels for astronauts and concluded that unground lunar dust and dust ground by two different methods were not toxicologically distinguishable. The safe exposure estimates were 1.3 ± 0.4 mg/m³ (jet-milled dust), 1.0 ± 0.5 mg/m³ (ball-milled dust) and 0.9 ± 0.3 mg/m³ (unground, natural dust). We estimate that 0.5-1 mg/m³ of lunar dust is safe for periodic human exposures during long stays in habitats on the lunar surface.

The role of exposure on differences in driver death rates by gender and age: Results of a quasi-induced method on crash data in Spain.

PubMed

Pulido, José; Barrio, Gregorio; Hoyos, Juan; Jiménez-Mejías, Eladio; Martín-Rodríguez, María Del Mar; Houwing, Sjoerd; Lardelli-Claret, Pablo

2016-09-01

Part of the differences by age and gender in driver death rates from traffic injuries depends on the amount of exposure (km/year travelled). Unfortunately, direct indicators of exposure are not available in many countries. Our aim was to compare the age and gender differences in death rates with and without adjustment by exposure using a quasi-induced exposure approach in Spain, during 2004-2012. Crude and adjusted death rate ratios (CDRR and ADRR, respectively) were calculated for each age and gender group. To obtain the latter estimates, in accordance with quasi-exposure reasoning, the number of registered drivers was replaced by the number of non-infractor drivers, passively involved in collisions with another vehicle whose driver committed an infraction. 18-29 years and female drivers were chosen as the reference categories for age and gender. Striking differences were found between CDRR and ADRR estimates. When CDRR were estimated, we found the highest traffic mortality among the youngest drivers, except for females in non-urban roads. ADRR however showed the highest mortality among the oldest groups, especially in females, peaking among drivers >74 years in all types of roads. Regarding differences by gender, both estimates revealed higher traffic mortality in males, although the differences were much smaller when using ADRR. CDRR and ADRR for males tended to converge as age increased. Death risk from traffic injuries among drivers is clearly influenced by the amount of exposure. These findings further emphasize the need to obtain direct traffic exposure estimates by subgroups of drivers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exposure to traffic-related air pollution and risk of development of childhood asthma: A systematic review and meta-analysis.

PubMed

Khreis, Haneen; Kelly, Charlotte; Tate, James; Parslow, Roger; Lucas, Karen; Nieuwenhuijsen, Mark

2017-03-01

The question of whether children's exposure to traffic-related air pollution (TRAP) contributes to their development of asthma is unresolved. We conducted a systematic review and performed meta-analyses to analyze the association between TRAP and asthma development in childhood. We systematically reviewed epidemiological studies published until 8 September 2016 and available in the Embase, Ovid MEDLINE (R), and Transport databases. We included studies that examined the association between children's exposure to TRAP metrics and their risk of 'asthma' incidence or lifetime prevalence, from birth to age 18years old. We extracted key characteristics of each included study using a predefined data items template and these were tabulated. We used the Critical Appraisal Skills Programme checklists to assess the validity of each included study. Where four or more independent risk estimates were available for a continuous pollutant exposure, we conducted overall and age-specific meta-analyses, and four sensitivity analyses for each summary meta-analytic exposure-outcome association. Forty-one studies met our eligibility criteria. There was notable variability in asthma definitions, TRAP exposure assessment methods and confounder adjustment. The overall random-effects risk estimates (95% CI) were 1.08 (1.03, 1.14) per 0.5×10 -5 m -1 black carbon (BC), 1.05 (1.02, 1.07) per 4μg/m 3 nitrogen dioxide (NO 2 ), 1.48 (0.89, 2.45) per 30μg/m 3 nitrogen oxides (NO x ), 1.03 (1.01, 1.05) per 1μg/m 3 Particulate Matter <2.5μm in diameter (PM 2.5 ), and 1.05 (1.02, 1.08) per 2μg/m 3 Particulate Matter <10μm in diameter (PM 10 ). Sensitivity analyses supported these findings. Across the main analysis and age-specific analysis, the least heterogeneity was seen for the BC estimates, some heterogeneity for the PM 2.5 and PM 10 estimates and the most heterogeneity for the NO 2 and NO x estimates. The overall risk estimates from the meta-analyses showed statistically significant associations for BC, NO 2 , PM 2.5 , PM 10 exposures and risk of asthma development. Our findings support the hypothesis that childhood exposure to TRAP contributes to their development of asthma. Future meta-analyses would benefit from greater standardization of study methods including exposure assessment harmonization, outcome harmonization, confounders' harmonization and the inclusion of all important confounders in individual studies. PROSPERO 2014: CRD42014015448. Copyright © 2016 Elsevier Ltd. All rights reserved.

Volume error analysis for lung nodules attached to pulmonary vessels in an anthropomorphic thoracic phantom

NASA Astrophysics Data System (ADS)

Kinnard, Lisa M.; Gavrielides, Marios A.; Myers, Kyle J.; Zeng, Rongping; Peregoy, Jennifer; Pritchard, William; Karanian, John W.; Petrick, Nicholas

2008-03-01

High-resolution CT, three-dimensional (3D) methods for nodule volumetry have been introduced, with the hope that such methods will be more accurate and consistent than currently used planar measures of size. However, the error associated with volume estimation methods still needs to be quantified. Volume estimation error is multi-faceted in the sense that it is impacted by characteristics of the patient, the software tool and the CT system. The overall goal of this research is to quantify the various sources of measurement error and, when possible, minimize their effects. In the current study, we estimated nodule volume from ten repeat scans of an anthropomorphic phantom containing two synthetic spherical lung nodules (diameters: 5 and 10 mm; density: -630 HU), using a 16-slice Philips CT with 20, 50, 100 and 200 mAs exposures and 0.8 and 3.0 mm slice thicknesses. True volume was estimated from an average of diameter measurements, made using digital calipers. We report variance and bias results for volume measurements as a function of slice thickness, nodule diameter, and X-ray exposure.

Exposure-Response Estimates for Diesel Engine Exhaust and Lung Cancer Mortality Based on Data from Three Occupational Cohorts

PubMed Central

Silverman, Debra T.; Garshick, Eric; Vlaanderen, Jelle; Portengen, Lützen; Steenland, Kyle

2013-01-01

Background: Diesel engine exhaust (DEE) has recently been classified as a known human carcinogen. Objective: We derived a meta-exposure–response curve (ERC) for DEE and lung cancer mortality and estimated lifetime excess risks (ELRs) of lung cancer mortality based on assumed occupational and environmental exposure scenarios. Methods: We conducted a meta-regression of lung cancer mortality and cumulative exposure to elemental carbon (EC), a proxy measure of DEE, based on relative risk (RR) estimates reported by three large occupational cohort studies (including two studies of workers in the trucking industry and one study of miners). Based on the derived risk function, we calculated ELRs for several lifetime occupational and environmental exposure scenarios and also calculated the fractions of annual lung cancer deaths attributable to DEE. Results: We estimated a lnRR of 0.00098 (95% CI: 0.00055, 0.0014) for lung cancer mortality with each 1-μg/m3-year increase in cumulative EC based on a linear meta-regression model. Corresponding lnRRs for the individual studies ranged from 0.00061 to 0.0012. Estimated numbers of excess lung cancer deaths through 80 years of age for lifetime occupational exposures of 1, 10, and 25 μg/m3 EC were 17, 200, and 689 per 10,000, respectively. For lifetime environmental exposure to 0.8 μg/m3 EC, we estimated 21 excess lung cancer deaths per 10,000. Based on broad assumptions regarding past occupational and environmental exposures, we estimated that approximately 6% of annual lung cancer deaths may be due to DEE exposure. Conclusions: Combined data from three U.S. occupational cohort studies suggest that DEE at levels common in the workplace and in outdoor air appear to pose substantial excess lifetime risks of lung cancer, above the usually acceptable limits in the United States and Europe, which are generally set at 1/1,000 and 1/100,000 based on lifetime exposure for the occupational and general population, respectively. Citation: Vermeulen R, Silverman DT, Garshick E, Vlaanderen J, Portengen L, Steenland K. 2014. Exposure-response estimates for diesel engine exhaust and lung cancer mortality based on data from three occupational cohorts. Environ Health Perspect 122:172–177; http://dx.doi.org/10.1289/ehp.1306880 PMID:24273233

NHEXAS PHASE I ARIZONA STUDY--STANDARD OPERATING PROCEDURE FOR PROBABILISTIC APPROACH FOR CALCULATING INGESTION EXPOSURE FROM DAY 4 COMPOSITE MEASUREMENTS, THE DIRECT METHOD OF EXPOSURE ESTIMATION (IIT-A-15.0)

EPA Science Inventory

The purpose of this SOP is to describe the procedures undertaken to calculate the ingestion exposure using composite food chemical residue values from the day of direct measurements. The calculation is based on the probabilistic approach. This SOP uses data that have been proper...

Smoke exposure and associated health effects across several fire seasons and locations in the Western US

NASA Astrophysics Data System (ADS)

O'Dell, K.; Ford, B.; Gan, R.; Liu, J.; Lassman, W.; Burke, M.; Pfister, G.; Vaidyanathan, A.; Volckens, J.; Magzamen, S.; Fischer, E. V.; Pierce, J. R.

2017-12-01

Wildfires are a significant source of particulate matter in the western United States. Wildfire activity in this region has increased over the past few decades and is projected to continue to increase further due to warmer and drier conditions. Particulate matter with diameters smaller than or equal to 2.5 microns (PM2.5) has known adverse effects on human health. However, due to an inconsistent association of wildfire PM2.5 and several disease outcomes, it is unclear if wildfire PM exerts similar health impacts as anthropogenic PM. Improved wildfire smoke exposure estimates are needed to gain a clearer understanding of the health impacts of wildfire PM2.5. Characterizing PM2.5 concentrations from wildfire smoke is challenging due to the transient nature of smoke. Current methods of determining smoke exposure rely on satellite retrievals of aerosol optical depth (AOD), estimates from chemical transport models (CTMs), or values reported by surface monitoring sites; each of these data sources has some limitations. To improve the accuracy of our exposure estimates, we developed new methods to blend these data. Our results indicate that blending information from the above-mentioned data sources along with counts of wildfire-smoke-related social-media posts results in better characterization of smoke exposure than any individual tool. We link our daily smoke PM2.5 exposure estimates with hospitalization and urgent-care admission data from Washington, Oregon, and Colorado during several fire seasons as well as prescription filling data from Oregon. We find a robust relationship, where a 10 μg m-3 increase in smoke is significantly associated with a 9.5% (95% CI: 6.2, 12.9) increase in the rate of asthma admissions and a 7.7% increase (95% CI: 6.5. 8.8) in the risk for respiratory rescue medication prescription refills. There was no significant association between smoke exposure and any cardiovascular endpoints. Our findings support the association of wildfire smoke exposure with adverse respiratory events, including subclinical outcomes, but we did not find significant associations with any cardiovascular outcomes. Public health messaging should target vulnerable populations to avoid smoke exposure during wildfire events.

Comparisons of discrete and integrative sampling accuracy in estimating pulsed aquatic exposures.

PubMed

Morrison, Shane A; Luttbeg, Barney; Belden, Jason B

2016-11-01

Most current-use pesticides have short half-lives in the water column and thus the most relevant exposure scenarios for many aquatic organisms are pulsed exposures. Quantifying exposure using discrete water samples may not be accurate as few studies are able to sample frequently enough to accurately determine time-weighted average (TWA) concentrations of short aquatic exposures. Integrative sampling methods that continuously sample freely dissolved contaminants over time intervals (such as integrative passive samplers) have been demonstrated to be a promising measurement technique. We conducted several modeling scenarios to test the assumption that integrative methods may require many less samples for accurate estimation of peak 96-h TWA concentrations. We compared the accuracies of discrete point samples and integrative samples while varying sampling frequencies and a range of contaminant water half-lives (t 50  = 0.5, 2, and 8 d). Differences the predictive accuracy of discrete point samples and integrative samples were greatest at low sampling frequencies. For example, when the half-life was 0.5 d, discrete point samples required 7 sampling events to ensure median values > 50% and no sampling events reporting highly inaccurate results (defined as < 10% of the true 96-h TWA). Across all water half-lives investigated, integrative sampling only required two samples to prevent highly inaccurate results and measurements resulting in median values > 50% of the true concentration. Regardless, the need for integrative sampling diminished as water half-life increased. For an 8-d water half-life, two discrete samples produced accurate estimates and median values greater than those obtained for two integrative samples. Overall, integrative methods are the more accurate method for monitoring contaminants with short water half-lives due to reduced frequency of extreme values, especially with uncertainties around the timing of pulsed events. However, the acceptability of discrete sampling methods for providing accurate concentration measurements increases with increasing aquatic half-lives. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Comparison of the β-Substitution Method and a Bayesian Method for Analyzing Left-Censored Data.

PubMed

Huynh, Tran; Quick, Harrison; Ramachandran, Gurumurthy; Banerjee, Sudipto; Stenzel, Mark; Sandler, Dale P; Engel, Lawrence S; Kwok, Richard K; Blair, Aaron; Stewart, Patricia A

2016-01-01

Classical statistical methods for analyzing exposure data with values below the detection limits are well described in the occupational hygiene literature, but an evaluation of a Bayesian approach for handling such data is currently lacking. Here, we first describe a Bayesian framework for analyzing censored data. We then present the results of a simulation study conducted to compare the β-substitution method with a Bayesian method for exposure datasets drawn from lognormal distributions and mixed lognormal distributions with varying sample sizes, geometric standard deviations (GSDs), and censoring for single and multiple limits of detection. For each set of factors, estimates for the arithmetic mean (AM), geometric mean, GSD, and the 95th percentile (X0.95) of the exposure distribution were obtained. We evaluated the performance of each method using relative bias, the root mean squared error (rMSE), and coverage (the proportion of the computed 95% uncertainty intervals containing the true value). The Bayesian method using non-informative priors and the β-substitution method were generally comparable in bias and rMSE when estimating the AM and GM. For the GSD and the 95th percentile, the Bayesian method with non-informative priors was more biased and had a higher rMSE than the β-substitution method, but use of more informative priors generally improved the Bayesian method's performance, making both the bias and the rMSE more comparable to the β-substitution method. An advantage of the Bayesian method is that it provided estimates of uncertainty for these parameters of interest and good coverage, whereas the β-substitution method only provided estimates of uncertainty for the AM, and coverage was not as consistent. Selection of one or the other method depends on the needs of the practitioner, the availability of prior information, and the distribution characteristics of the measurement data. We suggest the use of Bayesian methods if the practitioner has the computational resources and prior information, as the method would generally provide accurate estimates and also provides the distributions of all of the parameters, which could be useful for making decisions in some applications. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Occupational exposure to pesticides and prostate cancer: a systematic review and meta-analysis.

PubMed

Lewis-Mikhael, Anne-Mary; Bueno-Cavanillas, Aurora; Ofir Giron, Talia; Olmedo-Requena, Rocío; Delgado-Rodríguez, Miguel; Jiménez-Moleón, José Juan

2016-02-01

Epidemiological studies on exposure to pesticides and risk of prostate cancer (PC) provide inconsistent results. We aimed to explore various potential sources of heterogeneity not previously assessed and to derive updated risk estimates from homogenous studies. We searched PubMed, Web of Science and Scopus databases for case-control and cohort studies published from 1985 to April 2014. We assessed the quality of the articles using the Newcastle-Ottawa Scale. Pooled estimates were calculated using random-effects models. Heterogeneity was explored using subset analyses and metaregression. Fifty-two studies were included in the review and 25 in the meta-analysis. No association was found between low exposure to pesticides and PC, but association was significant for high exposure, pooled OR 1.33 (1.02 to 1.63), I(2)=44.8%, p=0.024. Heterogeneity was explained by a number of variables including method used to assess exposure. Pooled OR was weak and non-significant for studies measuring serum pesticide level, 1.12 (0.74 to 1.50), I(2)=0.00%, p=0.966. For studies applying self-reporting of exposure, pooled estimate was 1.34 (0.91 to 1.77), I(2)=0.00%, p=0.493, while a high significant association was detected for grouped exposure assessment, 2.24 (1.36 to 3.11), I(2)=0.00%, p=0.955. In spite of a weak significant association detected when pooling ORs for high occupational exposure to pesticides, the magnitude of the association was related to the method of exposure assessment used by the original studies. A family history-pesticide exposure interaction was also observed for a number of pesticides. 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/

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.

A comparison of methods for calculating population exposure estimates of daily weather for health research.

PubMed

Hanigan, Ivan; Hall, Gillian; Dear, Keith B G

2006-09-13

To explain the possible effects of exposure to weather conditions on population health outcomes, weather data need to be calculated at a level in space and time that is appropriate for the health data. There are various ways of estimating exposure values from raw data collected at weather stations but the rationale for using one technique rather than another; the significance of the difference in the values obtained; and the effect these have on a research question are factors often not explicitly considered. In this study we compare different techniques for allocating weather data observations to small geographical areas and different options for weighting averages of these observations when calculating estimates of daily precipitation and temperature for Australian Postal Areas. Options that weight observations based on distance from population centroids and population size are more computationally intensive but give estimates that conceptually are more closely related to the experience of the population. Options based on values derived from sites internal to postal areas, or from nearest neighbour sites--that is, using proximity polygons around weather stations intersected with postal areas--tended to include fewer stations' observations in their estimates, and missing values were common. Options based on observations from stations within 50 kilometres radius of centroids and weighting of data by distance from centroids gave more complete estimates. Using the geographic centroid of the postal area gave estimates that differed slightly from the population weighted centroids and the population weighted average of sub-unit estimates. To calculate daily weather exposure values for analysis of health outcome data for small areas, the use of data from weather stations internal to the area only, or from neighbouring weather stations (allocated by the use of proximity polygons), is too limited. The most appropriate method conceptually is the use of weather data from sites within 50 kilometres radius of the area weighted to population centres, but a simpler acceptable option is to weight to the geographic centroid.

Longitudinal T1 relaxation rate (R1) captures changes in short-term Mn exposure in welders

PubMed Central

Lewis, Mechelle M.; Flynn, Michael R.; Lee, Eun-Young; Van Buren, Scott; Van Buren, Eric; Du, Guangwei; Fry, Rebecca C.; Herring, Amy H.; Kong, Lan; Mailman, Richard B.; Huang, Xuemei

2016-01-01

Objectives We demonstrated recently that the T1 relaxation rate (R1) captured short-term Mn exposure in welders with chronic, relatively low exposure levels in a cross-sectional study. In the current study, we used a longitudinal design to examine whether R1 values reflect the short-term dynamics of Mn exposure. Methods Twenty-nine welders were evaluated at baseline and 12 months. Occupational questionnaires estimated short-term welding exposure using welding hours in the 90 days prior to each study visit (HrsW90). In addition, blood Mn levels, the pallidal index (PI; globus pallidus T1-weighted intensity (T1WI)/frontal white matter T1WI), and R1 values in brain regions of interest (ROIs) were determined as Mn biomarkers at each visit. Associations between changes in estimated welding exposure and changes in purported Mn biomarkers were assessed by Spearman’s correlations with adjustment for age and baseline R1, HrsW90, and blood Mn values. Results Changes in welding hours (HrsW90: the short-term welding exposure estimate), was associated significantly with changes in R1 values in the putamen (r=0.541, p=0.005), caudate (R=0.453, p=0.023), globus pallidus (R=0.430, p=0.032), amygdala (R=0.461, p=0.020), and hippocampus (R=0.447, p=0.025), but not with changes in blood Mn levels or the PI. Discussion Changes in R1 values correlated with changes in the short-term welding exposure estimate, but not with more traditional measures of Mn exposure (blood Mn levels or PI). These results suggest that R1 may serve as a useful marker to capture the short-term dynamics in Mn brain accumulation related to welding exposure. PMID:27567731

Cardiovascular health, traffic-related air pollution and noise: are associations mutually confounded? A systematic review.

PubMed

Tétreault, Louis-François; Perron, Stéphane; Smargiassi, Audrey

2013-10-01

This review assessed the confounding effect of one traffic-related exposure (noise or air pollutants) on the association between the other exposure and cardiovascular outcomes. A systematic review was conducted with the databases Medline and Embase. The confounding effects in studies were assessed by using change in the estimate with a 10 % cutoff point. The influence on the change in the estimate of the quality of the studies, the exposure assessment methods and the correlation between road noise and air pollutions were also assessed. Nine publications were identified. For most studies, the specified confounders produced changes in estimates <10 %. The correlation between noise and pollutants, the quality of the study and of the exposure assessment do not seem to influence the confounding effects. Results from this review suggest that confounding of cardiovascular effects by noise or air pollutants is low, though with further improvements in exposure assessment, the situation may change. More studies using pollution indicators specific to road traffic are needed to properly assess if noise and air pollution are subjected to confounding.

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

Development of improved wildfire smoke exposure estimates for health studies in the western U.S.

NASA Astrophysics Data System (ADS)

Ivey, C.; Holmes, H.; Loria Salazar, S. M.; Pierce, A.; Liu, C.

2016-12-01

Wildfire smoke exposure is a significant health concern in the western U.S. because large wildfires have increased in size and frequency over the past four years due to drought conditions. The transport phenomena in complex terrain and timing of the wildfire emissions make the smoke plumes difficult to simulate using conventional air quality models. Monitoring data can be used to estimate exposure metrics, but in rural areas the monitoring networks are too sparse to calculate wildfire exposure metrics for the entire population in a region. Satellite retrievals provide global, spatiotemporal air quality information and are used to track pollution plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Particulate matter (PM) exposures can be estimated using columnar aerosol optical depth (AOD), where satellite AOD retrievals serve as a spatial surrogate to simulate surface PM gradients. These exposure models have been successfully used in health effects studies in the eastern U.S. where complex mountainous terrain and surface reflectance do not limit AOD retrival from satellites. Using results from a chemical transport model (CTM) is another effective method to determine spatial gradients of pollutants. However, the CTM does not adequately capture the temporal and spatial distribution of wildfire smoke plumes. By combining the spatiotemporal pollutant fields from both satellite retrievals and CTM results with ground based pollutant observations the spatial wildfire smoke exposure model can be improved. This work will address the challenge of understanding the spatiotemporal distributions of pollutant concentrations to model human exposures of wildfire smoke in regions with complex terrain, where meteorological conditions as well as emission sources significantly influence the spatial distribution of pollutants. The focus will be on developing models to enhance exposure estimates of elevated PM and ozone concentrations from wildfire smoke plumes in the western U.S.

Gamma-H2AX-based dose estimation for whole and partial body radiation exposure.

PubMed

Horn, Simon; Barnard, Stephen; Rothkamm, Kai

2011-01-01

Most human exposures to ionising radiation are partial body exposures. However, to date only limited tools are available for rapid and accurate estimation of the dose distribution and the extent of the body spared from the exposure. These parameters are of great importance for emergency triage and clinical management of exposed individuals. Here, measurements of γ-H2AX immunofluorescence by microscopy and flow cytometry were compared as rapid biodosimetric tools for whole and partial body exposures. Ex vivo uniformly X-irradiated blood lymphocytes from one donor were used to generate a universal biexponential calibration function for γ-H2AX foci/intensity yields per unit dose for time points up to 96 hours post exposure. Foci--but not intensity--levels remained significantly above background for 96 hours for doses of 0.5 Gy or more. Foci-based dose estimates for ex vivo X-irradiated blood samples from 13 volunteers were in excellent agreement with the actual dose delivered to the targeted samples. Flow cytometric dose estimates for X-irradiated blood samples from 8 volunteers were in excellent agreement with the actual dose delivered at 1 hour post exposure but less so at 24 hours post exposure. In partial body exposures, simulated by mixing ex vivo irradiated and unirradiated lymphocytes, foci/intensity distributions were significantly over-dispersed compared to uniformly irradiated lymphocytes. For both methods and in all cases the estimated fraction of irradiated lymphocytes and dose to that fraction, calculated using the zero contaminated Poisson test and γ-H2AX calibration function, were in good agreement with the actual mixing ratios and doses delivered to the samples. In conclusion, γ-H2AX analysis of irradiated lymphocytes enables rapid and accurate assessment of whole body doses while dispersion analysis of foci or intensity distributions helps determine partial body doses and the irradiated fraction size in cases of partial body exposures.

Application of physiologically based pharmacokinetic (PBPK) model of trichloroethylene in rats for estimation of internal dose

EPA Science Inventory

Potential human health risk from chemical exposure must often be assessed for conditions for which suitable human or animal data are not available, requiring extrapolation across duration and concentration. The default method for exposure-duration adjustment is based on Haber's r...

EPA Exposure Research and the ExpoCast Project: New Methods and New Data (NIEHS Exposome webinar)

EPA Science Inventory

Estimates of human and ecological exposures are required as critical input to risk-based prioritization and screening of thousands of chemicals. In a 2009 commentary in Environmental Health Perspectives, Shelden and Hubal proposed that “Novel statistical and informatic approaches...

METHODS DEVELOPMENT AT THE NEAR LAB ECOLOGICAL RESEARCH AREA (NLERA) LOCATED IN THE NEUSE RIVER BASIN.

EPA Science Inventory

This task supports the Agency's efforts on developing a proper risk assessment tools to address Ecological and eventually Human exposures. The Agency needs to be able to identify, measure and estimate ecosystem exposure to multiple stressors. The research under this task suppor...

Association Between Satellite-based Estimates of Long-term PM2.5 Exposure and Coronary Artery Disease

EPA Science Inventory

Background: Epidemiological studies have identified associations between long-term PM2.5 exposure and cardiovascular events, though most have relied on concentrations from central-site air quality monitors. Methods: We utilized a cohort of 5679 patients who had undergone cardiac ...

SAP Minutes No. 2014-03 for FIFRA meeting held July 29-31, 2014. A set of scientific issues being considered by the Environmental Protection Agency regarding new high throughput methods to estimate chemical exposure

USDA-ARS?s Scientific Manuscript database

On July 29-31, 2014, the US Environmental Protection Agency convened a public meeting of the FIFRA Scientific Advisory Panel (SAP) to address scientific issues associated with the agency’s “new High Throughput Methods to Estimate Chemical Exposure”. EPA is proposing to use these methods to identify...

Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection*

PubMed Central

Fan, Jianqing; Li, Yingying; Yu, Ke

2012-01-01

Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index. PMID:23264708

Estimating water supply arsenic levels in the New England bladder cancer study

USGS Publications Warehouse

Nuckols, John R.; Beane Freeman, Laura E.; Lubin, Jay H.; Airola, Matthew S.; Baris, Dalsu; Ayotte, Joseph D.; Taylor, Anne; Paulu, Chris; Karagas, Margaret R.; Colt, Joanne; Ward, Mary H.; Huang, An-Tsun; Bress, William; Cherala, Sai; Silverman, Debra T.; Cantor, Kenneth P.

2011-01-01

Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods.

KABAM Version 1.0 User's Guide and Technical Documentation - Appendix H - Methods for Estimating Metabolism Rate Constant

EPA Pesticide Factsheets

Appendix H of KABAM Version 1.0 documentation related to estimating the metabolism rate constant. KABAM is a simulation model used to predict pesticide concentrations in aquatic regions for use in exposure assessments.

Methodologies for the quantitative estimation of toxicant dose to cigarette smokers using physical, chemical and bioanalytical data

PubMed Central

McAughey, John; Shepperd, Christopher J.

2013-01-01

Methodologies have been developed, described and demonstrated that convert mouth exposure estimates of cigarette smoke constituents to dose by accounting for smoke spilled from the mouth prior to inhalation (mouth-spill (MS)) and the respiratory retention (RR) during the inhalation cycle. The methodologies are applicable to just about any chemical compound in cigarette smoke that can be measured analytically and can be used with ambulatory population studies. Conversion of exposure to dose improves the relevancy for risk assessment paradigms. Except for urinary nicotine plus metabolites, biomarkers generally do not provide quantitative exposure or dose estimates. In addition, many smoke constituents have no reliable biomarkers. We describe methods to estimate the RR of chemical compounds in smoke based on their vapor pressure (VP) and to estimate the MS for a given subject. Data from two clinical studies were used to demonstrate dose estimation for 13 compounds, of which only 3 have urinary biomarkers. Compounds with VP > 10−5 Pa generally have RRs of 88% or greater, which do not vary appreciably with inhalation volume (IV). Compounds with VP < 10−7 Pa generally have RRs dependent on IV and lung exposure time. For MS, mean subject values from both studies were slightly greater than 30%. For constituents with urinary biomarkers, correlations with the calculated dose were significantly improved over correlations with mouth exposure. Of toxicological importance is that the dose correlations provide an estimate of the metabolic conversion of a constituent to its respective biomarker. PMID:23742081

Personalized cumulative UV tracking on mobiles & wearables.

PubMed

Dey, S; Sahoo, S; Agrawal, H; Mondal, A; Bhowmik, T; Tiwari, V N

2017-07-01

Maintaining a balanced Ultra Violet (UV) exposure level is vital for a healthy living as the excess of UV dose can lead to critical diseases such as skin cancer while the absence can cause vitamin D deficiency which has recently been linked to onset of cardiac abnormalities. Here, we propose a personalized cumulative UV dose (CUVD) estimation system for smartwatch and smartphone devices having the following novelty factors; (a) sensor orientation invariant measurement of UV exposure using a bootstrap resampling technique, (b) estimation of UV exposure using only light intensity (lux) sensor (c) optimal UV exposure dose estimation. Our proposed method will eliminate the need for a dedicated UV sensor thus widen the user base of the proposed solution, render it unobtrusive by eliminating the critical requirement of orienting the device in a direction facing the sun. The system is implemented on android mobile platform and validated on 1200 minutes of lux and UV index (UVI) data collected across several days covering morning to evening time frames. The result shows very impressive final UVI estimation accuracy. We believe our proposed solution will enable the future wearable and smartphone users to obtain a seamless personalized UV exposure dose across a day paving a way for simple yet very useful recommendations such as right skin protective measure for reducing risk factors of long term UV exposure related diseases like skin cancer and, cardiac abnormality.

The Global Burden of Occupational Disease.

PubMed

Rushton, Lesley

2017-09-01

Burden of occupational disease estimation contributes to understanding of both magnitude and relative importance of different occupational hazards and provides essential information for targeting risk reduction. This review summarises recent key findings and discusses their impact on occupational regulation and practice. New methods have been developed to estimate burden of occupational disease that take account of the latency of many chronic diseases and allow for exposure trends and workforce turnover. Results from these studies have shown in several countries and globally that, in spite of improvements in workplace technology, practices and exposures over the last decades, occupational hazards remain an important cause of ill health and mortality worldwide. Major data gaps have been identified particularly regarding exposure information. Reliable data on employment and disease are also lacking especially in developing countries. Burden of occupational disease estimates form an important part of decision-making processes.

Development of a source-exposure matrix for occupational exposure assessment of electromagnetic fields in the INTEROCC study

PubMed Central

Vila, Javier; Bowman, Joseph D; Figuerola, Jordi; Moriña, David; Kincl, Laurel; Richardson, Lesley; Cardis, Elisabeth

2017-01-01

Introduction To estimate occupational exposures to electromagnetic fields (EMF) for the INTEROCC study, a database of source-based measurements extracted from published and unpublished literature resources had been previously constructed. The aim of the current work was to summarize these measurements into a source-exposure matrix (SEM), accounting for their quality and relevance. Methods A novel methodology for combining available measurements was developed, based on order statistics and log-normal distribution characteristics. Arithmetic and geometric means, and estimates of variability and maximum exposure were calculated by EMF source, frequency band and dosimetry type. Mean estimates were weighted by our confidence on the pooled measurements. Results The SEM contains confidence-weighted mean and maximum estimates for 312 EMF exposure sources (from 0 Hz to 300 GHz). Operator position geometric mean electric field levels for RF sources ranged between 0.8 V/m (plasma etcher) and 320 V/m (RF sealer), while magnetic fields ranged from 0.02 A/m (speed radar) to 0.6 A/m (microwave heating). For ELF sources, electric fields ranged between 0.2 V/m (electric forklift) and 11,700 V/m (HVTL-hotsticks), while magnetic fields ranged between 0.14 μT (visual display terminals) and 17 μT (TIG welding). Conclusion The methodology developed allowed the construction of the first EMF-SEM and may be used to summarize similar exposure data for other physical or chemical agents. PMID:27827378

Radiation exposure assessment for portsmouth naval shipyard health studies.

PubMed

Daniels, R D; Taulbee, T D; Chen, P

2004-01-01

Occupational radiation exposures of 13,475 civilian nuclear shipyard workers were investigated as part of a retrospective mortality study. Estimates of annual, cumulative and collective doses were tabulated for future dose-response analysis. Record sets were assembled and amended through range checks, examination of distributions and inspection. Methods were developed to adjust for administrative overestimates and dose from previous employment. Uncertainties from doses below the recording threshold were estimated. Low-dose protracted radiation exposures from submarine overhaul and repair predominated. Cumulative doses are best approximated by a hybrid log-normal distribution with arithmetic mean and median values of 20.59 and 3.24 mSv, respectively. The distribution is highly skewed with more than half the workers having cumulative doses <10 mSv and >95% having doses <100 mSv. The maximum cumulative dose is estimated at 649.39 mSv from 15 person-years of exposure. The collective dose was 277.42 person-Sv with 96.8% attributed to employment at Portsmouth Naval Shipyard.

Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies.

PubMed

Satagopan, Jaya M; Sen, Ananda; Zhou, Qin; Lan, Qing; Rothman, Nathaniel; Langseth, Hilde; Engel, Lawrence S

2016-06-01

Matched case-control studies are popular designs used in epidemiology for assessing the effects of exposures on binary traits. Modern studies increasingly enjoy the ability to examine a large number of exposures in a comprehensive manner. However, several risk factors often tend to be related in a nontrivial way, undermining efforts to identify the risk factors using standard analytic methods due to inflated type-I errors and possible masking of effects. Epidemiologists often use data reduction techniques by grouping the prognostic factors using a thematic approach, with themes deriving from biological considerations. We propose shrinkage-type estimators based on Bayesian penalization methods to estimate the effects of the risk factors using these themes. The properties of the estimators are examined using extensive simulations. The methodology is illustrated using data from a matched case-control study of polychlorinated biphenyls in relation to the etiology of non-Hodgkin's lymphoma. © 2015, The International Biometric Society.

Mutation rates at the glycophorin A and HPRT loci in uranium miners exposed to radon progeny.

PubMed Central

Shanahan, E M; Peterson, D; Roxby, D; Quintana, J; Morely, A A; Woodward, A

1996-01-01

OBJECTIVES--To find whether a relation exists between estimated levels of exposure to radon and its progeny and mutations in hypoxanthine phosphoribosyl transferase (HPRT) and glycophorin A in a cohort of former uranium miners. METHODS--A cohort study involving a sample of miners from the Radium Hill uranium mine in South Australia, which operated from 1952 to 1961. Radiation exposures underground at Radium Hill were estimated from historical radon gas measures with a job exposure matrix. Workers from the mine who worked exclusively above ground according to mine records were selected as controls. In 1991-2 miners were interviewed and blood taken for measurement of somatic mutations. Mutation rates for HPRT and glycophorin A were estimated with standard assay techniques. RESULTS--Homozygous mutations of glycophorin A were increased in underground miners (P = 0.0027) and the mutation rate tended to rise with increasing exposure with the exception of the highest exposure (> 10 working level months). However, there was no association between place of work and either the hemizygous mutations of glycophorin A or the HPRT mutation. CONCLUSIONS--There may be an association between glycophorin A mutations and previous occupational exposure to ionising radiation. However, not enough is known at present to use these assays as biomarkers for historical exposure in underground mining cohorts. PMID:8704866

Explicit formula of finite difference method to estimate human peripheral tissue temperatures during exposure to severe cold stress.

PubMed

Khanday, M A; Hussain, Fida

2015-02-01

During cold exposure, peripheral tissues undergo vasoconstriction to minimize heat loss to preserve the maintenance of a normal core temperature. However, vasoconstricted tissues exposed to cold temperatures are susceptible to freezing and frostbite-related tissue damage. Therefore, it is imperative to establish a mathematical model for the estimation of tissue necrosis due to cold stress. To this end, an explicit formula of finite difference method has been used to obtain the solution of Pennes' bio-heat equation with appropriate boundary conditions to estimate the temperature profiles of dermal and subdermal layers when exposed to severe cold temperatures. The discrete values of nodal temperature were calculated at the interfaces of skin and subcutaneous tissues with respect to the atmospheric temperatures of 25 °C, 20 °C, 15 °C, 5 °C, -5 °C and -10 °C. The results obtained were used to identify the scenarios under which various degrees of frostbite occur on the surface of skin as well as the dermal and subdermal areas. The explicit formula of finite difference method proposed in this model provides more accurate predictions as compared to other numerical methods. This model of predicting tissue temperatures provides researchers with a more accurate prediction of peripheral tissue temperature and, hence, the susceptibility to frostbite during severe cold exposure. Copyright © 2014 Elsevier Ltd. All rights reserved.

Risks for the development of outcomes related to occupational allergies: an application of the asthma-specific job exposure matrix compared with self-reports and investigator scores on job-training-related exposure.

PubMed

Suarthana, E; Heederik, D; Ghezzo, H; Malo, J-L; Kennedy, S M; Gautrin, D

2009-04-01

Risks for development of occupational sensitisation, bronchial hyper-responsiveness, rhinoconjunctival and chest symptoms at work associated with continued exposure to high molecular weight (HMW) allergens were estimated with three exposure assessment methods. A Cox regression analysis with adjustment for atopy and smoking habit was carried out in 408 apprentices in animal health technology, pastry making, and dental hygiene technology with an 8-year follow-up after training. The risk of continued exposure after training, estimated by the asthma-specific job exposure matrix (JEM), was compared with self-reports and investigator scores on job-training-related exposure. Associations between outcomes and work duration in job(s) related to training were also evaluated. Exposure to animal-derived HMW allergens, subsequent to the apprenticeship period, as estimated by the JEM, was associated with a significantly increased risk for occupational sensitisation (hazard ratio (HR) 6.4; 95% CI 2.3 to 18.2) and rhinoconjunctival symptoms at work (HR 2.6; 95% CI 1.1 to 6.2). Exposure to low molecular weight (LMW) agents significantly increased the risk of developing bronchial hyper-responsiveness (HR 2.3; 95% CI 1.1 to 5.4). Exposure verification appeared to be important to optimise the sensitivity and the specificity, as well as HRs produced by the JEM. Self-reports and investigator scores also indicated that further exposure to HMW allergens increased the risk of developing occupational allergies. The agreement between self-reports, investigator scores, and the JEM were moderate to good. There was no significant association between respiratory outcomes and work duration in jobs related to training. The asthma-specific JEM could estimate the risk of various outcomes of occupational allergies associated with exposure to HMW and LMW allergens, but it is relatively labour intensive. Exposure verification is an important integrated step in the JEM that optimised the performance of the matrix.

Postmenopausal Breast Cancer Is Associated with Exposure to Traffic-Related Air Pollution in Montreal, Canada: A Case–Control Study

PubMed Central

Crouse, Dan L.; Goldberg, Mark S.; Ross, Nancy A.; Chen, Hong; Labrèche, France

2010-01-01

Background Only about 30% of cases of breast cancer can be explained by accepted risk factors. Occupational studies have shown associations between the incidence of breast cancer and exposure to contaminants that are found in ambient air. Objectives We sought to determine whether the incidence of postmenopausal breast cancer is associated with exposure to urban air pollution. Methods We used data from a case–control study conducted in Montreal, Quebec, in 1996–1997. Cases were 383 women with incident invasive breast cancer, and controls were 416 women with other incident, malignant cancers, excluding those potentially associated with selected occupational exposures. Concentrations of nitrogen dioxide (NO2) were measured across Montreal in 2005–2006. We developed a land-use regression model to predict concentrations of NO2 across Montreal for 2006, and developed two methods to extrapolate the estimates to 1985 and 1996. We linked these estimates to addresses of residences of subjects at time of interview. We used unconditional logistic regression to adjust for accepted and suspected risk factors and occupational exposures. Results For each increase of 5 ppb NO2 estimated in 1996, the adjusted odds ratio was 1.31 (95% confidence interval, 1.00–1.71). Although the size of effect varied somewhat across periods, we found an increased risk of approximately 25% for every increase of 5 ppb in exposure. Conclusions We found evidence of an association between the incidence of postmenopausal breast cancer and exposure to ambient concentrations of NO2. Further studies are needed to confirm whether NO2 or other components of traffic-related pollution are indeed associated with increased risks. PMID:20923746

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

Quantifying light exposure patterns in young adult students

NASA Astrophysics Data System (ADS)

Alvarez, Amanda A.; Wildsoet, Christine F.

2013-08-01

Exposure to bright light appears to be protective against myopia in both animals (chicks, monkeys) and children, but quantitative data on human light exposure are limited. In this study, we report on a technique for quantifying light exposure using wearable sensors. Twenty-seven young adult subjects wore a light sensor continuously for two weeks during one of three seasons, and also completed questionnaires about their visual activities. Light data were analyzed with respect to refractive error and season, and the objective sensor data were compared with subjects' estimates of time spent indoors and outdoors. Subjects' estimates of time spent indoors and outdoors were in poor agreement with durations reported by the sensor data. The results of questionnaire-based studies of light exposure should thus be interpreted with caution. The role of light in refractive error development should be investigated using multiple methods such as sensors to complement questionnaires.

Quantifying light exposure patterns in young adult students

PubMed Central

Alvarez, Amanda A.; Wildsoet, Christine F.

2014-01-01

Exposure to bright light appears to be protective against myopia in both animals (chicks, monkeys) and children, but quantitative data on human light exposure are limited. In this study, we report on a technique for quantifying light exposure using wearable sensors. Twenty-seven young adult subjects wore a light sensor continuously for two weeks during one of three seasons, and also completed questionnaires about their visual activities. Light data were analyzed with respect to refractive error and season, and the objective sensor data were compared with subjects’ estimates of time spent indoors and outdoors. Subjects’ estimates of time spent indoors and outdoors were in poor agreement with durations reported by the sensor data. The results of questionnaire-based studies of light exposure should thus be interpreted with caution. The role of light in refractive error development should be investigated using multiple methods such as sensors to complement questionnaires. PMID:25342873

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.

Silica exposure during construction activities: statistical modeling of task-based measurements from the literature.

PubMed

Sauvé, Jean-François; Beaudry, Charles; Bégin, Denis; Dion, Chantal; Gérin, Michel; Lavoué, Jérôme

2013-05-01

Many construction activities can put workers at risk of breathing silica containing dusts, and there is an important body of literature documenting exposure levels using a task-based strategy. In this study, statistical modeling was used to analyze a data set containing 1466 task-based, personal respirable crystalline silica (RCS) measurements gathered from 46 sources to estimate exposure levels during construction tasks and the effects of determinants of exposure. Monte-Carlo simulation was used to recreate individual exposures from summary parameters, and the statistical modeling involved multimodel inference with Tobit models containing combinations of the following exposure variables: sampling year, sampling duration, construction sector, project type, workspace, ventilation, and controls. Exposure levels by task were predicted based on the median reported duration by activity, the year 1998, absence of source control methods, and an equal distribution of the other determinants of exposure. The model containing all the variables explained 60% of the variability and was identified as the best approximating model. Of the 27 tasks contained in the data set, abrasive blasting, masonry chipping, scabbling concrete, tuck pointing, and tunnel boring had estimated geometric means above 0.1mg m(-3) based on the exposure scenario developed. Water-fed tools and local exhaust ventilation were associated with a reduction of 71 and 69% in exposure levels compared with no controls, respectively. The predictive model developed can be used to estimate RCS concentrations for many construction activities in a wide range of circumstances.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies.

PubMed

Vedal, Sverre; Han, Bin; Xu, Jia; Szpiro, Adam; Bai, Zhipeng

2017-12-15

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies

PubMed Central

Vedal, Sverre; Han, Bin; Szpiro, Adam; Bai, Zhipeng

2017-01-01

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources. PMID:29244738

Estimation of pyrethroid pesticide intake using regression ...

EPA Pesticide Factsheets

Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation of pesticide intakes for a defined demographic community, and (2) comparison of dietary pesticide intakes between the composite and individual samples. Extant databases were useful for assigning individual samples to composites, but they could not provide the breadth of information needed to facilitate measurable levels in every composite. Composite sample measurements were found to be good predictors of pyrethroid pesticide levels in their individual sample constituents where sufficient measurements are available above the method detection limit. Statistical inference shows little evidence of differences between individual and composite measurements and suggests that regression modeling of food groups based on composite dietary samples may provide an effective tool for estimating dietary pesticide intake for a defined population. The research presented in the journal article will improve community's ability to determine exposures through the dietary route with a less burdensome and costly method.

LC-MS/MS-based approach for obtaining exposure estimates of metabolites in early clinical trials using radioactive metabolites as reference standards.

PubMed

Zhang, Donglu; Raghavan, Nirmala; Chando, Theodore; Gambardella, Janice; Fu, Yunlin; Zhang, Duxi; Unger, Steve E; Humphreys, W Griffith

2007-12-01

An LC-MS/MS-based approach that employs authentic radioactive metabolites as reference standards was developed to estimate metabolite exposures in early drug development studies. This method is useful to estimate metabolite levels in studies done with non-radiolabeled compounds where metabolite standards are not available to allow standard LC-MS/MS assay development. A metabolite mixture obtained from an in vivo source treated with a radiolabeled compound was partially purified, quantified, and spiked into human plasma to provide metabolite standard curves. Metabolites were analyzed by LC-MS/MS using the specific mass transitions and an internal standard. The metabolite concentrations determined by this approach were found to be comparable to those determined by valid LC-MS/MS assays. This approach does not requires synthesis of authentic metabolites or the knowledge of exact structures of metabolites, and therefore should provide a useful method to obtain early estimates of circulating metabolites in early clinical or toxicological studies.

Trauma Exposure and Posttraumatic Stress Disorder Among Employees of New York City Companies Affected by the September 11, 2001 Attacks on the World Trade Center

PubMed Central

North, Carol S.; Pollio, David E.; Smith, Rebecca P.; King, Richard V.; Pandya, Anand; Surís, Alina M.; Hong, Barry A.; Dean, Denis J.; Wallace, Nancy E.; Herman, Daniel B.; Conover, Sarah; Susser, Ezra; Pfefferbaum, Betty

2013-01-01

Objective Several studies have provided prevalence estimates of posttraumatic stress disorder (PTSD) related to the September 11, 2001 (9/11) attacks in broadly affected populations, although without sufficiently addressing qualifying exposures required for assessing PTSD and estimating its prevalence. A premise that people throughout the New York City area were exposed to the attacks on the World Trade Center (WTC) towers and are thus at risk for developing PTSD has important implications for both prevalence estimates and service provision. This premise has not, however, been tested with respect to DSM-IV-TR criteria for PTSD. This study examined associations between geographic distance from the 9/11 attacks on the WTC and reported 9/11 trauma exposures, and the role of specific trauma exposures in the development of PTSD. Methods Approximately 3 years after the attacks, 379 surviving employees (102 with direct exposures, including 65 in the towers, and 277 with varied exposures) recruited from 8 affected organizations were interviewed using the Diagnostic Interview Schedule/Disaster Supplement and reassessed at 6 years. The estimated closest geographic distance from the WTC towers during the attacks and specific disaster exposures were compared with the development of 9/11–related PTSD as defined by the Diagnostic and Statistical Manual, Fourth Edition, Text Revision. Results The direct exposure zone was largely concentrated within a radius of 0.1 mi and completely contained within 0.75 mi of the towers. PTSD symptom criteria at any time after the disaster were met by 35% of people directly exposed to danger, 20% of those exposed only through witnessed experiences, and 35% of those exposed only through a close associate’s direct exposure. Outside these exposure groups, few possible sources of exposure were evident among the few who were symptomatic, most of whom had preexisting psychiatric illness. Conclusions Exposures deserve careful consideration among widely affected populations after large terrorist attacks when conducting clinical assessments, estimating the magnitude of population PTSD burdens, and projecting needs for specific mental health interventions. PMID:21900416

Median infectious dose (ID₅₀) of porcine reproductive and respiratory syndrome virus isolate MN-184 via aerosol exposure.

PubMed

Cutler, Timothy D; Wang, Chong; Hoff, Steven J; Kittawornrat, Apisit; Zimmerman, Jeffrey J

2011-08-05

The median infectious dose (ID(50)) of porcine reproductive and respiratory syndrome (PRRS) virus isolate MN-184 was determined for aerosol exposure. In 7 replicates, 3-week-old pigs (n=58) respired 10l of airborne PRRS virus from a dynamic aerosol toroid (DAT) maintained at -4°C. Thereafter, pigs were housed in isolation and monitored for evidence of infection. Infection occurred at virus concentrations too low to quantify by microinfectivity assays. Therefore, exposure dose was determined using two indirect methods ("calculated" and "theoretical"). "Calculated" virus dose was derived from the concentration of rhodamine B monitored over the exposure sequence. "Theoretical" virus dose was based on the continuous stirred-tank reactor model. The ID(50) estimate was modeled on the proportion of pigs that became infected using the probit and logit link functions for both "calculated" and "theoretical" exposure doses. Based on "calculated" doses, the probit and logit ID(50) estimates were 1 × 10(-0.13)TCID(50) and 1 × 10(-0.14)TCID(50), respectively. Based on "theoretical" doses, the probit and logit ID(50) were 1 × 10(0.26)TCID(50) and 1 × 10(0.24)TCID(50), respectively. For each point estimate, the 95% confidence interval included the other three point estimates. The results indicated that MN-184 was far more infectious than PRRS virus isolate VR-2332, the only other PRRS virus isolate for which ID(50) has been estimated for airborne exposure. Since aerosol ID(50) estimates are available for only these two isolates, it is uncertain whether one or both of these isolates represent the normal range of PRRS virus infectivity by this route. Copyright © 2011 Elsevier B.V. All rights reserved.

Comparison of two expert-based assessments of diesel exhaust exposure in a case-control study: Programmable decision rules versus expert review of individual jobs

PubMed Central

Pronk, Anjoeka; Stewart, Patricia A.; Coble, Joseph B.; Katki, Hormuzd A.; Wheeler, David C.; Colt, Joanne S.; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R.; Johnson, Alison; Waddell, Richard; Verrill, Castine; Cherala, Sai; Silverman, Debra T.; Friesen, Melissa C.

2012-01-01

Objectives Professional judgment is necessary to assess occupational exposure in population-based case-control studies; however, the assessments lack transparency and are time-consuming to perform. To improve transparency and efficiency, we systematically applied decision rules to the questionnaire responses to assess diesel exhaust exposure in the New England Bladder Cancer Study, a population-based case-control study. Methods 2,631 participants reported 14,983 jobs; 2,749 jobs were administered questionnaires (‘modules’) with diesel-relevant questions. We applied decision rules to assign exposure metrics based solely on the occupational history responses (OH estimates) and based on the module responses (module estimates); we combined the separate OH and module estimates (OH/module estimates). Each job was also reviewed one at a time to assign exposure (one-by-one review estimates). We evaluated the agreement between the OH, OH/module, and one-by-one review estimates. Results The proportion of exposed jobs was 20–25% for all jobs, depending on approach, and 54–60% for jobs with diesel-relevant modules. The OH/module and one-by-one review had moderately high agreement for all jobs (κw=0.68–0.81) and for jobs with diesel-relevant modules (κw=0.62–0.78) for the probability, intensity, and frequency metrics. For exposed subjects, the Spearman correlation statistic was 0.72 between the cumulative OH/module and one-by-one review estimates. Conclusions The agreement seen here may represent an upper level of agreement because the algorithm and one-by-one review estimates were not fully independent. This study shows that applying decision-based rules can reproduce a one-by-one review, increase transparency and efficiency, and provide a mechanism to replicate exposure decisions in other studies. PMID:22843440

Comparison of exposure assessment methods in a lung cancer case-control study: performance of a lifelong task-based questionnaire for asbestos and PAHs.

PubMed

Bourgkard, Eve; Wild, Pascal; Gonzalez, Maria; Févotte, Joëlle; Penven, Emmanuelle; Paris, Christophe

2013-12-01

To describe the performance of a lifelong task-based questionnaire (TBQ) in estimating exposures compared with other approaches in the context of a case-control study. A sample of 93 subjects was randomly selected from a lung cancer case-control study corresponding to 497 jobs. For each job, exposure assessments for asbestos and polycyclic aromatic hydrocarbons (PAHs) were obtained by expertise (TBQ expertise) and by algorithm using the TBQ (TBQ algorithm) as well as by expert appraisals based on all available occupational data (REFERENCE expertise) considered to be the gold standard. Additionally, a Job Exposure Matrix (JEM)-based evaluation for asbestos was also obtained. On the 497 jobs, the various evaluations were contrasted using Cohen's κ coefficient of agreement. Additionally, on the total case-control population, the asbestos dose-response relationship based on the TBQ algorithm was compared with the JEM-based assessment. Regarding asbestos, the TBQ-exposure estimates agreed well with the REFERENCE estimate (TBQ expertise: level-weighted κ (lwk)=0.68; TBQ algorithm: lwk=0.61) but less so with the JEM estimate (TBQ expertise: lwk=0.31; TBQ algorithm: lwk=0.26). Regarding PAHs, the agreements between REFERENCE expertise and TBQ were less good (TBQ expertise: lwk=0.43; TBQ algorithm: lwk=0.36). In the case-control study analysis, the dose-response relationship between lung cancer and cumulative asbestos based on the JEM is less steep than with the TBQ-algorithm exposure assessment and statistically non-significant. Asbestos-exposure estimates based on the TBQ were consistent with the REFERENCE expertise and yielded a steeper dose-response relationship than the JEM. For PAHs, results were less clear.

Health-care workers’ occupational exposures to body fluids in 21 countries in Africa: systematic review and meta-analysis

PubMed Central

Adewuyi, Emmanuel O; Tor-Anyiin, Amom; Aziz, David; Ogbole, Esther; Ogbonna, Brian O; Adeloye, Davies

2017-01-01

Abstract Objective To estimate the lifetime and 12-month prevalence of occupational exposure to body fluids among health-care workers in Africa. Methods Embase®, PubMed® and CINAHL databases were systematically searched for studies published between January 2000 and August 2017 that reported the prevalence of occupational exposure to blood or other body fluids among health-care workers in Africa. The continent-wide prevalence of exposure was estimated using random-effects meta-analysis. Findings Of the 904 articles identified, 65 studies from 21 African countries were included. The estimated pooled lifetime and 12-month prevalence of occupational exposure to body fluids were 65.7% (95% confidence interval, CI: 59.7–71.6) and 48.0% (95% CI: 40.7–55.3), respectively. Exposure was largely due to percutaneous injury, which had an estimated 12-month prevalence of 36.0% (95% CI: 31.2–40.8). The pooled 12-month prevalence of occupational exposure among medical doctors (excluding surgeons), nurses (including midwives and nursing assistants) and laboratory staff (including laboratory technicians) was 46.6% (95% CI: 33.5–59.7), 44.6% (95% CI: 34.1–55.0) and 34.3% (95% CI: 21.8–46.7), respectively. The risk of exposure was higher among health-care workers with no training on infection prevention and those who worked more than 40 hours per week. Conclusion The evidence available suggests that almost one half of health-care workers in Africa were occupationally exposed to body fluids annually. However, a lack of data from some countries was a major limitation. National governments and health-care institutions across Africa should prioritize efforts to minimize occupational exposure among health-care workers. PMID:29200524

Cytogenetic Reconstruction of Gamma-Ray Doses Delivered to Atomic Bomb Survivors: Dealing with Wide Distributions of Photon Energies and Contributions from Hematopoietic Stem/Progenitor Cells.

PubMed

Nakamura, Nori; Hirai, Yuko; Kodama, Yoshiaki; Hamasaki, Kanya; Cullings, Harry M; Cordova, Kismet A; Awa, Akio

2017-10-01

Retrospective estimation of the doses received by atomic bomb (A-bomb) survivors by cytogenetic methods has been hindered by two factors: One is that the photon energies released from the bomb were widely distributed, and since the aberration yield varies depending on the energy, the use of monoenergetic 60 Co gamma radiation to construct a calibration curve may bias the estimate. The second problem is the increasing proportion of newly formed lymphocytes entering into the lymphocyte pool with increasing time intervals since the exposures. These new cells are derived from irradiated precursor/stem cells whose radiosensitivity may differ from that of blood lymphocytes. To overcome these problems, radiation doses to tooth enamel were estimated using the electron spin resonance (ESR; or EPR, electron paramagnetic resonance) method and compared with the cytogenetically estimated doses from the same survivors. The ESR method is only weakly dependent on the photon energy and independent of the years elapsed since an exposure. Both ESR and cytogenetic doses were estimated from 107 survivors. The latter estimates were made by assuming that although a part of the cells examined could be lymphoid stem or precursor cells at the time of exposure, all the cells had the same radiosensitivity as blood lymphocytes, and that the A-bomb gamma-ray spectrum was the same as that of the 60 Co gamma rays. Subsequently, ESR and cytogenetic endpoints were used to estimate the kerma doses using individual DS02R1 information on shielding conditions. The results showed that the two sets of kerma doses were in close agreement, indicating that perhaps no correction is needed in estimating atomic bomb gamma-ray doses from the cytogenetically estimated 60 Co gamma-ray equivalent doses. The present results will make it possible to directly compare cytogenetic doses with the physically estimated doses of the survivors, which would pave the way for testing whether or not there are any systematic trends or factors affecting physically estimated doses.

High throughput heuristics for prioritizing human exposure to environmental chemicals.

PubMed

Wambaugh, John F; Wang, Anran; Dionisio, Kathie L; Frame, Alicia; Egeghy, Peter; Judson, Richard; Setzer, R Woodrow

2014-11-04

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understanding of health risks. We aim to develop a rapid heuristic method to determine potential human exposure to chemicals for application to the thousands of chemicals with little or no exposure data. We used Bayesian methodology to infer ranges of exposure consistent with biomarkers identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We performed linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using chemical descriptors and use information from multiple databases and structure-based calculators. Five descriptors are capable of explaining roughly 50% of the variability in geometric means across 106 NHANES chemicals for all the demographic groups, including children aged 6-11. We use these descriptors to estimate human exposure to 7968 chemicals, the majority of which have no other quantitative exposure prediction. For thousands of chemicals with no other information, this approach allows forecasting of average exposure intake of environmental chemicals.

Static and elevated pollen traps do not provide an accurate assessment of personal pollen exposure.

PubMed

Penel, V; Calleja, M; Pichot, C; Charpin, D

2017-03-01

Background. Volumetric pollen traps are commonly used to assess pollen exposure. These traps are well suited for estimating the regional mean airborne pollen concentration but are likely not to provide an accurate index of personal exposure. In this study, we tested the hypothesis that hair sampling may provide different pollen counts from those from pollen traps, especially when the pollen exposure is diverse. Methods. We compared pollen counts in hair washes to counts provided by stationary volumetric and gravimetric pollen traps in 2 different settings: urban with volunteers living in short distance from one another and from the static trap and suburban in which volunteers live in a scattered environment, quite far from the static trap. Results. Pollen counts in hair washes are in full agreement with trap counts for uniform pollen exposure. In contrast, for diverse pollen exposure, .individual pollen counts in hair washes vary strongly in quantity and taxa composition between individuals and dates. These results demonstrate that the pollen counts method (hair washes vs. stationary pollen traps) may lead to different absolute and relative contributions of taxa to the total pollen count. Conclusions. In a geographic area with a high diversity of environmental exposure to pollen, static pollen traps, in contrast to hair washes, do not provide a reliable estimate of this higher diversity.

Styrene-Associated Health Outcomes at a Windblade Manufacturing Plant

PubMed Central

McCague, Anna-Binney; Cox-Ganser, Jean M.; Harney, Joshua M.; Alwis, K. Udeni; Blount, Benjamin C.; Cummings, Kristin J.; Edwards, Nicole; Kreiss, Kathleen

2015-01-01

Background Health risks of using styrene to manufacture windblades for the green energy sector are unknown. Methods Using data collected from 355 (73%) current windblade workers and regression analysis, we investigated associations between health outcomes and styrene exposure estimates derived from urinary styrene metabolites. Results The median current styrene exposure was 53.6 mg/g creatinine (interquartile range: 19.5–94.4). Color blindness in men and women (standardized morbidity ratios 2.3 and 16.6, respectively) was not associated with exposure estimates, but was the type previously reported with styrene. Visual contrast sensitivity decreased and chest tightness increased (odds ratio 2.9) with increasing current exposure. Decreases in spirometric parameters and FeNO, and increases in the odds of wheeze and asthma-like symptoms (odds ratios 1.3 and 1.2, respectively) occurred with increasing cumulative exposure. Conclusions Despite styrene exposures below the recommended 400 mg/g creatinine, visual and respiratory effects indicate the need for additional preventative measures in this industry. PMID:26305283

Temporal Variability of Pesticide Concentrations in Homes and Implications for Attenuation Bias in Epidemiologic Studies

PubMed Central

Ward, Mary H.; Bell, Erin M.; Whitehead, Todd P.; Gunier, Robert B.; Friesen, Melissa C.; Nuckols, John R.

2013-01-01

Background: Residential pesticide exposure has been linked to adverse health outcomes in adults and children. High-quality exposure estimates are critical for confirming these associations. Past epidemiologic studies have used one measurement of pesticide concentrations in carpet dust to characterize an individual’s average long-term exposure. If concentrations vary over time, this approach could substantially misclassify exposure and attenuate risk estimates. Objectives: We assessed the repeatability of pesticide concentrations in carpet dust samples and the potential attenuation bias in epidemiologic studies relying on one sample. Methods: We collected repeated carpet dust samples (median = 3; range, 1–7) from 21 homes in Fresno County, California, during 2003–2005. Dust was analyzed for 13 pesticides using gas chromatography–mass spectrometry. We used mixed-effects models to estimate between- and within-home variance. For each pesticide, we computed intraclass correlation coefficients (ICCs) and the estimated attenuation of regression coefficients in a hypothetical case–control study collecting a single dust sample. Results: The median ICC was 0.73 (range, 0.37–0.95), demonstrating higher between-home than within-home variability for most pesticides. The expected magnitude of attenuation bias associated with using a single dust sample was estimated to be ≤ 30% for 7 of the 13 compounds evaluated. Conclusions: For several pesticides studied, use of one dust sample to represent an exposure period of approximately 2 years would not be expected to substantially attenuate odds ratios. Further study is needed to determine if our findings hold for longer exposure periods and for other pesticides. PMID:23462689

Risk of Skin Cancer from Space Radiation. Chapter 11

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Kim, Myung-Hee Y.; George, Kerry A.; Wu, Hong-Lu

2003-01-01

We review the methods for estimating the probability of increased incidence of skin cancers from space radiation exposure, and describe some of the individual factors that may contribute to risk projection models, including skin pigment, and synergistic effects of combined ionizing and UV exposure. The steep dose gradients from trapped electrons, protons, and heavy ions radiation during EVA and limitations in EVA dosimetry are important factors for projecting skin cancer risk of astronauts. We estimate that the probability of increased skin cancer risk varies more than 10-fold for individual astronauts and that the risk of skin cancer could exceed 1 % for future lunar base operations for astronauts with light skin color and hair. Limitations in physical dosimetry in estimating the distribution of dose at the skin suggest that new biodosimetry methods be developed for responding to accidental overexposure of the skin during future space missions.

Evaluation of Specific Absorption Rate as a Dosimetric Quantity for Electromagnetic Fields Bioeffects

PubMed Central

Panagopoulos, Dimitris J.; Johansson, Olle; Carlo, George L.

2013-01-01

Purpose To evaluate SAR as a dosimetric quantity for EMF bioeffects, and identify ways for increasing the precision in EMF dosimetry and bioactivity assessment. Methods We discuss the interaction of man-made electromagnetic waves with biological matter and calculate the energy transferred to a single free ion within a cell. We analyze the physics and biology of SAR and evaluate the methods of its estimation. We discuss the experimentally observed non-linearity between electromagnetic exposure and biological effect. Results We find that: a) The energy absorbed by living matter during exposure to environmentally accounted EMFs is normally well below the thermal level. b) All existing methods for SAR estimation, especially those based upon tissue conductivity and internal electric field, have serious deficiencies. c) The only method to estimate SAR without large error is by measuring temperature increases within biological tissue, which normally are negligible for environmental EMF intensities, and thus cannot be measured. Conclusions SAR actually refers to thermal effects, while the vast majority of the recorded biological effects from man-made non-ionizing environmental radiation are non-thermal. Even if SAR could be accurately estimated for a whole tissue, organ, or body, the biological/health effect is determined by tiny amounts of energy/power absorbed by specific biomolecules, which cannot be calculated. Moreover, it depends upon field parameters not taken into account in SAR calculation. Thus, SAR should not be used as the primary dosimetric quantity, but used only as a complementary measure, always reporting the estimating method and the corresponding error. Radiation/field intensity along with additional physical parameters (such as frequency, modulation etc) which can be directly and in any case more accurately measured on the surface of biological tissues, should constitute the primary measure for EMF exposures, in spite of similar uncertainty to predict the biological effect due to non-linearity. PMID:23750202

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

[Analysis of phthalates in aromatic and deodorant aerosol products and evaluation of exposure risk].

PubMed

Sato, Yoshiki; Sugaya, Naeko; Nakagawa, Tomoo; Morita, Masatoshi

2015-01-01

We established an analytical method for the detection of seven phthalates, dimethyl phthalate, diethyl phthalate (DEP), benzyl butyl phthalate, di-i-butyl phthalate, dibutyl phthalate (DBP), diethylhexyl phthalate (DEHP), and di-n-octhyl phthalate, using an ultra high performance liquid chromatograph equipped with a photodiode array detector. This method is quick, with minimal contamination, and was applied to the analysis of aromatic and deodorant aerosol products. Phthalates were detected in 15 of 52 samples purchased from 1999 to 2012 in Yokohama. Three types of phthalate (DEP, DBP, DEHP) were detected, and their concentrations ranged from 0.0085-0.23% DEP in nine samples, 0.012-0.045% DBP in four samples, and 0.012-0.033% DEHP in four samples. No other phthalate esters were detected. Furthermore, we estimated phthalate exposure via breathing in commonly used aromatic and deodorant aerosol products, then evaluated the associated risk. The estimated levels of phthalate exposure were lower than the tolerated daily limit, but the results indicated that aromatic and deodorant aerosol products could be a significant source of phthalate exposure.

Evaluation of field methods for estimating exposure of children in low-income families to polycyclic aromatic hydrocarbons

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

Wilson, N.K.; Chuang, J.C.; Lyu, C.

1996-12-31

Children in low-income families may have higher exposures to polycyclic aromatic hydrocarbons (PAH) and related compounds than children in higher-income families. These higher exposures could result from the location of their homes, nearer to industrial sites and traffic; from poorer diet; from environmental tobacco smoke; or other causes. The study was designed to evaluate methods and estimate the range of total exposures of low-income children to PAH through various pathways. Nonsmoking participants with preschool children, incomes at or below the official US poverty level, and space heating in their homes were recruited. The PAH concentrations were measured in the householdmore » indoor and outdoor air, house dust, and yard soil, and in the diet of both an adult and a preschool child living in the home. An initial study in two homes and an additional study of nine homes, four urban and five rural, during the heating season were completed. The problems and successes encountered in the recruitment process and selected results of the heating season measurements are summarized in the paper.« less

SYN-JEM: A Quantitative Job-Exposure Matrix for Five Lung Carcinogens.

PubMed

Peters, Susan; Vermeulen, Roel; Portengen, Lützen; Olsson, Ann; Kendzia, Benjamin; Vincent, Raymond; Savary, Barbara; Lavoué, Jérôme; Cavallo, Domenico; Cattaneo, Andrea; Mirabelli, Dario; Plato, Nils; Fevotte, Joelle; Pesch, Beate; Brüning, Thomas; Straif, Kurt; Kromhout, Hans

2016-08-01

The use of measurement data in occupational exposure assessment allows more quantitative analyses of possible exposure-response relations. We describe a quantitative exposure assessment approach for five lung carcinogens (i.e. asbestos, chromium-VI, nickel, polycyclic aromatic hydrocarbons (by its proxy benzo(a)pyrene (BaP)) and respirable crystalline silica). A quantitative job-exposure matrix (JEM) was developed based on statistical modeling of large quantities of personal measurements. Empirical linear models were developed using personal occupational exposure measurements (n = 102306) from Europe and Canada, as well as auxiliary information like job (industry), year of sampling, region, an a priori exposure rating of each job (none, low, and high exposed), sampling and analytical methods, and sampling duration. The model outcomes were used to create a JEM with a quantitative estimate of the level of exposure by job, year, and region. Decreasing time trends were observed for all agents between the 1970s and 2009, ranging from -1.2% per year for personal BaP and nickel exposures to -10.7% for asbestos (in the time period before an asbestos ban was implemented). Regional differences in exposure concentrations (adjusted for measured jobs, years of measurement, and sampling method and duration) varied by agent, ranging from a factor 3.3 for chromium-VI up to a factor 10.5 for asbestos. We estimated time-, job-, and region-specific exposure levels for four (asbestos, chromium-VI, nickel, and RCS) out of five considered lung carcinogens. Through statistical modeling of large amounts of personal occupational exposure measurement data we were able to derive a quantitative JEM to be used in community-based studies. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Development of a Job-Task-Exposure Matrix to assess occupational exposure to disinfectants among U.S. nurses

PubMed Central

Quinot, C; Dumas, O; Henneberger, PK; Varraso, R; Wiley, AS; Speizer, FE; Goldberg, M; Zock, JP; Camargo, CA; Le Moual, N

2016-01-01

Objectives Occupational exposure to disinfectants is associated with work-related asthma, especially in healthcare workers. However, little is known about the specific products involved. To evaluate disinfectant exposures, we designed job-exposure (JEM) and job-task-exposure (JTEM) matrices, which are thought to be less prone to differential misclassification bias than self-reported exposure. We then compared the three assessment methods: self-reported exposure, JEM, and JTEM. Methods Disinfectant use was assessed by an occupational questionnaire in 9,073 U.S. female registered nurses without asthma, aged 49–68 years, drawn from the Nurses’ Health Study II. A JEM was created based on self-reported frequency of use (1–3, 4–7 days/week) of 7 disinfectants and sprays in 8 nursing jobs. We then created a JTEM combining jobs and disinfection tasks to further reduce misclassification. Exposure was evaluated in 3 classes (low, medium, high) using product-specific cut-offs (e.g., <30%, 30–49.9%, ≥50%, respectively, for alcohol); the cut-offs were defined from the distribution of self-reported exposure per job/task. Results The most frequently reported disinfectants were alcohol (weekly use: 39%), bleach (22%) and sprays (20%). More nurses were classified as highly exposed by JTEM (alcohol 41%, sprays 41%, bleach 34%) than by JEM (21%, 30%, 26%, respectively). Agreement between JEM and JTEM was fair-to-moderate (kappa: 0.3–0.5) for most disinfectants. JEM and JTEM exposure estimates were heterogeneous in most nursing jobs, except in emergency room and education/administration. Conclusion The JTEM may provide more accurate estimates than the JEM, especially for nursing jobs with heterogeneous tasks. Use of the JTEM is likely to reduce exposure misclassification. PMID:27566782

Constructing inverse probability weights for continuous exposures: a comparison of methods.

PubMed

Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S

2014-03-01

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

ESTIMATING SOLAR RADIATION EXPOSURE IN WETLANDS USING RADIATION MODELS, FIELD DATA, AND GEOGRAPHIC INFORMATION SYSTEMS

EPA Science Inventory

This seminar will describe development of methods for the estimation of solar radiation doses in wetlands. The methodology presents a novel approach to incorporating aspects of solar radiation dosimetry that have historically received limited attention. These include effects of a...

Combining a Job-Exposure Matrix with Exposure Measurements to Assess Occupational Exposure to Benzene in a Population Cohort in Shanghai, China

PubMed Central

Friesen, Melissa C.; Coble, Joseph B.; Lu, Wei; Shu, Xiao-Ou; Ji, Bu-Tian; Xue, Shouzheng; Portengen, Lutzen; Chow, Wong-Ho; Gao, Yu-Tang; Yang, Gong; Rothman, Nathaniel; Vermeulen, Roel

2012-01-01

Background: Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone. Methods: We combined 63 221 short-term area air measurements of benzene exposure (1954–2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0–3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942). Results: Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, BGR95B: 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, rp = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (rp = 0.88). Conclusions: We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups’ exposure levels to deviate from the pooled average for their respective JEM intensity ratings. PMID:21976309

The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States

PubMed Central

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L.

2013-01-01

Geostatistical methods are widely used in estimating long-term exposures for air pollution epidemiological studies, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian Maximum Entropy (BME) method and applied this framework to estimate fine particulate matter (PM2.5) yearly average concentrations over the contiguous U.S. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingnees in the air monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM2.5 data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM2.5. Moreover, the MWBME method further reduces the MSE by 8.4% to 43.7% with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM2.5 across large geographical domains with expected spatial non-stationarity. PMID:22739679

Modelling the variation of land surface temperature as determinant of risk of heat-related health events

PubMed Central

2011-01-01

Background The evaluation of exposure to ambient temperatures in epidemiological studies has generally been based on records from meteorological stations which may not adequately represent local temperature variability. Here we propose a spatially explicit model to estimate local exposure to temperatures of large populations under various meteorological conditions based on satellite and meteorological data. Methods A general linear model was used to estimate surface temperatures using 15 LANDSAT 5 and LANDSAT 7 images for Quebec Province, Canada between 1987 and 2002 and spanning the months of June to August. The images encompassed both rural and urban landscapes and predictors included: meteorological records of temperature and wind speed, distance to major water bodies, Normalized Differential Vegetation Index (NDVI), land cover (built and bare land, water, or vegetation), latitude, longitude, and week of the year. Results The model explained 77% of the variance in surface temperature, accounting for both temporal and spatial variations. The standard error of estimates was 1.42°C. Land cover and NDVI were strong predictors of surface temperature. Conclusions This study suggests that a statistical approach to estimating surface temperature incorporating both spatially explicit satellite data and time-varying meteorological data may be relevant to assessing exposure to heat during the warm season in the Quebec. By allowing the estimation of space- and time-specific surface temperatures, this model may also be used to assess the possible impacts of land use changes under various meteorological conditions. It can be applied to assess heat exposure within a large population and at relatively fine-grained scale. It may be used to evaluate the acute health effect of heat exposure over long time frames. The method proposed here could be replicated in other areas around the globe for which satellite data and meteorological data is available. PMID:21251286

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.

Estimated dose rates to members of the public from external exposure to patients with 131I thyroid treatment

DOE PAGES

Dewji, S.; Bellamy, M.; Hertel, N.; ...

2015-03-25

The purpose of this study is to estimate dose rates that may result from exposure to patients who had been administered iodine-131 ( 131I) as part of medical therapy were calculated. These effective dose rate estimates were compared with simplified assumptions under United States Nuclear Regulatory Commission Regulatory Guide 8.39, which does not consider body tissue attenuation nor time-dependent redistribution and excretion of the administered 131I. Methods: Dose rates were estimated for members of the public potentially exposed to external irradiation from patients recently treated with 131I. Tissue attenuation and iodine biokinetics were considered in the patient in a largermore » comprehensive effort to improve external dose rate estimates. The external dose rate estimates are based on Monte Carlo simulations using the Phantom with Movable Arms and Legs (PIMAL), previously developed by Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission. PIMAL was employed to model the relative positions of the 131I patient and members of the public in three exposure scenarios: (1) traveling on a bus in a total of six seated or standing permutations, (2) two nursing home cases where a caregiver is seated at 30 cm from the patient’s bedside and a nursing home resident seated 250 cm away from the patient in an adjacent bed, and (3) two hotel cases where the patient and a guest are in adjacent rooms with beds on opposite sides of the common wall, with the patient and guest both in bed and either seated back-to-back or lying head to head. The biokinetic model predictions of the retention and distribution of 131I in the patient assumed a single voiding of urinary bladder contents that occurred during the trip at 2, 4, or 8 h after 131I administration for the public transportation cases, continuous first-order voiding for the nursing home cases, and regular periodic voiding at 4, 8, or 12 h after administration for the hotel room cases. Organ specific activities of 131I in the thyroid, bladder, and combined remaining tissues were calculated as a function of time after administration. Exposures to members of the public were considered for 131I patients with normal thyroid uptake (peak thyroid uptake of ~27% of administered 131I), differentiated thyroid cancer (DTC, 5% uptake), and hyperthyroidism (80% uptake). Results: The scenario with the patient seated behind the member of the public yielded the highest dose rate estimate of seated public transportation exposure cases. The dose rate to the adjacent room guest was highest for the exposure scenario in which the hotel guest and patient are seated by a factor of ~4 for the normal and differentiated thyroid cancer uptake cases and by a factor of ~3 for the hyperthyroid case. Conclusions: It was determined that for all modeled cases, the DTC case yielded the lowest external dose rates, whereas the hyperthyroid case yielded the highest dose rates. In estimating external dose to members of the public from patients with 131I therapy, consideration must be given to (patient- and case-specific) administered 131I activities and duration of exposure for a more complete estimate. The method implemented here included a detailed calculation model, which provides a means to determine dose rate estimates for a range of scenarios. Finally, the method was demonstrated for variations of three scenarios, showing how dose rates are expected to vary with uptake, voiding pattern, and patient location.« less

Estimated dose rates to members of the public from external exposure to patients with 131I thyroid treatment

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

Dewji, S.; Bellamy, M.; Hertel, N.

The purpose of this study is to estimate dose rates that may result from exposure to patients who had been administered iodine-131 ( 131I) as part of medical therapy were calculated. These effective dose rate estimates were compared with simplified assumptions under United States Nuclear Regulatory Commission Regulatory Guide 8.39, which does not consider body tissue attenuation nor time-dependent redistribution and excretion of the administered 131I. Methods: Dose rates were estimated for members of the public potentially exposed to external irradiation from patients recently treated with 131I. Tissue attenuation and iodine biokinetics were considered in the patient in a largermore » comprehensive effort to improve external dose rate estimates. The external dose rate estimates are based on Monte Carlo simulations using the Phantom with Movable Arms and Legs (PIMAL), previously developed by Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission. PIMAL was employed to model the relative positions of the 131I patient and members of the public in three exposure scenarios: (1) traveling on a bus in a total of six seated or standing permutations, (2) two nursing home cases where a caregiver is seated at 30 cm from the patient’s bedside and a nursing home resident seated 250 cm away from the patient in an adjacent bed, and (3) two hotel cases where the patient and a guest are in adjacent rooms with beds on opposite sides of the common wall, with the patient and guest both in bed and either seated back-to-back or lying head to head. The biokinetic model predictions of the retention and distribution of 131I in the patient assumed a single voiding of urinary bladder contents that occurred during the trip at 2, 4, or 8 h after 131I administration for the public transportation cases, continuous first-order voiding for the nursing home cases, and regular periodic voiding at 4, 8, or 12 h after administration for the hotel room cases. Organ specific activities of 131I in the thyroid, bladder, and combined remaining tissues were calculated as a function of time after administration. Exposures to members of the public were considered for 131I patients with normal thyroid uptake (peak thyroid uptake of ~27% of administered 131I), differentiated thyroid cancer (DTC, 5% uptake), and hyperthyroidism (80% uptake). Results: The scenario with the patient seated behind the member of the public yielded the highest dose rate estimate of seated public transportation exposure cases. The dose rate to the adjacent room guest was highest for the exposure scenario in which the hotel guest and patient are seated by a factor of ~4 for the normal and differentiated thyroid cancer uptake cases and by a factor of ~3 for the hyperthyroid case. Conclusions: It was determined that for all modeled cases, the DTC case yielded the lowest external dose rates, whereas the hyperthyroid case yielded the highest dose rates. In estimating external dose to members of the public from patients with 131I therapy, consideration must be given to (patient- and case-specific) administered 131I activities and duration of exposure for a more complete estimate. The method implemented here included a detailed calculation model, which provides a means to determine dose rate estimates for a range of scenarios. Finally, the method was demonstrated for variations of three scenarios, showing how dose rates are expected to vary with uptake, voiding pattern, and patient location.« less

Incorporating High-Dimensional Exposure Modelling into Studies of Air Pollution and Health.

PubMed

Liu, Yi; Shaddick, Gavin; Zidek, James V

2017-01-01

Performing studies on the risks of environmental hazards on human health requires accurate estimates of exposures that might be experienced by the populations at risk. Often there will be missing data and in many epidemiological studies, the locations and times of exposure measurements and health data do not match. To a large extent this will be due to the health and exposure data having arisen from completely different data sources and not as the result of a carefully designed study, leading to problems of both 'change of support' and 'misaligned data'. In such cases, a direct comparison of the exposure and health outcome is often not possible without an underlying model to align the two in the spatial and temporal domains. The Bayesian approach provides the natural framework for such models; however, the large amounts of data that can arise from environmental networks means that inference using Markov Chain Monte Carlo might not be computationally feasible in this setting. Here we adapt the integrated nested Laplace approximation to implement spatio-temporal exposure models. We also propose methods for the integration of large-scale exposure models and health analyses. It is important that any model structure allows the correct propagation of uncertainty from the predictions of the exposure model through to the estimates of risk and associated confidence intervals. The methods are demonstrated using a case study of the levels of black smoke in the UK, measured over several decades, and respiratory mortality.

PROGRAM PARAMS USERS GUIDE

EPA Science Inventory

PARAMS is a Windows-based computer program that implements 30 methods for estimating the parameters in indoor emissions source models, which are an essential component of indoor air quality (IAQ) and exposure models. These methods fall into eight categories: (1) the properties o...

Improving Assessment of Lifetime Solar Ultraviolet Radiation Exposure in Epidemiologic Studies: Comparison of Ultraviolet Exposure Assessment Methods in a Nationwide United States Occupational Cohort.

PubMed

Little, Mark P; Tatalovich, Zaria; Linet, Martha S; Fang, Michelle; Kendall, Gerald M; Kimlin, Michael G

2018-06-13

Solar ultraviolet radiation is the primary risk factor for skin cancers and sun-related eye disorders. Estimates of individual ambient ultraviolet irradiance derived from ground-based solar measurements and from satellite measurements have rarely been compared. Using self-reported residential history from 67,189 persons in a nationwide occupational US radiologic technologists cohort, we estimated ambient solar irradiance using data from ground-based meters and noontime satellite measurements. The mean distance-moved from city of longest residence in childhood increased from 137.6 km at ages 13-19 to 870.3 km at ages ≥65, with corresponding increases in absolute latitude-difference moved. At ages 20/40/60/80, the Pearson/Spearman correlation coefficients of ground-based and satellite-derived solar potential ultraviolet exposure, using irradiance and cumulative radiant-exposure metrics, were high (=0.87-0.92). There was also moderate correlation (Pearson/Spearman correlation coefficients=0.51-0.60) between irradiance at birth and at last-known address, for ground-based and satellite data. Satellite-based lifetime estimates of ultraviolet radiation were generally 14-15% lower than ground-based estimates, albeit with substantial uncertainties, possibly because ground-based estimates incorporate fluctuations in cloud and ozone, which are incompletely incorporated in the single noontime satellite-overpass ultraviolet value. If confirmed elsewhere, the findings suggest that ground-based estimates may improve exposure-assessment accuracy and potentially provide new insights into ultraviolet-radiation-disease relationships in epidemiologic studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Occupational exposure to magnetic fields in relation to mortality from brain cancer among electricity generation and transmission workers.

PubMed Central

Harrington, J M; McBride, D I; Sorahan, T; Paddle, G M; van Tongeren, M

1997-01-01

OBJECTIVE: To investigate whether the risks of mortality from brain cancer are related to occupational exposure to magnetic fields. METHODS: A total of 112 cases of primary brain cancer (1972-91) were identified from a cohort of 84,018 male and female employees of the (then) Central Electricity Generating Board and its privatised successor companies. Individual cumulative occupational exposures to magnetic fields were estimated by linking available computerised job history data with magnetic field measurements collected over 675 person-workshifts. Estimated exposure histories of the case workers were compared with those of 654 control workers drawn from the cohort (nested case-control study), by means of conditional logistic regression. RESULTS: For exposure assessments based on arithmetic means, the risk of mortality from brain cancer for subjects with an estimated cumulative exposure to magnetic fields of 5.4-13.4 microT.y v subjects with lower exposures (0.0-5.3 microT.y) was 1.04 (95% confidence interval (95% CI) 0.60 to 1.80). The corresponding relative risk in subjects with higher exposures (> or = 13.5 microT.y) was 0.95 (95% CI 0.54 to 1.69). There was no indication of a positive trend for cumulative exposure and risk of mortality from brain cancer either when the analysis used exposure assessments based on geometric means or when the analysis was restricted to exposures received within five years of the case diagnosis (or corresponding period for controls). CONCLUSIONS: Although the exposure categorisation was based solely on recent observations, the study findings do not support the hypothesis that the risk of brain cancer is associated with occupational exposure to magnetic fields. PMID:9072027

INTEROCC case–control study: lack of association between glioma tumors and occupational exposure to selected combustion products, dusts and other chemical agents

PubMed Central

2013-01-01

Background The aim was to investigate possible associations between glioma (an aggressive type of brain cancer) and occupational exposure to selected agents: combustion products (diesel and gasoline exhaust emissions, benzo(a)pyrene), dusts (animal dust, asbestos, crystalline silica, wood dust) and some other chemical agents (formaldehyde, oil mist, sulphur dioxide). Methods The INTEROCC study included cases diagnosed with glioma during 2000–2004 in sub-regions of seven countries. Population controls, selected from various sampling frames in different centers, were frequency or individually matched to cases by sex, age and center. Face-to-face interviews with the subject or a proxy respondent were conducted by trained interviewers. Detailed information was collected on socio-economic and lifestyle characteristics, medical history and work history. Occupational exposure to the 10 selected agents was assessed by a job exposure matrix (JEM) which provides estimates of the probability and level of exposure for different occupations. Using a 25% probability of exposure in a given occupation in the JEM as the threshold for considering a worker exposed, the lifetime prevalence of exposure varied from about 1% to about 15% for the different agents. Associations between glioma and each of the 10 agents were estimated by conditional logistic regression, and using three separate exposure indices: i) ever vs. never; ii) lifetime cumulative exposure; iii) total duration of exposure. Results The study sample consisted of 1,800 glioma cases and 5,160 controls. Most odds ratio estimates were close to the null value. None of the ten agents displayed a significantly increased odds ratio nor any indication of dose–response relationships with cumulative exposure or with duration of exposure. Conclusion Thus, there was no evidence that these exposures influence risk of glioma. PMID:23587105

Exposure assessment for a nested case-control study of lung cancer among European asphalt workers.

PubMed

Agostini, Michela; Ferro, Gilles; Olsson, Ann; Burstyn, Igor; De Vocht, Frank; Hansen, Johnni; Lassen, Christina Funch; Johansen, Christoffer; Kjaerheim, Kristina; Langard, Sverre; Stucker, Isabelle; Ahrens, Wolfgang; Behrens, Thomas; Lindbohm, Marja-Liisa; Heikkilä, Pirjo; Heederik, Dick; Portengen, Lützen; Shaham, Judith; Boffetta, Paolo; Kromhout, Hans

2010-10-01

Development of a method for retrospective assessment of exposure to bitumen fume, bitumen condensate, organic vapour, polycyclic aromatic hydrocarbons, and co-exposures to known or suspected lung carcinogens for a nested case-control study of lung cancer mortality among European asphalt workers. Company questionnaires and structured questionnaires used in interviews and industry-specific job-exposure matrices (JEMs) were elaborated and applied. Three sources of information were eventually used for exposure assessment and assignment: (i) data obtained in cohort phase, (ii) data from living subjects, next-of-kin, and fellow-workers questionnaires, and (iii) JEMs for bitumen exposure by inhalation and via skin and co-exposures to known or suspected lung carcinogens within and outside cohort companies. Inhalation and dermal exposure estimates for bitumen were adjusted for time trends, time spent in a job, and other determinants of exposure (e.g. oil gravel paving). Clothing patterns, personal protective devices, and personal hygiene were taken into consideration while estimating dermal exposure. Occupational exposures could be assessed for 433 cases and 1253 controls for relevant time periods. Only 43% of work histories were spent inside original asphalt and construction companies. A total of 95.8% of job periods in cohort companies could be coded at a more detailed level. Imputation of work time and 'hygienic behaviour' multipliers was needed for <10% of work history years. Overall, downward trends in exposure were present and differences existed between countries and companies. As expected, correlations were strongest (r > 0.7) among bitumen-related agents, while correlations between coal tar, bitumen-related agents, and established lung carcinogens were weaker (r < 0.4). A systematic and detailed approach was developed to estimate inhalation and dermal exposure for a nested case-control study among asphalt workers.

A motion deblurring method with long/short exposure image pairs

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Hua, Weiping; Zhao, Jufeng; Gong, Xiaoli; Zhu, Liyao

2018-01-01

In this paper, a motion deblurring method with long/short exposure image pairs is presented. The long/short exposure image pairs are captured for the same scene under different exposure time. The image pairs are treated as the input of the deblurring method and more information could be used to obtain a deblurring result with high image quality. Firstly, the luminance equalization process is carried out to the short exposure image. And the blur kernel is estimated with the image pair under the maximum a posteriori (MAP) framework using conjugate gradient algorithm. Then a L0 image smoothing based denoising method is applied to the luminance equalized image. And the final deblurring result is obtained with the gain controlled residual image deconvolution process with the edge map as the gain map. Furthermore, a real experimental optical system is built to capture the image pair in order to demonstrate the effectiveness of the proposed deblurring framework. The long/short image pairs are obtained under different exposure time and camera gain control. Experimental results show that the proposed method could provide a superior deblurring result in both subjective and objective assessment compared with other deblurring approaches.

Estimating the extent and distribution of new-onset adult asthma in British Columbia using frequentist and Bayesian approaches.

PubMed

Beach, Jeremy; Burstyn, Igor; Cherry, Nicola

2012-07-01

We previously described a method to identify the incidence of new-onset adult asthma (NOAA) in Alberta by industry and occupation, utilizing Workers' Compensation Board (WCB) and physician billing data. The aim of this study was to extend this method to data from British Columbia (BC) so as to compare the two provinces and to incorporate Bayesian methodology into estimates of risk. WCB claims for any reason 1995-2004 were linked to physician billing data. NOAA was defined as a billing for asthma (ICD-9 493) in the 12 months before a WCB claim without asthma in the previous 3 years. Incidence was calculated by occupation and industry. In a matched case-referent analysis, associations with exposures were examined using an asthma-specific job exposure matrix (JEM). Posterior distributions from the Alberta analysis and estimated misclassification parameters were used as priors in the Bayesian analysis of the BC data. Among 1 118 239 eligible WCB claims the incidence of NOAA was 1.4%. Sixteen occupations and 44 industries had a significantly increased risk; six industries had a decreased risk. The JEM identified wood dust [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.08-2.24] and animal antigens (OR 1.66, 95% CI 1.17-2.36) as related to an increased risk of NOAA. Exposure to isocyanates was associated with decreased risk (OR 0.57, 95% CI 0.39-0.85). Bayesian analyses taking account of exposure misclassification and informative priors resulted in posterior distributions of ORs with lower boundary of 95% credible intervals >1.00 for almost all exposures. The distribution of NOAA in BC appeared somewhat similar to that in Alberta, except for isocyanates. Bayesian analyses allowed incorporation of prior evidence into risk estimates, permitting reconsideration of the apparently protective effect of isocyanate exposure.

The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California

USGS Publications Warehouse

Richardson, L.A.; Champ, P.A.; Loomis, J.B.

2012-01-01

There is a growing concern that human health impacts from exposure to wildfire smoke are ignored in estimates of monetized damages from wildfires. Current research highlights the need for better data collection and analysis of these impacts. Using unique primary data, this paper quantifies the economic cost of health effects from the largest wildfire in Los Angeles County's modern history. A cost of illness estimate is $9.50 per exposed person per day. However, theory and empirical research consistently find that this measure largely underestimates the true economic cost of health effects from exposure to a pollutant in that it ignores the cost of defensive actions taken as well as disutility. For the first time, the defensive behavior method is applied to calculate the willingness to pay for a reduction in one wildfire smoke induced symptom day, which is estimated to be $84.42 per exposed person per day. ?? 2011.

Air pollution as a risk factor in health impact assessments of a travel mode shift towards cycling

PubMed Central

Raza, Wasif; Forsberg, Bertil; Johansson, Christer; Sommar, Johan Nilsson

2018-01-01

ABSTRACT Background: Promotion of active commuting provides substantial health and environmental benefits by influencing air pollution, physical activity, accidents, and noise. However, studies evaluating intervention and policies on a mode shift from motorized transport to cycling have estimated health impacts with varying validity and precision. Objective: To review and discuss the estimation of air pollution exposure and its impacts in health impact assessment studies of a shift in transport from cars to bicycles in order to guide future assessments. Methods: A systematic database search of PubMed was done primarily for articles published from January 2000 to May 2016 according to PRISMA guidelines. Results: We identified 18 studies of health impact assessment of change in transport mode. Most studies investigated future hypothetical scenarios of increased cycling. The impact on the general population was estimated using a comparative risk assessment approach in the majority of these studies, whereas some used previously published cost estimates. Air pollution exposure during cycling was estimated based on the ventilation rate, the pollutant concentration, and the trip duration. Most studies employed exposure-response functions from studies comparing background levels of fine particles between cities to estimate the health impacts of local traffic emissions. The effect of air pollution associated with increased cycling contributed small health benefits for the general population, and also only slightly increased risks associated with fine particle exposure among those who shifted to cycling. However, studies calculating health impacts based on exposure-response functions for ozone, black carbon or nitrogen oxides found larger effects attributed to changes in air pollution exposure. Conclusion: A large discrepancy between studies was observed due to different health impact assessment approaches, different assumptions for calculation of inhaled dose and different selection of dose-response functions. This kind of assessments would improve from more holistic approaches using more specific exposure-response functions. PMID:29400262

Development of a dosimeter for distributed body organs

NASA Technical Reports Server (NTRS)

Khandelwal, G. S.

1976-01-01

Calculational methods for estimation of dose from external proton exposure of aribtrary convex bodies is briefly reviewed and all of the necessary information for the estimation of dose in soft tissue is presented. Special emphasis is on retaining the effects of nuclear reaction especially in relation to the dose equivalent.

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.

Acute Gastroenteritis and Recreational Water: Highest Burden ...

EPA Pesticide Factsheets

OBJECT I VES : To provide summary estimates of gastroenteritis risks and illness burden associated with recreational water exposure and determine whether children have higher risks and burden.METHODS: We combined individual participant data from 13 prospective cohorts at marine and freshwater beaches throughout the United States (n = 84 411). We measured incident outcomes within 10 days of exposure: diarrhea, gastrointestinal illness, missed daily activity (work, school, vacation), and medical visits. We estimated the relationship between outcomes and 2 exposures: body immersion swimming and Enterococcus spp. fecal indicator bacteria levels in the water. We also estimated the population-attributable risk associated with these exposures.RESULTS: Water exposure accounted for 21% of diarrhea episodes and 9% of missed daily activities but was unassociated with gastroenteritis leading to medical consultation. Children aged 0 to 4 and 5 to 10 years had the most water exposure, exhibited stronger associations between levels of water quality and illness, and accounted for the largest attributable illness burden.CONCLUSIONS: The higher gastroenteritis risk and associated burden in young children presents important new information to inform future recreational water quality guidelines designed to protect public health. Meta-analysis of 13 beach sites and nearly 90,000 subjects found that swimming at the beach increased diarrhea incidence and individuals who swam in water

Cancer risk from incidental ingestion exposures to PAHs associated with coal-tar-sealed pavement

USGS Publications Warehouse

Williams, E. Spencer; Mahler, Barbara J.; Van Metre, Peter C.

2012-01-01

Recent (2009-10) studies documented significantly higher concentrations of polycyclic aromatic hydrocarbons (PAHs) in settled house dust in living spaces and soil adjacent to parking lots sealed with coal-tar-based products. To date, no studies have examined the potential human health effects of PAHs from these products in dust and soil. Here we present the results of an analysis of potential cancer risk associated with incidental ingestion exposures to PAHs in settings near coal-tar-sealed pavement. Exposures to benzo[a]pyrene equivalents were characterized across five scenarios. The central tendency estimate of excess cancer risk resulting from lifetime exposures to soil and dust from nondietary ingestion in these settings exceeded 1 × 10–4, as determined using deterministic and probabilistic methods. Soil was the primary driver of risk, but according to probabilistic calculations, reasonable maximum exposure to affected house dust in the first 6 years of life was sufficient to generate an estimated excess lifetime cancer risk of 6 × 10–5. Our results indicate that the presence of coal-tar-based pavement sealants is associated with significant increases in estimated excess lifetime cancer risk for nearby residents. Much of this calculated excess risk arises from exposures to PAHs in early childhood (i.e., 0–6 years of age).

Prospective Study of Particulate Air Pollution Exposures, Subclinical Atherosclerosis, and Clinical Cardiovascular Disease

PubMed Central

Kaufman, Joel D.; Adar, Sara D.; Allen, Ryan W.; Barr, R. Graham; Budoff, Matthew J.; Burke, Gregory L.; Casillas, Adrian M.; Cohen, Martin A.; Curl, Cynthia L.; Daviglus, Martha L.; Roux, Ana V. Diez; Jacobs, David R.; Kronmal, Richard A.; Larson, Timothy V.; Liu, Sally Lee-Jane; Lumley, Thomas; Navas-Acien, Ana; O'Leary, Daniel H.; Rotter, Jerome I.; Sampson, Paul D.; Sheppard, Lianne; Siscovick, David S.; Stein, James H.; Szpiro, Adam A.; Tracy, Russell P.

2012-01-01

The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) was initiated in 2004 to investigate the relation between individual-level estimates of long-term air pollution exposure and the progression of subclinical atherosclerosis and the incidence of cardiovascular disease (CVD). MESA Air builds on a multicenter, community-based US study of CVD, supplementing that study with additional participants, outcome measurements, and state-of-the-art air pollution exposure assessments of fine particulate matter, oxides of nitrogen, and black carbon. More than 7,000 participants aged 45–84 years are being followed for over 10 years for the identification and characterization of CVD events, including acute myocardial infarction and other coronary artery disease, stroke, peripheral artery disease, and congestive heart failure; cardiac procedures; and mortality. Subcohorts undergo baseline and follow-up measurements of coronary artery calcium using computed tomography and carotid artery intima-medial wall thickness using ultrasonography. This cohort provides vast exposure heterogeneity in ranges currently experienced and permitted in most developed nations, and the air monitoring and modeling methods employed will provide individual estimates of exposure that incorporate residence-specific infiltration characteristics and participant-specific time-activity patterns. The overarching study aim is to understand and reduce uncertainty in health effect estimation regarding long-term exposure to air pollution and CVD. PMID:23043127

Spatiotemporal Interpolation Methods for the Application of Estimating Population Exposure to Fine Particulate Matter in the Contiguous U.S. and a Real-Time Web Application.

PubMed

Li, Lixin; Zhou, Xiaolu; Kalo, Marc; Piltner, Reinhard

2016-07-25

Appropriate spatiotemporal interpolation is critical to the assessment of relationships between environmental exposures and health outcomes. A powerful assessment of human exposure to environmental agents would incorporate spatial and temporal dimensions simultaneously. This paper compares shape function (SF)-based and inverse distance weighting (IDW)-based spatiotemporal interpolation methods on a data set of PM2.5 data in the contiguous U.S. Particle pollution, also known as particulate matter (PM), is composed of microscopic solids or liquid droplets that are so small that they can get deep into the lungs and cause serious health problems. PM2.5 refers to particles with a mean aerodynamic diameter less than or equal to 2.5 micrometers. Based on the error statistics results of k-fold cross validation, the SF-based method performed better overall than the IDW-based method. The interpolation results generated by the SF-based method are combined with population data to estimate the population exposure to PM2.5 in the contiguous U.S. We investigated the seasonal variations, identified areas where annual and daily PM2.5 were above the standards, and calculated the population size in these areas. Finally, a web application is developed to interpolate and visualize in real time the spatiotemporal variation of ambient air pollution across the contiguous U.S. using air pollution data from the U.S. Environmental Protection Agency (EPA)'s AirNow program.

Spatiotemporal Interpolation Methods for the Application of Estimating Population Exposure to Fine Particulate Matter in the Contiguous U.S. and a Real-Time Web Application

PubMed Central

Li, Lixin; Zhou, Xiaolu; Kalo, Marc; Piltner, Reinhard

2016-01-01

Appropriate spatiotemporal interpolation is critical to the assessment of relationships between environmental exposures and health outcomes. A powerful assessment of human exposure to environmental agents would incorporate spatial and temporal dimensions simultaneously. This paper compares shape function (SF)-based and inverse distance weighting (IDW)-based spatiotemporal interpolation methods on a data set of PM2.5 data in the contiguous U.S. Particle pollution, also known as particulate matter (PM), is composed of microscopic solids or liquid droplets that are so small that they can get deep into the lungs and cause serious health problems. PM2.5 refers to particles with a mean aerodynamic diameter less than or equal to 2.5 micrometers. Based on the error statistics results of k-fold cross validation, the SF-based method performed better overall than the IDW-based method. The interpolation results generated by the SF-based method are combined with population data to estimate the population exposure to PM2.5 in the contiguous U.S. We investigated the seasonal variations, identified areas where annual and daily PM2.5 were above the standards, and calculated the population size in these areas. Finally, a web application is developed to interpolate and visualize in real time the spatiotemporal variation of ambient air pollution across the contiguous U.S. using air pollution data from the U.S. Environmental Protection Agency (EPA)’s AirNow program. PMID:27463722

A New Method for Partial Correction of Residual Confounding in Time-Series and Other Observational Studies.

PubMed

Flanders, W Dana; Strickland, Matthew J; Klein, Mitchel

2017-05-15

Methods exist to detect residual confounding in epidemiologic studies. One requires a negative control exposure with 2 key properties: 1) conditional independence of the negative control and the outcome (given modeled variables) absent confounding and other model misspecification, and 2) associations of the negative control with uncontrolled confounders and the outcome. We present a new method to partially correct for residual confounding: When confounding is present and our assumptions hold, we argue that estimators from models that include a negative control exposure with these 2 properties tend to be less biased than those from models without it. Using regression theory, we provide theoretical arguments that support our claims. In simulations, we empirically evaluated the approach using a time-series study of ozone effects on asthma emergency department visits. In simulations, effect estimators from models that included the negative control exposure (ozone concentrations 1 day after the emergency department visit) had slightly or modestly less residual confounding than those from models without it. Theory and simulations show that including the negative control can reduce residual confounding, if our assumptions hold. Our method differs from available methods because it uses a regression approach involving an exposure-based indicator rather than a negative control outcome to partially correct for confounding. © The Author 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.

A case-control study of airways obstruction among construction workers: Airways Obstruction Among Construction Workers

DOE PAGES

Dement, John; Welch, Laura; Ringen, Knut; ...

2015-06-29

Background: While smoking is the major cause of chronic obstructive pulmonary disease (COPD), occupational exposures to vapors, gases, dusts, and fumes (VGDF) increase COPD risk. This case-control study estimated the risk of COPD attributable to occupational exposures among construction workers. Methods: The study population included 834 cases and 1243 controls participating in a national medical screening program for older construction workers between 1997 and 2013. Qualitative exposure indices were developed based on lifetime work and exposure histories. Results: Approximately 18% (95%CI=2–24%) of COPD risk can be attributed to construction-related exposures, which are additive to the risk contributed by smoking. Amore » measure of all VGDF exposures combined was a strong predictor of COPD risk. Conclusions: Construction workers are at increased risk of COPD as a result of broad and complex effects of many exposures acting independently or interactively. Control methods should be implemented to prevent worker exposures, and smoking cessation should be promoted« less

A case-control study of airways obstruction among construction workers: Airways Obstruction Among Construction Workers

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

Dement, John; Welch, Laura; Ringen, Knut

Background: While smoking is the major cause of chronic obstructive pulmonary disease (COPD), occupational exposures to vapors, gases, dusts, and fumes (VGDF) increase COPD risk. This case-control study estimated the risk of COPD attributable to occupational exposures among construction workers. Methods: The study population included 834 cases and 1243 controls participating in a national medical screening program for older construction workers between 1997 and 2013. Qualitative exposure indices were developed based on lifetime work and exposure histories. Results: Approximately 18% (95%CI=2–24%) of COPD risk can be attributed to construction-related exposures, which are additive to the risk contributed by smoking. Amore » measure of all VGDF exposures combined was a strong predictor of COPD risk. Conclusions: Construction workers are at increased risk of COPD as a result of broad and complex effects of many exposures acting independently or interactively. Control methods should be implemented to prevent worker exposures, and smoking cessation should be promoted« less

Estimated radiation exposure of German commercial airline cabin crew in the years 1960-2003 modeled using dose registry data for 2004-2015.

PubMed

Wollschläger, Daniel; Hammer, Gaël Paul; Schafft, Thomas; Dreger, Steffen; Blettner, Maria; Zeeb, Hajo

2018-05-01

Exposure to ionizing radiation of cosmic origin is an occupational risk factor in commercial aircrew. In a historic cohort of 26,774 German aircrew, radiation exposure was previously estimated only for cockpit crew using a job-exposure matrix (JEM). Here, a new method for retrospectively estimating cabin crew dose is developed. The German Federal Radiation Registry (SSR) documents individual monthly effective doses for all aircrew. SSR-provided doses on 12,941 aircrew from 2004 to 2015 were used to model cabin crew dose as a function of age, sex, job category, solar activity, and male pilots' dose; the mean annual effective dose was 2.25 mSv (range 0.01-6.39 mSv). In addition to an inverse association with solar activity, exposure followed age- and sex-dependent patterns related to individual career development and life phases. JEM-derived annual cockpit crew doses agreed with SSR-provided doses for 2004 (correlation 0.90, 0.40 mSv root mean squared error), while the estimated average annual effective dose for cabin crew had a prediction error of 0.16 mSv, equaling 7.2% of average annual dose. Past average annual cabin crew dose can be modeled by exploiting systematic external influences as well as individual behavioral determinants of radiation exposure, thereby enabling future dose-response analyses of the full aircrew cohort including measurement error information.

Occupational Diesel Exposure, Duration of Employment, and Lung Cancer

PubMed Central

Picciotto, Sally; Costello, Sadie; Eisen, Ellen A.

2016-01-01

Background: If less healthy workers terminate employment earlier, thus accumulating less exposure, yet remain at greater risk of the health outcome, estimated health effects of cumulative exposure will be biased downward. If exposure also affects termination of employment, then the bias cannot be addressed using conventional methods. We examined these conditions as a prelude to a reanalysis of lung cancer mortality in the Diesel Exhaust in Miners Study. Methods: We applied an accelerated failure time model to assess the effect of exposures to respirable elemental carbon (a surrogate for diesel) on time to termination of employment among nonmetal miners who ever worked underground (n = 8,307). We then applied the parametric g-formula to assess how possible interventions setting respirable elemental carbon exposure limits would have changed lifetime risk of lung cancer, adjusting for time-varying employment status. Results: Median time to termination was 36% shorter (95% confidence interval = 33%, 39%), per interquartile range width increase in respirable elemental carbon exposure. Lung cancer risk decreased with more stringent interventions, with a risk ratio of 0.8 (95% confidence interval = 0.5, 1.1) comparing a limit of ≤25 µg/m3 respirable elemental carbon to no intervention. The fraction of cases attributable to diesel exposure was 27% in this population. Conclusions: The g-formula controlled for time-varying confounding by employment status, the signature of healthy worker survivor bias, which was also affected by diesel exposure. It also offers an alternative approach to risk assessment for estimating excess cumulative risk, and the impact of interventions based entirely on an observed population. PMID:26426944

A review of job-exposure matrix methodology for application to workers exposed to radiation from internally deposited plutonium or other radioactive materials.

PubMed

Liu, Hanhua; Wakeford, Richard; Riddell, Anthony; O'Hagan, Jacqueline; MacGregor, David; Agius, Raymond; Wilson, Christine; Peace, Mark; de Vocht, Frank

2016-03-01

Any potential health effects of radiation emitted from radionuclides deposited in the bodies of workers exposed to radioactive materials can be directly investigated through epidemiological studies. However, estimates of radionuclide exposure and consequent tissue-specific doses, particularly for early workers for whom monitoring was relatively crude but exposures tended to be highest, can be uncertain, limiting the accuracy of risk estimates. We review the use of job-exposure matrices (JEMs) in peer-reviewed epidemiological and exposure assessment studies of nuclear industry workers exposed to radioactive materials as a method for addressing gaps in exposure data, and discuss methodology and comparability between studies. We identified nine studies of nuclear worker cohorts in France, Russia, the USA and the UK that had incorporated JEMs in their exposure assessments. All these JEMs were study or cohort-specific, and although broadly comparable methodologies were used in their construction, this is insufficient to enable the transfer of any one JEM to another study. Moreover there was often inadequate detail on whether, or how, JEMs were validated. JEMs have become more detailed and more quantitative, and this trend may eventually enable better comparison across, and the pooling of, studies. We conclude that JEMs have been shown to be a valuable exposure assessment methodology for imputation of missing exposure data for nuclear worker cohorts with data not missing at random. The next step forward for direct comparison or pooled analysis of complete cohorts would be the use of transparent and transferable methods.

Burden of Disease from Toxic Waste Sites in India, Indonesia, and the Philippines in 2010

PubMed Central

Caravanos, Jack; Ericson, Bret; Sunga-Amparo, Jennifer; Susilorini, Budi; Sharma, Promila; Landrigan, Philip J.; Fuller, Richard

2013-01-01

Background: Prior calculations of the burden of disease from toxic exposures have not included estimates of the burden from toxic waste sites due to the absence of exposure data. Objective: We developed a disability-adjusted life year (DALY)-based estimate of the disease burden attributable to toxic waste sites. We focused on three low- and middle-income countries (LMICs): India, Indonesia, and the Philippines. Methods: Sites were identified through the Blacksmith Institute’s Toxic Sites Identification Program, a global effort to identify waste sites in LMICs. At least one of eight toxic chemicals was sampled in environmental media at each site, and the population at risk estimated. By combining estimates of disease incidence from these exposures with population data, we calculated the DALYs attributable to exposures at each site. Results: We estimated that in 2010, 8,629,750 persons were at risk of exposure to industrial pollutants at 373 toxic waste sites in the three countries, and that these exposures resulted in 828,722 DALYs, with a range of 814,934–1,557,121 DALYs, depending on the weighting factor used. This disease burden is comparable to estimated burdens for outdoor air pollution (1,448,612 DALYs) and malaria (725,000 DALYs) in these countries. Lead and hexavalent chromium collectively accounted for 99.2% of the total DALYs for the chemicals evaluated. Conclusions: Toxic waste sites are responsible for a significant burden of disease in LMICs. Although some factors, such as unidentified and unscreened sites, may cause our estimate to be an underestimate of the actual burden of disease, other factors, such as extrapolation of environmental sampling to the entire exposed population, may result in an overestimate of the burden of disease attributable to these sites. Toxic waste sites are a major, and heretofore underrecognized, global health problem. PMID:23649493

COLLECTING URINE SAMPLES FROM YOUNG CHILDREN FOR PESTICIDE STUDIES

EPA Science Inventory

To estimate pesticide exposure for young children wearing diapers, a method for collecting urine samples for analysis of pesticide metabolites is needed. To find a practical method, two possibilities were investigated: (1) analysis of expressed urine from cotton diaper inserts ...

Health Risk of Exposure to Atmospheric Pollutant Particles

EPA Science Inventory

In relation to multi-component mixture nature of atmospheric PM, this presentation will discuss methods for estimating the respiratory internal dose by experiment and mathematical modeling, limitations of each method and interpretations of the results in the context of health ris...

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

PubMed

Liu, Shelley H; Bobb, Jennifer F; Lee, Kyu Ha; Gennings, Chris; Claus Henn, Birgit; Bellinger, David; Austin, Christine; Schnaas, Lourdes; Tellez-Rojo, Martha M; Hu, Howard; Wright, Robert O; Arora, Manish; Coull, Brent A

2018-07-01

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

Estimating Water Supply Arsenic Levels in the New England Bladder Cancer Study

PubMed Central

Freeman, Laura E. Beane; Lubin, Jay H.; Airola, Matthew S.; Baris, Dalsu; Ayotte, Joseph D.; Taylor, Anne; Paulu, Chris; Karagas, Margaret R.; Colt, Joanne; Ward, Mary H.; Huang, An-Tsun; Bress, William; Cherala, Sai; Silverman, Debra T.; Cantor, Kenneth P.

2011-01-01

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (≥ 150 µg/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case–control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 µg/L; range, 0.1–11.5), statistical models of water utility measurement data (49%; median, 0.4 µg/L; range, 0.3–3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 µg/L; range, 0.6–22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods. PMID:21421449

Estimating water supply arsenic levels in the New England bladder cancer study

USGS Publications Warehouse

Nuckols, J.R.; Beane, Freeman L.E.; Lubin, J.H.; Airola, M.S.; Baris, D.; Ayotte, J.D.; Taylor, A.; Paulu, C.; Karagas, M.R.; Colt, J.; Ward, M.H.; Huang, A.-T.; Bress, W.; Cherala, S.; Silverman, D.T.; Cantor, K.P.

2011-01-01

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (??? 150 ??g/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case-control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 ??g/L; range, 0.1-11.5), statistical models of water utility measurement data (49%; median, 0.4 ??g/L; range, 0.3-3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 ??g/L; range, 0.6-22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods.

Residential Radon and Brain Tumour Incidence in a Danish Cohort

PubMed Central

Bräuner, Elvira V.; Andersen, Zorana J.; Andersen, Claus E.; Pedersen, Camilla; Gravesen, Peter; Ulbak, Kaare; Hertel, Ole; Loft, Steffen; Raaschou-Nielsen, Ole

2013-01-01

Background Increased brain tumour incidence over recent decades may reflect improved diagnostic methods and clinical practice, but remain unexplained. Although estimated doses are low a relationship between radon and brain tumours may exist. Objective To investigate the long-term effect of exposure to residential radon on the risk of primary brain tumour in a prospective Danish cohort. Methods During 1993–1997 we recruited 57,053 persons. We followed each cohort member for cancer occurrence from enrolment until 31 December 2009, identifying 121 primary brain tumour cases. We traced residential addresses from 1 January 1971 until 31 December 2009 and calculated radon concentrations at each address using information from central databases regarding geology and house construction. Cox proportional hazards models were used to estimate incidence rate-ratios (IRR) and 95% confidence intervals (CI) for the risk of primary brain tumours associated with residential radon exposure with adjustment for age, sex, occupation, fruit and vegetable consumption and traffic-related air pollution. Effect modification by air pollution was assessed. Results Median estimated radon was 40.5 Bq/m3. The adjusted IRR for primary brain tumour associated with each 100 Bq/m3 increment in average residential radon levels was 1.96 (95% CI: 1.07; 3.58) and this was exposure-dependently higher over the four radon exposure quartiles. This association was not modified by air pollution. Conclusions We found significant associations and exposure-response patterns between long-term residential radon exposure radon in a general population and risk of primary brain tumours, adding new knowledge to this field. This finding could be chance and needs to be challenged in future studies. PMID:24066143

Measuring Exposure to Protobacco Marketing and Media: A Field Study Using Ecological Momentary Assessment

PubMed Central

Scharf, Deborah M.; Setodji, Claude M.; Shadel, William G.

2012-01-01

Introduction: The aims of this study were to validate ecological momentary assessment (EMA) as a method for measuring exposure to tobacco-related marketing and media and to use this method to provide detailed descriptive data on college students’ exposure to protobacco marketing and media. Methods: College students (n = 134; ages 18–24 years) recorded their exposures to protobacco marketing and media on handheld devices for 21 consecutive days. Participants also recalled exposures to various types of protobacco marketing and media at the end of the study period. Results: Retrospectively recalled and EMA-based estimates of protobacco marketing exposure captured different information. The correlation between retrospectively recalled and EMA-logged exposures to tobacco marketing and media was moderate (r = .37, p < .001), and EMA-logged exposures were marginally associated with the intention to smoke at the end of the study, whereas retrospective recall of exposure was not. EMA data showed that college students were exposed to protobacco marketing through multiple channels in a relatively short period: Exposures (M = 8.24, SD = 7.85) occurred primarily in the afternoon (42%), on weekends (35%), and at point-of-purchase locations (68%) or in movies/TV (20%), and exposures to Marlboro, Newport, and Camel represented 56% of all exposures combined and 70% of branded exposures. Conclusions: Findings support the validity of EMA as a method for capturing detailed information about youth exposure to protobacco marketing and media that are not captured through other existing methods. Such data have the potential to highlight areas for policy change and prevention in order to reduce the impact of tobacco marketing on youth. PMID:22039076

Analysis of EPR and FISH studies of radiation doses in persons who lived in the upper reaches of the Techa River.

PubMed

Degteva, M O; Shagina, N B; Shishkina, E A; Vozilova, A V; Volchkova, A Y; Vorobiova, M I; Wieser, A; Fattibene, P; Della Monaca, S; Ainsbury, E; Moquet, J; Anspaugh, L R; Napier, B A

2015-11-01

Waterborne radioactive releases into the Techa River from the Mayak Production Association in Russia during 1949-1956 resulted in significant doses to about 30,000 persons who lived in downstream settlements. The residents were exposed to internal and external radiation. Two methods for reconstruction of the external dose are considered in this paper, electron paramagnetic resonance (EPR) measurements of teeth, and fluorescence in situ hybridization (FISH) measurements of chromosome translocations in circulating lymphocytes. The main issue in the application of the EPR and FISH methods for reconstruction of the external dose for the Techa Riverside residents was strontium radioisotopes incorporated in teeth and bones that act as a source of confounding local exposures. In order to estimate and subtract doses from incorporated (89,90)Sr, the EPR and FISH assays were supported by measurements of (90)Sr-body burdens and estimates of (90)Sr concentrations in dental tissues by the luminescence method. The resulting dose estimates derived from EPR to FISH measurements for residents of the upper Techa River were found to be consistent: The mean values vary from 510 to 550 mGy for the villages located close to the site of radioactive release to 130-160 mGy for the more distant villages. The upper bound of individual estimates for both methods is equal to 2.2-2.3 Gy. The EPR- and FISH-based dose estimates were compared with the doses calculated for the donors using the most recent Techa River Dosimetry System (TRDS). The TRDS external dose assessments are based on the data on contamination of the Techa River floodplain, simulation of air kerma above the contaminated soil, age-dependent lifestyles and individual residence histories. For correct comparison, TRDS-based doses were calculated from two sources: external exposure from the contaminated environment and internal exposure from (137)Cs incorporated in donors' soft tissues. It is shown here that the TRDS-based absorbed doses in tooth enamel and muscle are in agreement with EPR- and FISH-based estimates within uncertainty bounds. Basically, this agreement between the estimates has confirmed the validity of external doses calculated with the TRDS.

A BRIEF HISTORY OF THE DEVELOPMENT OF EXPOSURE ASSESSMENT METHODS AT US EPA/NERL USING ALVEOLAR BREATH AS THE BIOLOGICAL MEDIUM

EPA Science Inventory

Historically, ambient air (and perhaps water, soil, food, etc.) measurements were used to estimate the potential for human exposure to environmental pollutants based on various default assumptions. For instance, if a certain level of benzene was measured in the air, then a typ...

Use of (1-3)-β-D-glucan Concentrations in Dust as a Surrogate Method for Estimating Specific Mold Exposures

EPA Science Inventory

Indoor exposure to fungi has been associated with respiratory symptoms, often attributed to their major cell wall component, (1-3)-β-D-glucan (DG). This and the ease and low cost of performing DG analysis rather than cultivation or microscopic counting of mold spores, has prompte...

Community Health Risk Assessment of Primary Aluminum Smelter Emissions

PubMed Central

Larivière, Claude

2014-01-01

Objective: Primary aluminum production is an industrial process with high potential health risk for workers. We consider in this article how to assess community health risks associated with primary aluminum smelter emissions. Methods: We reviewed the literature on health effects, community exposure data, and dose–response relationships of the principal hazardous agents emitted. Results: On the basis of representative measured community exposure levels, we were able to make rough estimates on health risks associated with specific agents and categorize these as none, low, medium, or high. Conclusions: It is possible to undertake a rough-estimate community Health Risk Assessment for individual smelters on the basis of information available in the epidemiological literature and local community exposure data. PMID:24806724

Caries status in 16 year-olds with varying exposure to water fluoridation in Ireland.

PubMed

Mullen, J; McGaffin, J; Farvardin, N; Brightman, S; Haire, C; Freeman, R

2012-12-01

Most of the Republic of Ireland's public water supplies have been fluoridated since the mid-1960s while Northern Ireland has never been fluoridated, apart from some small short-lived schemes in east Ulster. This study examines dental caries status in 16 year-olds in a part of Ireland straddling fluoridated and non-fluoridated water supply areas and compares two methods of assessing the effectiveness of water fluoridation. The cross-sectional survey tested differences in caries status by two methods: 1, Estimated Fluoridation Status as used previously in national and regional studies in the Republic and in the All-Island study of 2002; 2, Percentage Lifetime Exposure, a modification of a system described by Slade in 1995 and used in Australian caries research. Adolescents were selected for the study by a two-part random sampling process. Firstly, schools were selected in each area by creating three tiers based on school size, and selecting schools randomly from each tier. Then random sampling of 16-year-olds from these schools, based on a pre-set sampling fraction for each tier of schools. With both systems of measurement, significantly lower caries levels were found in those children with the greatest exposure to fluoridated water when compared to those with the least exposure. The survey provides further evidence of the effectiveness in reducing dental caries experience up to 16 years of age. The extra intricacies involved in using the Percentage Lifetime Exposure method did not provide much more information when compared to the simpler Estimated Fluoridation Status method.

Dose estimation to eye lens of industrial gamma radiography workers using the Monte Carlo method.

PubMed

de Lima, Alexandre Roza; Hunt, John Graham; Da Silva, Francisco Cesar Augusto

2017-12-01

The ICRP Statement on Tissue Reactions (2011), based on epidemiological evidence, recommended a reduction for the eye lens equivalent dose limit from 150 to 20 mSv per year. This paper presents mainly the dose estimations received by industrial gamma radiography workers, during planned or accidental exposure to the eye lens, Hp(10) and effective dose. A Brazilian Visual Monte Carlo Dose Calculation program was used and two relevant scenarios were considered. For the planned exposure situation, twelve radiographic exposures per day for 250 days per year, which leads to a direct exposure of 10 h per year, were considered. The simulation was carried out using a 192 Ir source with 1.0 TBq of activity; a source/operator distance between 5 and 10 m and placed at heights of 0.02 m, 1 m and 2 m, and an exposure time of 12 s. Using a standard height of 1 m, the eye lens doses were estimated as being between 16.3 and 60.3 mGy per year. For the accidental exposure situation, the same radionuclide and activity were used, but in this case the doses were calculated with and without a collimator. The heights above ground considered were 1.0 m, 1.5 m and 2.0 m; the source/operator distance was 40 cm, and the exposure time 74 s. The eye lens doses at 1.5 m were 12.3 and 0.28 mGy without and with a collimator, respectively. The conclusions were that: (1) the estimated doses show that the 20 mSv annual limit for eye lens equivalent dose can directly impact industrial gamma radiography activities, mainly in industries with high number of radiographic exposures per year; (2) the risk of lens opacity has a low probability for a single accident, but depending on the number of accidental exposures and the dose levels found in planned exposures, the threshold dose can easily be exceeded during the professional career of an industrial radiography operator, and; (3) in a first approximation, Hp(10) can be used to estimate the equivalent dose to the eye lens.

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

An empirical model to estimate daily forest fire smoke exposure over a large geographic area using air quality, meteorological, and remote sensing data

PubMed Central

Yao, Jiayun; Henderson, Sarah B

2014-01-01

Exposure to forest fire smoke (FFS) is associated with a range of adverse health effects. The British Columbia Asthma Medication Surveillance (BCAMS) product was developed to detect potential impacts from FFS in British Columbia (BC), Canada. However, it has been a challenge to estimate FFS exposure with sufficient spatial coverage for the provincial population. We constructed an empirical model to estimate FFS-related fine particulate matter (PM2.5) for all populated areas of BC using data from the most extreme FFS days in 2003 through 2012. The input data included PM2.5 measurements on the previous day, remotely sensed aerosols, remotely sensed fires, hand-drawn tracings of smoke plumes from satellite images, fire danger ratings, and the atmospheric venting index. The final model explained 71% of the variance in PM2.5 observations. Model performance was tested in days with high, moderate, and low levels of FFS, resulting in correlations from 0.57 to 0.83. We also developed a method to assign the model estimates to geographical local health areas for use in BCAMS. The simplicity of the model allows easy application in time-constrained public health surveillance, and its sufficient spatial coverage suggests utility as an exposure assessment tool for epidemiologic studies on FFS exposure. PMID:24301352

Imputation method for lifetime exposure assessment in air pollution epidemiologic studies

PubMed Central

2013-01-01

Background Environmental epidemiology, when focused on the life course of exposure to a specific pollutant, requires historical exposure estimates that are difficult to obtain for the full time period due to gaps in the historical record, especially in earlier years. We show that these gaps can be filled by applying multiple imputation methods to a formal risk equation that incorporates lifetime exposure. We also address challenges that arise, including choice of imputation method, potential bias in regression coefficients, and uncertainty in age-at-exposure sensitivities. Methods During time periods when parameters needed in the risk equation are missing for an individual, the parameters are filled by an imputation model using group level information or interpolation. A random component is added to match the variance found in the estimates for study subjects not needing imputation. The process is repeated to obtain multiple data sets, whose regressions against health data can be combined statistically to develop confidence limits using Rubin’s rules to account for the uncertainty introduced by the imputations. To test for possible recall bias between cases and controls, which can occur when historical residence location is obtained by interview, and which can lead to misclassification of imputed exposure by disease status, we introduce an “incompleteness index,” equal to the percentage of dose imputed (PDI) for a subject. “Effective doses” can be computed using different functional dependencies of relative risk on age of exposure, allowing intercomparison of different risk models. To illustrate our approach, we quantify lifetime exposure (dose) from traffic air pollution in an established case–control study on Long Island, New York, where considerable in-migration occurred over a period of many decades. Results The major result is the described approach to imputation. The illustrative example revealed potential recall bias, suggesting that regressions against health data should be done as a function of PDI to check for consistency of results. The 1% of study subjects who lived for long durations near heavily trafficked intersections, had very high cumulative exposures. Thus, imputation methods must be designed to reproduce non-standard distributions. Conclusions Our approach meets a number of methodological challenges to extending historical exposure reconstruction over a lifetime and shows promise for environmental epidemiology. Application to assessment of breast cancer risks will be reported in a subsequent manuscript. PMID:23919666

The Economic Impact of Exposure to Secondhand Smoke in Minnesota

PubMed Central

Foldes, Steven S.; Alesci, Nina L.; Samet, Jonathan

2009-01-01

Objectives. Using the risk categories established by the 2006 US surgeon general's report, we estimated medical treatment costs related to exposure to secondhand tobacco smoke (SHS) in the state of Minnesota. Methods. We estimated the prevalence and costs of treated medical conditions related to SHS exposure in 2003 with data from Blue Cross and Blue Shield (Minnesota's largest insurer), the Current Population Survey, and population attributable risk estimates for these conditions reported in the scientific literature. We adjusted treatment costs to the state level by health insurance category by using the Medical Expenditure Panel Survey. Results. The total annual cost of treatment in Minnesota for conditions for which the 2006 surgeon general's report found sufficient evidence to conclude a causal link with exposure to SHS was $228.7 million in 2008 dollars—equivalent to $44.58 per Minnesota resident. Sensitivity analyses showed a range from $152.1 million to $330.0 million. Conclusions. The results present a strong rationale for regulating smoking in public places and were used to support the passage of Minnesota's Freedom to Breathe Act of 2007. PMID:19197082

Measuring exposure to protobacco marketing and media: a field study using ecological momentary assessment.

PubMed

Martino, Steven C; Scharf, Deborah M; Setodji, Claude M; Shadel, William G

2012-04-01

The aims of this study were to validate ecological momentary assessment (EMA) as a method for measuring exposure to tobacco-related marketing and media and to use this method to provide detailed descriptive data on college students' exposure to protobacco marketing and media. College students (n = 134; ages 18-24 years) recorded their exposures to protobacco marketing and media on handheld devices for 21 consecutive days. Participants also recalled exposures to various types of protobacco marketing and media at the end of the study period. Retrospectively recalled and EMA-based estimates of protobacco marketing exposure captured different information. The correlation between retrospectively recalled and EMA-logged exposures to tobacco marketing and media was moderate (r = .37, p < .001), and EMA-logged exposures were marginally associated with the intention to smoke at the end of the study, whereas retrospective recall of exposure was not. EMA data showed that college students were exposed to protobacco marketing through multiple channels in a relatively short period: Exposures (M = 8.24, SD = 7.85) occurred primarily in the afternoon (42%), on weekends (35%), and at point-of-purchase locations (68%) or in movies/TV (20%), and exposures to Marlboro, Newport, and Camel represented 56% of all exposures combined and 70% of branded exposures. Findings support the validity of EMA as a method for capturing detailed information about youth exposure to protobacco marketing and media that are not captured through other existing methods. Such data have the potential to highlight areas for policy change and prevention in order to reduce the impact of tobacco marketing on youth.

Multiple exposure photographic (MEP) technique: an objective assessment of sperm motility in infertility management.

PubMed

Adetoro, O O

1988-06-01

Multiple exposure photography (MEP), an objective technique, was used in determining the percentage of motile sperms in the semen samples from 41 males being investigated for infertility. This technique was compared with the conventional subjective ordinary microscopy method of spermatozoal motility assessment. A satisfactory correlation was observed in percentage sperm motility assessment using the two methods but the MEP estimation was more consistent and reliable. The value of this technique of sperm motility study in the developing world is discussed.

An estimate by two methods of thyroid absorbed doses due to BRAVO fallout in several Northern Marshall Islands.

PubMed

Musolino, S V; Greenhouse, N A; Hull, A P

1997-10-01

Estimates of the thyroid absorbed doses due to fallout originating from the 1 March 1954 BRAVO thermonuclear test on Bikini Atoll have been made for several inhabited locations in the Northern Marshall Islands. Rongelap, Utirik, Rongerik and Ailinginae Atolls were also inhabited on 1 March 1954, where retrospective thyroid absorbed doses have previously been reconstructed. The current estimates are based primarily on external exposure data, which were recorded shortly after each nuclear test in the Castle Series, and secondarily on soil concentrations of 137Cs in samples collected in 1978 and 1988, along with aerial monitoring done in 1978. The external exposures and 137Cs soil concentrations were representative of the atmospheric transport and deposition patterns of the entire Castle Series tests and show that the BRAVO test was the major contributor to fallout exposure during the Castle series and other test series which were carried out in the Marshall Islands. These data have been used as surrogates for fission product radioiodines and telluriums in order to estimate the range of thyroid absorbed doses that may have occurred throughout the Marshall Islands. Dosimetry based on these two sets of estimates agreed within a factor of 4 at the locations where BRAVO was the dominant contributor to the total exposure and deposition. Both methods indicate that thyroid absorbed doses in the range of 1 Gy (100 rad) may have been incurred in some of the northern locations, whereas the doses at southern locations did not significantly exceed levels comparable to those from worldwide fallout. The results of these estimates indicate that a systematic medical survey for thyroid disease should be conducted, and that a more definitive dose reconstruction should be made for all the populated atolls and islands in the Northern Marshall Islands beyond Rongelap, Utirik, Rongerik and Ailinginae, which were significantly contaminated by BRAVO fallout.

Bladder cancer incidence and exposure to polycyclic aromatic hydrocarbons among asphalt pavers

PubMed Central

Burstyn, Igor; Kromhout, Hans; Johansen, Christoffer; Langard, Sverre; Kauppinen, Timo; Shaham, Judith; Ferro, Gilles; Boffetta, Paolo

2007-01-01

Objectives To investigate the association between exposures to polycyclic aromatic hydrocarbons (PAH) that arises during asphalt paving, and risk of bladder cancer. Methods 7298 men included in the historical cohort were first employed between 1913 and 1999 in companies applying asphalt in Denmark, Norway, Finland and Israel. The minimal duration of employment for inclusion in the cohort was two seasons of work. Occupational histories were extracted from personnel files. A follow‐up for cancer incidence was conducted through national cancer registries. The authors estimated exposures to benzo(a)pyrene as a marker for 4–6 ring PAH. Exposures were reconstructed by using information about changes in asphalt paving technology in each company over time, the modelled relation between production characteristics and exposure levels, and job histories. Relative risks and associated 95% confidence intervals were estimated using Poisson regression. Results 48 bladder cancers among asphalt paving workers were detected; of these, 39 cases were exposed at least 15 years before the diagnosis. Cumulative exposure to PAH was not associated with the incidence of bladder cancer. The association with average exposure became stronger when 15‐year lag was considered, revealing a twofold increase in relative bladder cancer risk in the two higher exposure categories. There was an indication of exposure‐response association with lagged averaged exposure. Risk estimates were adjusted for age, country, duration of employment and calendar period, did not show heterogeneity among countries and did not materially change when re‐estimated after excluding non‐primary cancers from follow‐up. Previously conducted sensitivity analysis indicates that confounding by cigarette smoking is an unlikely explanation for the observed exposure‐response trends. Conclusions The authors were unable to control for all possible sources of confounding and bias. The results do not allow conclusion on the presence or absence of a causal link between exposures to PAH and risk of bladder cancer among asphalt workers. PMID:17332134

Estimation of the incubation period of influenza A (H1N1-2009) among imported cases: addressing censoring using outbreak data at the origin of importation.

PubMed

Nishiura, Hiroshi; Inaba, Hisashi

2011-03-07

Empirical estimates of the incubation period of influenza A (H1N1-2009) have been limited. We estimated the incubation period among confirmed imported cases who traveled to Japan from Hawaii during the early phase of the 2009 pandemic (n=72). We addressed censoring and employed an infection-age structured argument to explicitly model the daily frequency of illness onset after departure. We assumed uniform and exponential distributions for the frequency of exposure in Hawaii, and the hazard rate of infection for the latter assumption was retrieved, in Hawaii, from local outbreak data. The maximum likelihood estimates of the median incubation period range from 1.43 to 1.64 days according to different modeling assumptions, consistent with a published estimate based on a New York school outbreak. The likelihood values of the different modeling assumptions do not differ greatly from each other, although models with the exponential assumption yield slightly shorter incubation periods than those with the uniform exposure assumption. Differences between our proposed approach and a published method for doubly interval-censored analysis highlight the importance of accounting for the dependence of the frequency of exposure on the survival function of incubating individuals among imported cases. A truncation of the density function of the incubation period due to an absence of illness onset during the exposure period also needs to be considered. When the data generating process is similar to that among imported cases, and when the incubation period is close to or shorter than the length of exposure, accounting for these aspects is critical for long exposure times. Copyright © 2010 Elsevier Ltd. All rights reserved.

Elimination Rates of Dioxin Congeners in Former Chlorophenol Workers from Midland, Michigan

PubMed Central

Collins, James J.; Bodner, Kenneth M.; Wilken, Michael; Bodnar, Catherine M.

2012-01-01

Background: Exposure reconstructions and risk assessments for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other dioxins rely on estimates of elimination rates. Limited data are available on elimination rates for congeners other than TCDD. Objectives: We estimated apparent elimination rates using a simple first-order one-compartment model for selected dioxin congeners based on repeated blood sampling in a previously studied population. Methods: Blood samples collected from 56 former chlorophenol workers in 2004–2005 and again in 2010 were analyzed for dioxin congeners. We calculated the apparent elimination half-life in each individual for each dioxin congener and examined factors potentially influencing elimination rates and the impact of estimated ongoing background exposures on rate estimates. Results: Mean concentrations of all dioxin congeners in the sampled participants declined between sampling times. Median apparent half-lives of elimination based on changes in estimated mass in the body were generally consistent with previous estimates and ranged from 6.8 years (1,2,3,7,8,9-hexachlorodibenzo-p-dioxin) to 11.6 years (pentachlorodibenzo-p-dioxin), with a composite half-life of 9.3 years for TCDD toxic equivalents. None of the factors examined, including age, smoking status, body mass index or change in body mass index, initial measured concentration, or chloracne diagnosis, was consistently associated with the estimated elimination rates in this population. Inclusion of plausible estimates of ongoing background exposures decreased apparent half-lives by approximately 10%. Available concentration-dependent toxicokinetic models for TCDD underpredicted observed elimination rates for concentrations < 100 ppt. Conclusions: The estimated elimination rates from this relatively large serial sampling study can inform occupational and environmental exposure and serum evaluations for dioxin compounds. PMID:23063871

AC field exposure study: human exposure to 60-Hz electric fields

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

Silva, J.M.

1985-04-01

The objective of this study was to develop a method of estimating human exposure to the 60 Hz electric fields created by transmission lines. The Activity Systems Model simulates human activities in a variety of situations where exposure to electric fields is possible. The model combines maps of electric fields, activity maps, and experimentally determined activity factors to provide histograms of time spent in electric fields of various strengths in the course of agricultural, recreational, and domestic activities. For corroboration, the study team measured actual human exposure at locations across the United States near transmission lines ranging in voltage frommore » 115 to 1200 kV. The data were collected with a specially designed vest that measures exposure. These data demonstrate the accuracy of the exposure model presented in this report and revealed that most exposure time is spent in fields of magnitudes similar to many household situations. The report provides annual exposure estimates for human activities near transmission lines and in the home and compares them with exposure data from typical laboratory animal experiments. For one exposure index, the cumulative product of time and electric field, exposure during some of the laboratory animal experiments is two to four orders of magnitude greater than cumulative exposure for a human during one year of outdoor work on a farm crossed by a transmission line.« less

Estimated Exposure to Arsenic in Breastfed and Formula-Fed Infants in a United States Cohort

PubMed Central

Carignan, Courtney C.; Jackson, Brian P.; Farzan, Shohreh F.; Gandolfi, A. Jay; Punshon, Tracy; Folt, Carol L.; Karagas, Margaret R.

2015-01-01

Background: Previous studies indicate that concentrations of arsenic in breast milk are relatively low even in areas with high drinking-water arsenic. However, it is uncertain whether breastfeeding leads to reduced infant exposure to arsenic in regions with lower arsenic concentrations. Objective: We estimated the relative contributions of breast milk and formula to arsenic exposure during early infancy in a U.S. population. Methods: We measured arsenic in home tap water (n = 874), urine from 6-week-old infants (n = 72), and breast milk from mothers (n = 9) enrolled in the New Hampshire Birth Cohort Study (NHBCS) using inductively coupled plasma mass spectrometry. Using data from a 3-day food diary, we compared urinary arsenic across infant feeding types and developed predictive exposure models to estimate daily arsenic intake from breast milk and formula. Results: Urinary arsenic concentrations were generally low (median, 0.17 μg/L; maximum, 2.9 μg/L) but 7.5 times higher for infants fed exclusively with formula than for infants fed exclusively with breast milk (β = 2.02; 95% CI: 1.21, 2.83; p < 0.0001, adjusted for specific gravity). Similarly, the median estimated daily arsenic intake by NHBCS infants was 5.5 times higher for formula-fed infants (0.22 μg/kg/day) than for breastfed infants (0.04 μg/kg/day). Given median arsenic concentrations measured in NHBCS tap water and previously published for formula powder, formula powder was estimated to account for ~ 70% of median exposure among formula-fed NHBCS infants. Conclusions: Our findings suggest that breastfed infants have lower arsenic exposure than formula-fed infants, and that both formula powder and drinking water can be sources of exposure for U.S. infants. Citation: Carignan CC, Cottingham KL, Jackson BP, Farzan SF, Gandolfi AJ, Punshon T, Folt CL, Karagas MR. 2015. Estimated exposure to arsenic in breastfed and formula-fed infants in a United States cohort. Environ Health Perspect 123:500–506; http://dx.doi.org/10.1289/ehp.1408789 PMID:25707031

Comparison of modeled estimates of inhalation exposure to aerosols during use of consumer spray products.

PubMed

Park, Jihoon; Yoon, Chungsik; Lee, Kiyoung

2018-05-30

In the field of exposure science, various exposure assessment models have been developed to complement experimental measurements; however, few studies have been published on their validity. This study compares the estimated inhaled aerosol doses of several inhalation exposure models to experimental measurements of aerosols released from consumer spray products, and then compares deposited doses within different parts of the human respiratory tract according to deposition models. Exposure models, including the European Center for Ecotoxicology of Chemicals Targeted Risk Assessment (ECETOC TRA), the Consumer Exposure Model (CEM), SprayExpo, ConsExpo Web and ConsExpo Nano, were used to estimate the inhaled dose under various exposure scenarios, and modeled and experimental estimates were compared. The deposited dose in different respiratory regions was estimated using the International Commission on Radiological Protection model and multiple-path particle dosimetry models under the assumption of polydispersed particles. The modeled estimates of the inhaled doses were accurate in the short term, i.e., within 10 min of the initial spraying, with a differences from experimental estimates ranging from 0 to 73% among the models. However, the estimates for long-term exposure, i.e., exposure times of several hours, deviated significantly from the experimental estimates in the absence of ventilation. The differences between the experimental and modeled estimates of particle number and surface area were constant over time under ventilated conditions. ConsExpo Nano, as a nano-scale model, showed stable estimates of short-term exposure, with a difference from the experimental estimates of less than 60% for all metrics. The deposited particle estimates were similar among the deposition models, particularly in the nanoparticle range for the head airway and alveolar regions. In conclusion, the results showed that the inhalation exposure models tested in this study are suitable for estimating short-term aerosol exposure (within half an hour), but not for estimating long-term exposure. Copyright © 2018 Elsevier GmbH. All rights reserved.

Model framework for integrating multiple exposure pathways to chemicals in household cleaning products.

PubMed

Shin, H-M; McKone, T E; Bennett, D H

2017-07-01

We present a screening-level exposure-assessment method which integrates exposure from all plausible exposure pathways as a result of indoor residential use of cleaning products. The exposure pathways we considered are (i) exposure to a user during product use via inhalation and dermal, (ii) exposure to chemical residues left on clothing, (iii) exposure to all occupants from the portion released indoors during use via inhalation and dermal, and (iv) exposure to the general population due to down-the-drain disposal via inhalation and ingestion. We use consumer product volatilization models to account for the chemical fractions volatilized to air (f volatilized ) and disposed down the drain (f down-the-drain ) during product use. For each exposure pathway, we use a fate and exposure model to estimate intake rates (iR) in mg/kg/d. Overall, the contribution of the four exposure pathways to the total exposure varies by the type of cleaning activities and with chemical properties. By providing a more comprehensive exposure model and by capturing additional exposures from often-overlooked exposure pathways, our method allows us to compare the relative contribution of various exposure routes and could improve high-throughput exposure assessment for chemicals in cleaning products. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Performance and Storage Integrity of Dried Blood Spots for PCB, BFR and Pesticide Measurements

PubMed Central

Batterman, Stuart; Chernyak, Sergei

2014-01-01

Dried blood spots (DBS) can provide accurate and valuable estimates of exposure to environmental toxicants, and the use of information derived from archived newborn DBS information has enormous potential to open up new research on the impacts of early chemical exposure on disease. Broad application of DBS for the purpose of quantitative exposure estimation requires robust and validated methods. This study investigates the suitability of DBS analyses for population studies of exposure to three chemical groups: polychlorinated biphenyls (PCBs), brominated flame retardants (BFRs), and chlorinated pesticides. It examines background (matrix) contamination, recovery and extraction variability, sensitivity, and storage stability. DBS samples prepared using 50 μL of adult blood were analyzed by GC/MS, and method performance was confirmed by using certified materials and paired DBS-blood samples from six volunteers. Several of the target compounds and their degradation products have not been previously measured in DBS. All target compounds were detected in DBS samples collected from the volunteers. Sample DBS cards showed background contamination of several compounds. When stored at room temperature, target compounds, excluding PBDEs, were stable for up to one month. When refrigerated or frozen, stability was acceptable for all compounds up to one year, and multiyear storage appears acceptable at colder (e.g., −80 °C) temperatures. Multicompartment models may be used to estimate or correct for storage losses. Considering concentrations of contaminants for adults and children reported in the literature, and experimental values of detection limits and background contamination, DBS samples are suitable for quantifying exposures to many PCBs, BFRs and persistent pesticides. PMID:25058892

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.

Time-dependent effect of intensity of smoking and of occupational exposure to asbestos on the risk of lung cancer: results from the ICARE case-control study.

PubMed

Lévêque, Emilie; Lacourt, Aude; Luce, Danièle; Sylvestre, Marie-Pierre; Guénel, Pascal; Stücker, Isabelle; Leffondré, Karen

2018-05-18

To estimate the impact of intensity of both smoking and occupational exposure to asbestos on the risk of lung cancer throughout the whole exposure history. Data on 2026 male cases and 2610 male controls came from the French ICARE (Investigation of occupational and environmental causes of respiratory cancers) population-based, case-control study. Lifetime smoking history and occupational history were collected from standardised questionnaires and face-to-face interviews. Occupational exposure to asbestos was assessed using a job exposure matrix. The effects of annual average daily intensity of smoking (reported average number of cigarettes smoked per day) and asbestos exposure (estimated average daily air concentration of asbestos fibres at work) were estimated using a flexible weighted cumulative index of exposure in logistic regression models. Intensity of smoking in the 10 years preceding diagnosis had a much stronger association with the risk of lung cancer than more distant intensity. By contrast, intensity of asbestos exposure that occurred more than 40 years before diagnosis had a stronger association with the risk of lung cancer than more recent intensity, even if intensity in the 10 years preceding diagnosis also had a significant effect. Our results illustrate the dynamic of the effect of intensity of both smoking and occupational exposure to asbestos on the risk of lung cancer. They confirm that the timing of exposure plays an important role, and suggest that standard analytical methods assuming equal weights of intensity over the whole exposure history may be questionable. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Using new satellite based exposure methods to study the association between pregnancy pm2.5 exposure, premature birth and birth weight in Massachusetts

PubMed Central

2012-01-01

Background Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. Methods We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5) levels during pregnancy in Massachusetts for a 9-year period (2000–2008). Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births) and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. Results Birth weight was negatively associated with PM2.5 across all tested periods. For example, a 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI) = −21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI) = 1.01–1.13) for each 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy period. Conclusions The presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants. PMID:22709681

Comparison of temporal realistic telecommunication base station exposure with worst-case estimation in two countries.

PubMed

Mahfouz, Zaher; Verloock, Leen; Joseph, Wout; Tanghe, Emmeric; Gati, Azeddine; Wiart, Joe; Lautru, David; Hanna, Victor Fouad; Martens, Luc

2013-12-01

The influence of temporal daily exposure to global system for mobile communications (GSM) and universal mobile telecommunications systems and high speed downlink packet access (UMTS-HSDPA) is investigated using spectrum analyser measurements in two countries, France and Belgium. Temporal variations and traffic distributions are investigated. Three different methods to estimate maximal electric-field exposure are compared. The maximal realistic (99 %) and the maximal theoretical extrapolation factor used to extrapolate the measured broadcast control channel (BCCH) for GSM and the common pilot channel (CPICH) for UMTS are presented and compared for the first time in the two countries. Similar conclusions are found in the two countries for both urban and rural areas: worst-case exposure assessment overestimates realistic maximal exposure up to 5.7 dB for the considered example. In France, the values are the highest, because of the higher population density. The results for the maximal realistic extrapolation factor at the weekdays are similar to those from weekend days.

Improving estimates of air pollution exposure through ubiquitous sensing technologies

PubMed Central

de Nazelle, Audrey; Seto, Edmund; Donaire-Gonzalez, David; Mendez, Michelle; Matamala, Jaume; Nieuwenhuijsen, Mark J; Jerrett, Michael

2013-01-01

Traditional methods of exposure assessment in epidemiological studies often fail to integrate important information on activity patterns, which may lead to bias, loss of statistical power or both in health effects estimates. Novel sensing technologies integrated with mobile phones offer potential to reduce exposure measurement error. We sought to demonstrate the usability and relevance of the CalFit smartphone technology to track person-level time, geographic location, and physical activity patterns for improved air pollution exposure assessment. We deployed CalFit-equipped smartphones in a free living-population of 36 subjects in Barcelona, Spain. Information obtained on physical activity and geographic location was linked to space-time air pollution mapping. For instance, we found on average travel activities accounted for 6% of people’s time and 24% of their daily inhaled NO2. Due to the large number of mobile phone users, this technology potentially provides an unobtrusive means of collecting epidemiologic exposure data at low cost. PMID:23416743

Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case-control study

PubMed Central

2012-01-01

Background Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments. Methods National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions. Results Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 μg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls. Conclusions We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health PMID:22475580

Integrative assessment of multiple pesticides as risk factors for non-Hodgkin's lymphoma among men

PubMed Central

De Roos, A J; Zahm, S; Cantor, K; Weisenburger, D; Holmes, F; Burmeister, L; Blair, A

2003-01-01

Methods: During the 1980s, the National Cancer Institute conducted three case-control studies of NHL in the midwestern United States. These pooled data were used to examine pesticide exposures in farming as risk factors for NHL in men. The large sample size (n = 3417) allowed analysis of 47 pesticides simultaneously, controlling for potential confounding by other pesticides in the model, and adjusting the estimates based on a prespecified variance to make them more stable. Results: Reported use of several individual pesticides was associated with increased NHL incidence, including organophosphate insecticides coumaphos, diazinon, and fonofos, insecticides chlordane, dieldrin, and copper acetoarsenite, and herbicides atrazine, glyphosate, and sodium chlorate. A subanalysis of these "potentially carcinogenic" pesticides suggested a positive trend of risk with exposure to increasing numbers. Conclusion: Consideration of multiple exposures is important in accurately estimating specific effects and in evaluating realistic exposure scenarios. PMID:12937207

A Monte Carlo program to calculate the exposure rate from airborne radioactive gases inside a nuclear reactor containment building.

PubMed

Sherbini, S; Tamasanis, D; Sykes, J; Porter, S W

1986-12-01

A program was developed to calculate the exposure rate resulting from airborne gases inside a reactor containment building. The calculations were performed at the location of a wall-mounted area radiation monitor. The program uses Monte Carlo techniques and accounts for both the direct and scattered components of the radiation field at the detector. The scattered component was found to contribute about 30% of the total exposure rate at 50 keV and dropped to about 7% at 2000 keV. The results of the calculations were normalized to unit activity per unit volume of air in the containment. This allows the exposure rate readings of the area monitor to be used to estimate the airborne activity in containment in the early phases of an accident. Such estimates, coupled with containment leak rates, provide a method to obtain a release rate for use in offsite dose projection calculations.

Assessment of dermal exposure of greenhouse workers to the pesticide bupirimate.

PubMed

Jongen, M J; Engel, R; Leenheers, L H

1992-01-01

An HPLC method was developed for estimation of dermal exposure of greenhouse workers to the pesticide bupirimate. Chromatography was performed on a cyano-modified silica column with methanol-water (6:4 by volume) containing 5 g/L ammonium sulfate as eluent. UV detection at 310 nm was used for quantitation. Dermal exposure was assessed by letting the workers wear cotton gloves and by measuring foliar dislodgable residues in the greenhouses as potential exposure. The analytical procedure was validated for measurement of bupirimate on cotton gloves and in solutions used for the estimation of foliar dislodgable residues. Gloves were extracted with methanol. Recovery of bupirimate from fortified gloves was complete. Methanol extracts with one volume of water added and solutions containing dislodgable residues were injected directly onto the HPLC system. The limit of detection was 30 micrograms/L. Between-day coefficients of variation were 7 and 4% at concentrations of 0.6 and 28 mg/L, respectively.

Spatial Resolution Requirements for Traffic-Related Air Pollutant Exposure Evaluations

PubMed Central

Batterman, Stuart; Chambliss, Sarah; Isakov, Vlad

2014-01-01

Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9,700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 hr, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification. PMID:25132794

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.

THE UNIQUE VALUE OF BREATH BIOMARKERS FOR ESTIMATING PHAMACOKINETIC RATE CONSTANTS AND BODY BURDEN FROM RANDOM/INTERMITTENT DOSE

EPA Science Inventory

Biomarker measurements are used in three ways: 1) evaluating the time course and distribution of a chemical in the body, 2) estimating previous exposure or dose, and 3) assessing disease state. Blood and urine measurements are the primary methods employed. Of late, it has been ...

A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

PubMed

Houseman, E Andres; Virji, M Abbas

2017-08-01

Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models, except for the auto-regressive moving average model. Plots of means from the Bayesian model showed good fit to the observed data. The proposed Bayesian model provides an approach for modeling non-stationary autocorrelation in a hierarchical modeling framework to estimate task means, standard deviations, quantiles, and parameter estimates for covariates that are less biased and have better performance characteristics than some of the contemporary methods. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

Lung Cancer and Elemental Carbon Exposure in Trucking Industry Workers

PubMed Central

Laden, Francine; Hart, Jaime E.; Davis, Mary E.; Eisen, Ellen A.; Smith, Thomas J.

2012-01-01

Background: Diesel exhaust has been considered to be a probable lung carcinogen based on studies of occupationally exposed workers. Efforts to define lung cancer risk in these studies have been limited in part by lack of quantitative exposure estimates. Objective: We conducted a retrospective cohort study to assess lung cancer mortality risk among U.S. trucking industry workers. Elemental carbon (EC) was used as a surrogate of exposure to engine exhaust from diesel vehicles, traffic, and loading dock operations. Methods: Work records were available for 31,135 male workers employed in the unionized U.S. trucking industry in 1985. A statistical model based on a national exposure assessment was used to estimate historical work-related exposures to EC. Lung cancer mortality was ascertained through the year 2000, and associations with cumulative and average EC were estimated using proportional hazards models. Results: Duration of employment was inversely associated with lung cancer risk consistent with a healthy worker survivor effect and a cohort composed of prevalent hires. After adjusting for employment duration, we noted a suggestion of a linear exposure–response relationship. For each 1,000-µg/m3 months of cumulative EC, based on a 5-year exposure lag, the hazard ratio (HR) was 1.07 [95% confidence interval (CI): 0.99, 1.15] with a similar association for a 10-year exposure lag [HR = 1.09 (95% CI: 0.99, 1.20)]. Average exposure was not associated with relative risk. Conclusions: Lung cancer mortality in trucking industry workers increased in association with cumulative exposure to EC after adjusting for negative confounding by employment duration. PMID:22739103

The risk of coronary artery disease estimated non-invasively in patients with essential hypertension environmentally exposed to cigarette smoke.

PubMed

Gać, Paweł; Jaźwiec, Przemysław; Poręba, Małgorzata; Mazur, Grzegorz; Pawlas, Krystyna; Sobieszczańska, Małgorzata; Poręba, Rafał

2017-12-01

The relationship between environmental exposure of non-smokers to cigarette smoke and the coronary artery calcium scores has not been sufficiently documented. The aim of the study was to identify the relationship between environmental exposure to cigarette smoke and the risk of coronary artery disease (CAD) estimated non-invasively through measurement of coronary artery calcium score by computed tomography in patients with essential hypertension. The study was conducted on 67 patients with essential hypertension, non-smokers environmentally exposed to cigarette smoke (group A) and on 67 patients with essential hypertension, non-smokers not exposed to cigarette smoke (group B), selected using the case to case. Environmental exposure to cigarette smoke was evaluated using a questionnaire. The risk of development of coronary artery disease was estimated non-invasively through measurement of coronary artery calcium score (CA CS ) by computed tomography. Group A was characterised by significantly higher CA CS and left anterior descending (LAD CS ) calcium scores than group B. Compared to group B, group A had significantly higher percentage of patients with significant risk of CAD estimated on the basis of CA CS values, and significantly lower percentage of patients with practically no risk of CAD estimated with the same method. Advanced age, peripheral artery diseases and environmental exposure to cigarette smoke are independent risk factors associated with increased CA CS and LAD CS values. In addition, higher BMI and hypercholesterolemia are independent risk factors for increased values of LAD CS . In patients with essential hypertension environmental exposure to cigarette smoke may result in elevated risk of coronary artery disease estimated non-invasively through measurement of coronary artery calcium score by computed tomography. Copyright © 2017 Elsevier B.V. All rights reserved.

Multimedia models of human exposure to industrial emissions through food products: Identifying the critical pathways

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

McKone, T.E.; Maddalena, R.L.; Dowdy, D.L.

1995-12-31

The magnitude of potential human exposure through foods can be and has been assessed through food-product samples. Reducing these exposures requires that measuring not only the exposure media (food) concentrations but also defining the processes that link various contaminant sources to food. The authors present here a general approach for quantifying human exposure to contaminants in home-grown foods using four factors-ambient environmental concentrations in air and soil; bioconcentration factors between air, soil, leaves, and roots; translocations from leaves and roots to edible-plant parts; and human activity patterns associated with consumption of home-grown food products. The authors combined these factors inmore » a general model and used sensitivity analyses to assess the important contributions to the imprecision of exposure estimates. Despite large uncertainties about human activities, they found the major source of uncertainty (variance) in exposure estimates is attributable to imprecision in quantifying bioconcentration. This is especially evident for persistent and fat-soluble compounds--such as PCBs, PAHs, dioxins, and furans. The evaluation of analytical and theoretical methods used to characterize bioconcentration factors reveals that molecular connectivity indices (MCIs) based on molecular structure are better predictors of bioconcentration in plants than are the solubility factors currently in use. The authors describe ongoing laboratory experiments in exposure chambers with garden foods such as leafy vegetables and root crops. They then assess the ability of these methods to better define chemical mass transfers among the components of the home-garden system-air, soil-organic phases, soil solution, plant roots, and plant leaves.« less

43 CFR Appendix I to Part 11 - Methods for Estimating the Areas of Ground Water and Surface Water Exposure During the...

Code of Federal Regulations, 2010 CFR

2010-10-01

... the initial mixing distance, is estimated by: Cp=25(Wi)/(T0.7 Q) where Cp is the peak concentration... equation: Tp=9.25×106 Wi/(QCp) where Tp is the time estimate, in hours, and Wi, Cp, and Q are defined above... downstream location, past the initial mixing distance, is estimated by: Cp=C(q)/(Q+ where Cp and Q are...

43 CFR Appendix I to Part 11 - Methods for Estimating the Areas of Ground Water and Surface Water Exposure During the...

Code of Federal Regulations, 2012 CFR

2012-10-01

... the initial mixing distance, is estimated by: Cp=25(Wi)/(T0.7 Q) where Cp is the peak concentration... equation: Tp=9.25×106 Wi/(QCp) where Tp is the time estimate, in hours, and Wi, Cp, and Q are defined above... downstream location, past the initial mixing distance, is estimated by: Cp=C(q)/(Q+ where Cp and Q are...

43 CFR Appendix I to Part 11 - Methods for Estimating the Areas of Ground Water and Surface Water Exposure During the...

Code of Federal Regulations, 2013 CFR

2013-10-01

... the initial mixing distance, is estimated by: Cp=25(Wi)/(T0.7 Q) where Cp is the peak concentration... equation: Tp=9.25×106 Wi/(QCp) where Tp is the time estimate, in hours, and Wi, Cp, and Q are defined above... downstream location, past the initial mixing distance, is estimated by: Cp=C(q)/(Q+ where Cp and Q are...

43 CFR Appendix I to Part 11 - Methods for Estimating the Areas of Ground Water and Surface Water Exposure During the...

Code of Federal Regulations, 2011 CFR

2011-10-01

... the initial mixing distance, is estimated by: Cp=25(Wi)/(T0.7 Q) where Cp is the peak concentration... equation: Tp=9.25×106 Wi/(QCp) where Tp is the time estimate, in hours, and Wi, Cp, and Q are defined above... downstream location, past the initial mixing distance, is estimated by: Cp=C(q)/(Q+ where Cp and Q are...

43 CFR Appendix I to Part 11 - Methods for Estimating the Areas of Ground Water and Surface Water Exposure During the...

Code of Federal Regulations, 2014 CFR

2014-10-01

... the initial mixing distance, is estimated by: Cp=25(Wi)/(T0.7 Q) where Cp is the peak concentration... equation: Tp=9.25×106 Wi/(QCp) where Tp is the time estimate, in hours, and Wi, Cp, and Q are defined above... downstream location, past the initial mixing distance, is estimated by: Cp=C(q)/(Q+ where Cp and Q are...

Technical Note: Comparison of accelerated methods for evaluating leaching from preservative-treated wood

Treesearch

Stan T. Lebow; Patricia K. Lebow; Kolby C. Hirth

2017-01-01

Current standardized methods are not well-suited for estimating in-service preservative leaching from treated wood products. This study compared several alternative leaching methods to a commonly used standard method, and to leaching under natural exposure conditions. Small blocks or lumber specimens were pressure treated with a wood preservative containing borax and...

Using PM2.5 concentrations to estimate the health burden from solid fuel combustion, with application to Irish and Scottish homes

PubMed Central

2013-01-01

Background This study estimates the potential population health burden from exposure to combustion-derived particulate air pollution in domestic settings in Ireland and Scotland. Methods The study focused on solid fuel combustion used for heating and the use of gas for cooking. PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) was used as the pollutant mixture indicator. Measured PM2.5 concentrations in homes using solid fuels were adjusted for other sources of PM2.5 by subtracting PM2.5 concentrations in homes using gas for cooking but not solid fuel heating. Health burden was estimated for exposure indoors 6 pm - midnight, or all day (24-hour), by combining estimated attributable annual PM2.5 exposures with (i) selected epidemiological functions linking PM2.5 with mortality and morbidity (involving some re-scaling from PM10 to PM2.5, and adjustments ‘translating’ from concentrations to exposures) and (ii) on the current population exposed and background rates of morbidity and mortality. Results PM2.5 concentrations in coal and wood burning homes were similar to homes using gas for cooking, used here as a baseline (mean 24-hr PM2.5 concentrations 8.6 μg/m3) and so health impacts were not calculated. Concentrations of PM2.5 in homes using peat were higher (24-hr mean 15.6 μg/m3); however, health impacts were calculated for the exposed population in Ireland only; the proportion exposed in Scotland was very small. The assessment for winter evening exposure (estimated annual average increase of 2.11 μg/m3 over baseline) estimated 21 additional annual cases of all-cause mortality, 55 of chronic bronchitis, and 30,100 and 38,000 annual lower respiratory symptom days (including cough) and restricted activity days respectively. Conclusion New methods for estimating the potential health burden of combustion-generated pollution from solid fuels in Irish and Scottish homes are provided. The methodology involves several approximations and uncertainties but is consistent with a wider movement towards quantifying risks in PM2.5 irrespective of source. Results show an effect of indoor smoke from using peat (but not wood or coal) for heating and cooking; but they do not suggest that this is a major public health issue. PMID:23782423

A GIS-based method for household recruitment in a prospective pesticide exposure study.

PubMed

Allpress, Justine L E; Curry, Ross J; Hanchette, Carol L; Phillips, Michael J; Wilcosky, Timothy C

2008-04-30

Recent advances in GIS technology and remote sensing have provided new opportunities to collect ecologic data on agricultural pesticide exposure. Many pesticide studies have used historical or records-based data on crops and their associated pesticide applications to estimate exposure by measuring residential proximity to agricultural fields. Very few of these studies collected environmental and biological samples from study participants. One of the reasons for this is the cost of identifying participants who reside near study fields and analyzing samples obtained from them. In this paper, we present a cost-effective, GIS-based method for crop field selection and household recruitment in a prospective pesticide exposure study in a remote location. For the most part, our multi-phased approach was carried out in a research facility, but involved two brief episodes of fieldwork for ground truthing purposes. This method was developed for a larger study designed to examine the validity of indirect pesticide exposure estimates by comparing measured exposures in household dust, water and urine with records-based estimates that use crop location, residential proximity and pesticide application data. The study focused on the pesticide atrazine, a broadleaf herbicide used in corn production and one of the most widely-used pesticides in the U.S. We successfully used a combination of remotely-sensed data, GIS-based methods and fieldwork to select study fields and recruit participants in Illinois, a state with high corn production and heavy atrazine use. Our several-step process consisted of the identification of potential study fields and residential areas using aerial photography; verification of crop patterns and land use via site visits; development of a GIS-based algorithm to define recruitment areas around crop fields; acquisition of geocoded household-level data within each recruitment area from a commercial vendor; and confirmation of final participant household locations via ground truthing. The use of these procedures resulted in a sufficient sample of participants from 14 recruitment areas in seven Illinois counties. One of the challenges in pesticide research is the identification and recruitment of study participants, which is time consuming and costly, especially when the study site is in a remote location. We have demonstrated how GIS-based processes can be used to recruit participants, increase efficiency and enhance accuracy. The method that we used ultimately made it possible to collect biological samples from a specific demographic group within strictly defined exposure areas, with little advance knowledge of the location or population.

Applications of measures of cumulative exposure to assessing air pollution health effects

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

Abbey, D.E.; Euler, G.L.; Magie, A.R.

A method for assessing the health effects of long-term cumulative exposures to air pollutants or other environmental exposures is proposed and illustrated using self-reported symptoms of chronic obstructive pulmonary disease (COPD) for a population of 7,343 non-smokers. Using zip code by month, residence histories, and interpolated exposure estimates from the network of California air monitoring stations, two alternative exposure indices were calculated to estimate cumulative exposure over an 11-yr period above different threshold levels for each of four pollutants. The indices were used with multiple logistic regression models to form dose-response curves for relative risks adjusting for covariates. Statistically significantmore » effects were noted for total suspended particulates, total oxidants, sulfur dioxide, and passive smoking. A description is also given of how the indices are currently being used in a 10-yr follow-up of the study population. This follow-up study is utilizing data collected by the National Cancer Institute-funded Adventist Health Study and has mortality, cancer incidence, heart disease incidence, and change in self-reported COPD symptoms as outcomes.« less

Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example.

PubMed

Guo, How-Ran

2011-10-20

Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.

Effect decomposition in the presence of an exposure-induced mediator-outcome confounder

PubMed Central

VanderWeele, Tyler J.; Vansteelandt, Stijn; Robins, James M.

2014-01-01

Methods from causal mediation analysis have generalized the traditional approach to direct and indirect effects in the epidemiologic and social science literature by allowing for interaction and non-linearities. However, the methods from the causal inference literature have themselves been subject to a major limitation in that the so-called natural direct and indirect effects that are employed are not identified from data whenever there is a variable that is affected by the exposure, which also confounds the relationship between the mediator and the outcome. In this paper we describe three alternative approaches to effect decomposition that give quantities that can be interpreted as direct and indirect effects, and that can be identified from data even in the presence of an exposure-induced mediator-outcome confounder. We describe a simple weighting-based estimation method for each of these three approaches, illustrated with data from perinatal epidemiology. The methods described here can shed insight into pathways and questions of mediation even when an exposure-induced mediator-outcome confounder is present. PMID:24487213

Lung cancer mortality and exposure to polycyclic aromatic hydrocarbons in British coke oven workers

PubMed Central

2013-01-01

Background Workers on coke oven plants may be exposed to potentially carcinogenic polycyclic aromatic hydrocarbons (PAHs), particularly during work on the ovens tops. Two cohorts, employees of National Smokeless Fuels (NSF) and the British Steel Corporation (BSC) totalling more than 6,600 British coke plant workers employed in 1967, had been followed up to mid-1987 for mortality. Previous analyses suggested an excess in lung cancer risk of around 25%, or less when compared with Social Class IV (‘partly skilled’). Analyses based on internal comparisons within the cohorts identified statistical associations with estimates of individual exposures, up to the start of follow-up, to benzene-soluble materials (BSM), widely used as a metric for mixtures of PAHs. Some associations were also found with times spent in certain coke ovens jobs with specific exposure scenarios, but results were not consistent across the two cohorts and limitations in the exposure estimates were noted. The present study was designed to reanalyse the existing data on lung cancer mortality, incorporating revised and improved exposure estimates to BSM and to benzo[a]pyrene (B[a]P), including increments during the follow-up and a lag for latency. Methods Mean annual average concentrations of both BSM and B[a]P were estimated by analysis of variance (ANOVA) from concentration measurements at all NSF and six BSC plants, and summarised by job and plant, with a temporal trend (for the BSM only). These were combined with subjects’ work histories, to produce exposure estimates in each year of follow-up, with a 10-year lag to allow for latency. Exposures to BSM and to B[a]P were sufficiently uncorrelated to permit analysis in relation to each variable separately. Lung cancer death risks during the follow-up were analysed in relation to the estimated time-dependent exposures, both continuous and grouped, using Cox regression models, with adjustment for age. Results Changing the exposure estimates changed the estimated relative risks compared with earlier results, but the new analyses showed no significant trends with continuous measures of exposure to either BSM or B[a]P, nor with time spent on ovens tops. Analyses with grouped exposures showed mixed results. Across all BSC plants, the relative risk coefficient for working 5 or more years on ovens tops, where the exposures were highest, was 1.81, which was statistically significant. However, results for those with 0–5 years on ovens tops did not suggest a trend; the evidence for an underlying relationship was thus suggestive but not strong. Conclusions The new results are in line with previous findings; they show some signs consistent with an effect of coke ovens work on lung cancer risk, especially on ovens tops, but the preponderant absence of significant results, and the inconsistencies between results for NSF and BSC, highlight how little evidence there is in these data of any effect. PMID:24131617

Method for minimizing the radiation exposure from scoliosis radiographs. [X ray

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

De Smet, A.A.; Fritz, S.L.; Asher, M.A.

1981-01-01

The radiation exposure resulting from standard scoliosis radiographs was determined for eighteen adolescent girls. The risk of inducing breast cancer was estimated from the skin-exposure doses. The average skin exposure to the breasts was 59.6 millirads (0.59 mGy) for the anteroposterior radiograph. Assuming a total of twenty-two anteroposterior radiographs during a course of treatment, the cumulative exposure would result in a 1.35% relative increase in the risk of development of breast cancer. By utilizing collimation of the x-ray beam and proper selection of grids, films, and screens, the radiation risk of scoliosis radiographs is minimized.

A LITERATURE REVIEW OF WIPE SAMPLING METHODS FOR CHEMICAL WARFARE AGENTS AND TOXIC INDUSTRIAL CHEMICALS

EPA Science Inventory

Wipe sampling is an important technique for the estimation of contaminant deposition in buildings, homes, or outdoor surfaces as a source of possible human exposure. Numerous

methods of wipe sampling exist, and each method has its own specification for the type of wipe, we...

Community exposures to airborne agricultural pesticides in California: ranking of inhalation risks.

PubMed Central

Lee, Sharon; McLaughlin, Robert; Harnly, Martha; Gunier, Robert; Kreutzer, Richard

2002-01-01

We assessed inhalation risks to California communities from airborne agricultural pesticides by probability distribution analysis using ambient air data provided by the California Air Resources Board and the California Department of Pesticide Regulation. The pesticides evaluated include chloropicrin, chlorothalonil, chlorpyrifos, S,S,S-tributyl phosphorotrithioate, diazinon, 1,3-dichloropropene, dichlorvos (naled breakdown product), endosulfan, eptam, methidathion, methyl bromide, methyl isothiocyanate (MITC; metam sodium breakdown product), molinate, propargite, and simazine. Risks were estimated for the median and 75th and 95th percentiles of probability (50, 25, and 5% of the exposed populations). Exposure estimates greater than or equal to noncancer reference values occurred for 50% of the exposed populations (adults and children) for MITC subchronic and chronic exposures, methyl bromide subchronic exposures (year 2000 monitoring), and 1,3-dichloropropene subchronic exposures (1990 monitoring). Short-term chlorpyrifos exposure estimates exceeded the acute reference value for 50% of children (not adults) in the exposed population. Noncancer risks were uniformly higher for children due to a proportionately greater inhalation rate-to-body weight ratio compared to adults and other factors. Target health effects of potential concern for these exposures include neurologic effects (methyl bromide and chlorpyrifos) and respiratory effects (1,3-dichloropropene and MITC). The lowest noncancer risks occurred for simazine and chlorothalonil. Lifetime cancer risks of one-in-a-million or greater were estimated for 50% of the exposed population for 1,3-dichloropropene (1990 monitoring) and 25% of the exposed populations for methidathion and molinate. Pesticide vapor pressure was found to be a better predictor of inhalation risk compared to other methods of ranking pesticides as potential toxic air contaminants. PMID:12460795

Multifactorial analysis of human blood cell responses to clinical total body irradiation

NASA Technical Reports Server (NTRS)

Yuhas, J. M.; Stokes, T. R.; Lushbaugh, C. C.

1972-01-01

Multiple regression analysis techniques are used to study the effects of therapeutic radiation exposure, number of fractions, and time on such quantal responses as tumor control and skin injury. The potential of these methods for the analysis of human blood cell responses is demonstrated and estimates are given of the effects of total amount of exposure and time of protraction in determining the minimum white blood cell concentration observed after exposure of patients from four disease groups.

Estimating carbon monoxide exposure

NASA Technical Reports Server (NTRS)

Edgerley, R. H.

1971-01-01

Method predicts effects of carbon monoxide on astronauts confined in spacecraft cabin atmospheres. Information on need for low toxicity level also applies to confined spaces. Benefits are applicable to industry and public health.

Comparison of high intensity focused ultrasound (HIFU) exposures using empirical and backscatter attenuation estimation methods

NASA Astrophysics Data System (ADS)

Civale, John; Ter Haar, Gail; Rivens, Ian; Bamber, Jeff

2005-09-01

Currently, the intensity to be used in our clinical HIFU treatments is calculated from the acoustic path lengths in different tissues measured on diagnostic ultrasound images of the patient in the treatment position, and published values of ultrasound attenuation coefficients. This yields an approximate value for the acoustic power at the transducer required to give a stipulated focal intensity in situ. Estimation methods for the actual acoustic attenuation have been investigated in large parts of the tissue path overlying the target volume from the backscattered ultrasound signal for each patient (backscatter attenuation estimation: BAE). Several methods have been investigated. The backscattered echo information acquired from an Acuson scanner has been used to compute the diffraction-corrected attenuation coefficient at each frequency using two methods: a substitution method and an inverse diffraction filtering process. A homogeneous sponge phantom was used to validate the techniques. The use of BAE to determine the correct HIFU exposure parameters for lesioning has been tested in ex vivo liver. HIFU lesions created with a 1.7-MHz therapy transducer have been studied using a semiautomated image processing technique. The reproducibility of lesion size for given in situ intensities determined using BAE and empirical techniques has been compared.

Electron spin resonance analysis of tooth enamel does not indicate exposures to large radiation doses in a large proportion of distally-exposed A-bomb survivors.

PubMed

Hirai, Yuko; Kodama, Yoshiaki; Cullings, Harry M; Miyazawa, Chuzo; Nakamura, Nori

2011-01-01

The atomic bombs in Hiroshima and Nagasaki led to two different types of radiation exposure; one was direct and brief and the other was indirect and persistent. The latter (so-called exposure to residual radiation) resulted from the presence of neutron activation products in the soil, or from fission products present in the fallout. Compared with the doses from direct exposures, estimations of individual doses from residual radiation have been much more complicated, and estimates vary widely among researchers. The present report bases its conclusions on radiation doses recorded in tooth enamel from survivors in Hiroshima. Those survivors were present at distances of about 3 km or greater from the hypocenter at the time of the explosion, and have DS02 estimated doses (direct exposure doses) of less than 5 mGy (and are regarded as control subjects). Individual doses were estimated by measuring CO(2)(-) radicals in tooth enamel with the electron spin resonance (ESR; or electron paramagnetic resonance, EPR) method. The results from 56 molars donated by 49 survivors provided estimated doses which vary from -200 mGy to 500 mGy, and the median dose was 17 mGy (25% and 75% quartiles are -54 mGy and 137 mGy, respectively) for the buccal parts and 13 mGy (25% and 75% quartiles: -49 mGy and 87 mGy, respectively) for the lingual parts of the molars. Three molars had ESR-estimated doses of 300 to 400 mGy for both the buccal and lingual parts, which indicates possible exposures to excess doses of penetrating radiation, although the origin of such radiation remains to be determined. The results did not support claims that a large fraction of distally-exposed survivors received large doses (e.g. 1 Gy) of external penetrating radiation resulting from residual radiation.

Satellite constraints on surface concentrations of particulate matter

NASA Astrophysics Data System (ADS)

Ford Hotmann, Bonne

Because of the increasing evidence of the widespread adverse effects on human health from exposure to poor air quality and the recommendations of the World Health Organization to significantly reduce PM2.5 in order to reduce these risks, better estimates of surface air quality globally are required. However, surface measurements useful for monitoring particulate exposure are scarce, especially in developing countries which often experience the worst air pollution. Therefore, other methods are necessary to augment estimates in regions with limited surface observations. The prospect of using satellite observations to infer surface air quality is attractive; however, it requires knowledge of the complicated relationship between satellite-observed aerosol optical depth (AOD) and surface concentrations. This dissertation explores how satellite observations can be used in conjunction with a chemical transport model (GEOS-Chem) to better understand this relationship. First, we investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. [2009] previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ~35% of PM2.5 mass and exhibits similar seasonality to total surface PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but under represents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer. Next, we examine the usefulness of deriving premature mortality estimates from "satellite-based" PM2.5 concentrations. In particular, we examine how uncertainties in the model AOD-to-surface-PM2.5 relationship, satellite retrieved AOD, and particulars of the concentration-response function can impact these mortality estimates. We find that the satellite-based estimates suggest premature mortality due to chronic PM2.5 exposure is 2-16% higher in the U.S. and 4-13% lower in China compared to model-based estimates. However, this difference is overshadowed by the uncertainty in the methodology, which we quantify to be on order of 20% for the model-to- surface-PM2.5 relationship, 10% for the satellite AOD and 30-60% or greater with regards to the application of concentration response functions. Because there is a desire for acute exposure estimates, especially with regards to extreme events, we also examine how premature mortality due to acute exposure can be estimated from global models and satellite-observations. We find similar differences between model and satellite-based mortality estimates as with chronic exposure. However the range of uncertainty is much larger on these shorter timescales. This work suggests that although satellites can be useful for constraining model estimates of PM2.5, national mortality estimates from the two methods are not significantly different. In order to improve the efficacy of satellite-based PM2.5 mortality estimates, future work will need to focus on improving the model representation of the regional AOD-to-surface-PM2.5 relationship, reducing biases in satellite-retrieved AOD and advancing our understanding of personal and population-level responses to PM2.5 exposure.

Human exposure and internal dose assessments of acrylamide in food.

PubMed

Dybing, E; Farmer, P B; Andersen, M; Fennell, T R; Lalljie, S P D; Müller, D J G; Olin, S; Petersen, B J; Schlatter, J; Scholz, G; Scimeca, J A; Slimani, N; Törnqvist, M; Tuijtelaars, S; Verger, P

2005-03-01

This review provides a framework contributing to the risk assessment of acrylamide in food. It is based on the outcome of the ILSI Europe FOSIE process, a risk assessment framework for chemicals in foods and adds to the overall framework by focusing especially on exposure assessment and internal dose assessment of acrylamide in food. Since the finding that acrylamide is formed in food during heat processing and preparation of food, much effort has been (and still is being) put into understanding its mechanism of formation, on developing analytical methods and determination of levels in food, and on evaluation of its toxicity and potential toxicity and potential human health consequences. Although several exposure estimations have been proposed, a systematic review of key information relevant to exposure assessment is currently lacking. The European and North American branches of the International Life Sciences Institute, ILSI, discussed critical aspects of exposure assessment, parameters influencing the outcome of exposure assessment and summarised data relevant to the acrylamide exposure assessment to aid the risk characterisation process. This paper reviews the data on acrylamide levels in food including its formation and analytical methods, the determination of human consumption patterns, dietary intake of the general population, estimation of maximum intake levels and identification of groups of potentially high intakes. Possible options and consequences of mitigation efforts to reduce exposure are discussed. Furthermore the association of intake levels with biomarkers of exposure and internal dose, considering aspects of bioavailability, is reviewed, and a physiologically-based toxicokinetic (PBTK) model is described that provides a good description of the kinetics of acrylamide in the rat. Each of the sections concludes with a summary of remaining gaps and uncertainties.

Exposure–Response Analyses of Asbestos and Lung Cancer Subtypes in a Pooled Analysis of Case–Control Studies

PubMed Central

Vermeulen, Roel; Schüz, Joachim; Kromhout, Hans; Pesch, Beate; Peters, Susan; Behrens, Thomas; Portengen, Lützen; Mirabelli, Dario; Gustavsson, Per; Kendzia, Benjamin; Almansa, Josue; Luzon, Veronique; Vlaanderen, Jelle; Stücker, Isabelle; Guida, Florence; Consonni, Dario; Caporaso, Neil; Landi, Maria Teresa; Field, John; Brüske, Irene; Wichmann, Heinz-Erich; Siemiatycki, Jack; Parent, Marie-Elise; Richiardi, Lorenzo; Merletti, Franco; Jöckel, Karl-Heinz; Ahrens, Wolfgang; Pohlabeln, Hermann; Plato, Nils; Tardón, Adonina; Zaridze, David; McLaughlin, John; Demers, Paul; Szeszenia-Dabrowska, Neonila; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Stanescu Dumitru, Rodica; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Boffetta, Paolo; Bueno-de-Mesquita, Bas; Forastiere, Francesco; Brüning, Thomas; Straif, Kurt

2017-01-01

Background: Evidence is limited regarding risk and the shape of the exposure–response curve at low asbestos exposure levels. We estimated the exposure–response for occupational asbestos exposure and assessed the joint effect of asbestos exposure and smoking by sex and lung cancer subtype in general population studies. Methods: We pooled 14 case–control studies conducted in 1985–2010 in Europe and Canada, including 17,705 lung cancer cases and 21,813 controls with detailed information on tobacco habits and lifetime occupations. We developed a quantitative job-exposure-matrix to estimate job-, time period-, and region-specific exposure levels. Fiber-years (ff/ml-years) were calculated for each subject by linking the matrix with individual occupational histories. We fit unconditional logistic regression models to estimate odds ratios (ORs), 95% confidence intervals (CIs), and trends. Results: The fully adjusted OR for ever-exposure to asbestos was 1.24 (95% CI, 1.18, 1.31) in men and 1.12 (95% CI, 0.95, 1.31) in women. In men, increasing lung cancer risk was observed with increasing exposure in all smoking categories and for all three major lung cancer subtypes. In women, lung cancer risk for all subtypes was increased in current smokers (ORs ~two-fold). The joint effect of asbestos exposure and smoking did not deviate from multiplicativity among men, and was more than additive among women. Conclusions: Our results in men showed an excess risk of lung cancer and its subtypes at low cumulative exposure levels, with a steeper exposure–response slope in this exposure range than at higher, previously studied levels. (See video abstract at, http://links.lww.com/EDE/B161.) PMID:28141674

Prenatal Exposure to Traffic-Related Air Pollution and Ultrasound Measures of Fetal Growth in the INMA Sabadell Cohort

PubMed Central

Aguilera, Inmaculada; Garcia-Esteban, Raquel; Iñiguez, Carmen; Nieuwenhuijsen, Mark J.; Rodríguez, Àgueda; Paez, Montserrat; Ballester, Ferran; Sunyer, Jordi

2010-01-01

Background Few studies have used longitudinal ultrasound measurements to assess the effect of traffic-related air pollution on fetal growth. Objective We examined the relationship between exposure to nitrogen dioxide (NO2) and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] on fetal growth assessed by 1,692 ultrasound measurements among 562 pregnant women from the Sabadell cohort of the Spanish INMA (Environment and Childhood) study. Methods We used temporally adjusted land-use regression models to estimate exposures to NO2 and BTEX. We fitted mixed-effects models to estimate longitudinal growth curves for femur length (FL), head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), and estimated fetal weight (EFW). Unconditional and conditional SD scores were calculated at 12, 20, and 32 weeks of gestation. Sensitivity analyses were performed considering time–activity patterns during pregnancy. Results Exposure to BTEX from early pregnancy was negatively associated with growth in BPD during weeks 20–32. None of the other fetal growth parameters were associated with exposure to air pollution during pregnancy. When considering only women who spent < 2 hr/day in nonresidential outdoor locations, effect estimates were stronger and statistically significant for the association between NO2 and growth in HC during weeks 12–20 and growth in AC, BPD, and EFW during weeks 20–32. Conclusions Our results lend some support to an effect of exposure to traffic-related air pollutants from early pregnancy on fetal growth during mid-pregnancy. PMID:20103496

Estimation of Inorganic Arsenic Exposure in Populations With Frequent Seafood Intake: Evidence From MESA and NHANES

PubMed Central

Jones, Miranda R.; Tellez-Plaza, Maria; Vaidya, Dhananjay; Grau, Maria; Francesconi, Kevin A.; Goessler, Walter; Guallar, Eliseo; Post, Wendy S.; Kaufman, Joel D.; Navas-Acien, Ana

2016-01-01

The sum of urinary inorganic arsenic (iAs) and methylated arsenic (monomethylarsonate and dimethylarsinate (DMA)) species is the main biomarker of iAs exposure. Assessing iAs exposure, however, is difficult in populations with moderate-to-high seafood intakes. In the present study, we used subsamples from the Multi-Ethnic Study of Atherosclerosis (2000–2002) (n = 310) and the 2003–2006 National Health and Nutrition Examination Survey (n = 1,175). We calibrated urinary concentrations of non–seafood-derived iAs, DMA, and methylarsonate, as well as the sum of inorganic and methylated arsenic species, in the Multi-Ethnic Study of Atherosclerosis and of DMA in the National Health and Nutrition Examination Survey by regressing their original concentrations by arsenobetaine and extracting model residuals. To confirm that calibrated biomarkers reflected iAs exposure but not seafood intake, we compared urinary arsenic concentrations by levels of seafood and rice intakes. Self-reported seafood intakes, estimated n-3 polyunsaturated fatty acid levels, and measured n-3 polyunsaturated fatty acid levels were positively associated with the original urinary arsenic biomarkers. Using the calibrated arsenic biomarkers, we found a marked attenuation of the associations with self-reported seafood intake and estimated or measured n-3 fatty acids, whereas associations with self-reported rice intake remained similar. Our residual-based method provides estimates of iAs exposure and metabolism for each participant that no longer reflect seafood intake and can facilitate research about low-to-moderate levels of iAs exposure in populations with high seafood intakes. PMID:27702745

The economic burden of lung cancer and mesothelioma due to occupational and para-occupational asbestos exposure

PubMed Central

Tompa, Emile; Kalcevich, Christina; McLeod, Chris; Lebeau, Martin; Song, Chaojie; McLeod, Kim; Kim, Joanne; Demers, Paul A

2017-01-01

Objectives To estimate the economic burden of lung cancer and mesothelioma due to occupational and para-occupational asbestos exposure in Canada. Methods We estimate the lifetime cost of newly diagnosed lung cancer and mesothelioma cases associated with occupational and para-occupational asbestos exposure for calendar year 2011 based on the societal perspective. The key cost components considered are healthcare costs, productivity and output costs, and quality of life costs. Results There were 427 cases of newly diagnosed mesothelioma cases and 1904 lung cancer cases attributable to asbestos exposure in 2011 for a total of 2331 cases. Our estimate of the economic burden is $C831 million in direct and indirect costs for newly identified cases of mesothelioma and lung cancer and $C1.5 billion in quality of life costs based on a value of $C100 000 per quality-adjusted life year. This amounts to $C356 429 and $C652 369 per case, respectively. Conclusions The economic burden of lung cancer and mesothelioma associated with occupational and para-occupational asbestos exposure is substantial. The estimate identified is for 2331 newly diagnosed, occupational and para-occupational exposure cases in 2011, so it is only a portion of the burden of existing cases in that year. Our findings provide important information for policy decision makers for priority setting, in particular the merits of banning the mining of asbestos and use of products containing asbestos in countries where they are still allowed and also the merits of asbestos removal in older buildings with asbestos insulation. PMID:28756416

Respirator use and its impact on particulate matter exposure in aluminum manufacturing facilities.

PubMed

Liu, Sa; Noth, Elizabeth; Eisen, Ellen; Cullen, Mark R; Hammond, Katharine

2018-05-31

Objectives As part of a large epidemiologic study of particulate health effect, this study aimed to report respirator use among total particulate matter (TPM) samples collected in a major aluminum manufacturing company from 1966‒2013 and evaluate the impact of respirator-use adjustment on exposure estimation. Methods Descriptive analyses were performed to evaluate respirator use across facilities and by facility type and job. Protection factors were applied to TPM measurements for recorded respirator use. Estimated TPM exposure for each job ‒ before and after respirator-use adjustment ‒ were compared to assess the impact of adjustment on exposure estimation. Results Respirator use was noted for 37% of 12 402 full-shift personal TPM samples. Measured TPM concentration ranged from less than detectable to 8220 mg/m3, with arithmetic mean, median and standard deviation being 10.6, 0.87 and 130 mg/m 3 , respectively. Respirators were used more often in smelting facilities (52% of TPM measurements) than in fabricating (17%) or refinery facilities (28%) (P<0.01). Sixty-two percent of jobs in smelting facilities were subject to respirator-use adjustment, whereas it was 20% and 70% in fabricating and refinery facilities, respectively. Applying protection factors to TPM measurements significantly reduced estimated job mean TPM exposures and changed exposure categories in these facilities, with larger impact in smelting than fabricating facilities. Conclusions Respirator use varied by time, facility and job. Adjusting respirator use resulted in differential impact in smelting and fabricating facilities, which will need to be incorporated into ongoing epidemiologic studies accordingly.

Influence of exposure assessment and parameterization on exposure response. Aspects of epidemiologic cohort analysis using the Libby Amphibole asbestos worker cohort.

PubMed

Bateson, Thomas F; Kopylev, Leonid

2015-01-01

Recent meta-analyses of occupational epidemiology studies identified two important exposure data quality factors in predicting summary effect measures for asbestos-associated lung cancer mortality risk: sufficiency of job history data and percent coverage of work history by measured exposures. The objective was to evaluate different exposure parameterizations suggested in the asbestos literature using the Libby, MT asbestos worker cohort and to evaluate influences of exposure measurement error caused by historically estimated exposure data on lung cancer risks. Focusing on workers hired after 1959, when job histories were well-known and occupational exposures were predominantly based on measured exposures (85% coverage), we found that cumulative exposure alone, and with allowance of exponential decay, fit lung cancer mortality data similarly. Residence-time-weighted metrics did not fit well. Compared with previous analyses based on the whole cohort of Libby workers hired after 1935, when job histories were less well-known and exposures less frequently measured (47% coverage), our analyses based on higher quality exposure data yielded an effect size as much as 3.6 times higher. Future occupational cohort studies should continue to refine retrospective exposure assessment methods, consider multiple exposure metrics, and explore new methods of maintaining statistical power while minimizing exposure measurement error.

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.

Urban and Transport Planning Related Exposures and Mortality: A Health Impact Assessment for Cities

PubMed Central

Mueller, Natalie; Rojas-Rueda, David; Basagaña, Xavier; Cirach, Marta; Cole-Hunter, Tom; Dadvand, Payam; Donaire-Gonzalez, David; Foraster, Maria; Gascon, Mireia; Martinez, David; Tonne, Cathryn; Triguero-Mas, Margarita; Valentín, Antònia; Nieuwenhuijsen, Mark

2016-01-01

Background: By 2050, nearly 70% of the global population is projected to live in urban areas. Because the environments we inhabit affect our health, urban and transport designs that promote healthy living are needed. Objective: We estimated the number of premature deaths preventable under compliance with international exposure recommendations for physical activity (PA), air pollution, noise, heat, and access to green spaces. Methods: We developed and applied the Urban and TranspOrt Planning Health Impact Assessment (UTOPHIA) tool to Barcelona, Spain. Exposure estimates and mortality data were available for 1,357,361 residents. We compared recommended with current exposure levels. We quantified the associations between exposures and mortality and calculated population attributable fractions to estimate the number of premature deaths preventable. We also modeled life-expectancy and economic impacts. Results: We estimated that annually, nearly 20% of mortality could be prevented if international recommendations for performance of PA; exposure to air pollution, noise, and heat; and access to green space were followed. Estimations showed that the greatest portion of preventable deaths was attributable to increases in PA, followed by reductions of exposure to air pollution, traffic noise, and heat. Access to green spaces had smaller effects on mortality. Compliance was estimated to increase the average life expectancy by 360 (95% CI: 219, 493) days and result in economic savings of 9.3 (95% CI: 4.9, 13.2) billion EUR/year. Conclusions: PA factors and environmental exposures can be modified by changes in urban and transport planning. We emphasize the need for a) the reduction of motorized traffic through the promotion of active and public transport and b) the provision of green infrastructure, both of which are suggested to provide opportunities for PA and for mitigation of air pollution, noise, and heat. Citation: Mueller N, Rojas-Rueda D, Basagaña X, Cirach M, Cole-Hunter T, Dadvand P, Donaire-Gonzalez D, Foraster M, Gascon M, Martinez D, Tonne C, Triguero-Mas M, Valentín A, Nieuwenhuijsen M. 2017. Urban and transport planning related exposures and mortality: a health impact assessment for cities. Environ Health Perspect 125:89–96; http://dx.doi.org/10.1289/EHP220 PMID:27346385

Benzene exposure and risk of lymphohaematopoietic cancers in 25 000 offshore oil industry workers

PubMed Central

Stenehjem, J S; Kjærheim, K; Bråtveit, M; Samuelsen, S O; Barone-Adesi, F; Rothman, N; Lan, Q; Grimsrud, T K

2015-01-01

Background: The aim of this work was to examine the risk of lymphohaematopoietic (LH) cancer according to benzene exposure among offshore workers. Methods: Cancer registry data were used to identify 112 cancer cases diagnosed during 1999–2011 in a cohort of 24 917 Norwegian men reporting offshore work between 1965 and 1999. Analyses were conducted according to a stratified case–cohort design with a reference subcohort of 1661 workers. Cox regression was used to estimate hazard ratios with 95% confidence intervals, adjusted for other benzene exposure and smoking. Results: Most workers were exposed to benzene for <15 years. The upper range values of average intensity and cumulative exposure were estimated to 0.040 p.p.m. and 0.948 p.p.m.-years, respectively. Risks were consistently elevated among exposed workers for all LH cancers combined and for most subgroups, although case numbers were small and yielded imprecise risk estimates. There was evidence of dose-related risk patterns according to cumulative exposure for acute myeloid leukaemia (AML), multiple myeloma (MM) (P trends 0.052 and 0.024, respectively), and suggestively so for chronic lymphocytic leukaemia (CLL) according to average intensity (P trend 0.094). Conclusions: Our results support an association between cumulative and intensity metrics of low-level benzene exposure and risk for AML, MM, and suggestively for CLL. PMID:25867262

In situ LTE exposure of the general public: Characterization and extrapolation.

PubMed

Joseph, Wout; Verloock, Leen; Goeminne, Francis; Vermeeren, Günter; Martens, Luc

2012-09-01

In situ radiofrequency (RF) exposure of the different RF sources is characterized in Reading, United Kingdom, and an extrapolation method to estimate worst-case long-term evolution (LTE) exposure is proposed. All electric field levels satisfy the International Commission on Non-Ionizing Radiation Protection (ICNIRP) reference levels with a maximal total electric field value of 4.5 V/m. The total values are dominated by frequency modulation (FM). Exposure levels for LTE of 0.2 V/m on average and 0.5 V/m maximally are obtained. Contributions of LTE to the total exposure are limited to 0.4% on average. Exposure ratios from 0.8% (LTE) to 12.5% (FM) are obtained. An extrapolation method is proposed and validated to assess the worst-case LTE exposure. For this method, the reference signal (RS) and secondary synchronization signal (S-SYNC) are measured and extrapolated to the worst-case value using an extrapolation factor. The influence of the traffic load and output power of the base station on in situ RS and S-SYNC signals are lower than 1 dB for all power and traffic load settings, showing that these signals can be used for the extrapolation method. The maximal extrapolated field value for LTE exposure equals 1.9 V/m, which is 32 times below the ICNIRP reference levels for electric fields. Copyright © 2012 Wiley Periodicals, Inc.

Estimation of occupational cosmic radiation exposure among airline personnel: Agreement between a job-exposure matrix, aggregate, and individual dose estimates.

PubMed

Talibov, Madar; Salmelin, Raili; Lehtinen-Jacks, Susanna; Auvinen, Anssi

2017-04-01

Job-exposure matrices (JEM) are used for exposure assessment in occupational studies, but they can involve errors. We assessed agreement between the Nordic Occupational Cancer Studies JEM (NOCCA-JEM) and aggregate and individual dose estimates for cosmic radiation exposure among Finnish airline personnel. Cumulative cosmic radiation exposure for 5,022 airline crew members was compared between a JEM and aggregate and individual dose estimates. The NOCCA-JEM underestimated individual doses. Intraclass correlation coefficient was 0.37, proportion of agreement 64%, kappa 0.46 compared with individual doses. Higher agreement was achieved with aggregate dose estimates, that is annual medians of individual doses and estimates adjusted for heliocentric potentials. The substantial disagreement between NOCCA-JEM and individual dose estimates of cosmic radiation may lead to exposure misclassification and biased risk estimates in epidemiological studies. Using aggregate data may provide improved estimates. Am. J. Ind. Med. 60:386-393, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Development of a Job-Exposure Matrix (AsbJEM) to Estimate Occupational Exposure to Asbestos in Australia.

PubMed

van Oyen, Svein C; Peters, Susan; Alfonso, Helman; Fritschi, Lin; de Klerk, Nicholas H; Reid, Alison; Franklin, Peter; Gordon, Len; Benke, Geza; Musk, Arthur W

2015-07-01

Occupational exposure data on asbestos are limited and poorly integrated in Australia so that estimates of disease risk and attribution of disease causation are usually calculated from data that are not specific for local conditions. To develop a job-exposure matrix (AsbJEM) to estimate occupational asbestos exposure levels in Australia, making optimal use of the available exposure data. A dossier of all available exposure data in Australia and information on industry practices and controls was provided to an expert panel consisting of three local industrial hygienists with thorough knowledge of local and international work practices. The expert panel estimated asbestos exposures for combinations of occupation, industry, and time period. Intensity and frequency grades were estimated to enable the calculation of annual exposure levels for each occupation-industry combination for each time period. Two indicators of asbestos exposure intensity (mode and peak) were used to account for different patterns of exposure between occupations. Additionally, the probable type of asbestos fibre was determined for each situation. Asbestos exposures were estimated for 537 combinations of 224 occupations and 60 industries for four time periods (1943-1966; 1967-1986; 1987-2003; ≥2004). Workers in the asbestos manufacturing, shipyard, and insulation industries were estimated to have had the highest average exposures. Up until 1986, 46 occupation-industry combinations were estimated to have had exposures exceeding the current Australian exposure standard of 0.1 f ml(-1). Over 90% of exposed occupations were considered to have had exposure to a mixture of asbestos varieties including crocidolite. The AsbJEM provides empirically based quantified estimates of asbestos exposure levels for Australian jobs since 1943. This exposure assessment application will contribute to improved understanding and prediction of asbestos-related diseases and attribution of disease causation. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Risk of DDT residue in maize consumed by infants as complementary diet in southwest Ethiopia.

PubMed

Mekonen, Seblework; Lachat, Carl; Ambelu, Argaw; Steurbaut, Walter; Kolsteren, Patrick; Jacxsens, Liesbeth; Wondafrash, Mekitie; Houbraken, Michael; Spanoghe, Pieter

2015-04-01

Infants in Ethiopia are consuming food items such as maize as a complementary diet. However, this may expose infants to toxic contaminants like DDT. Maize samples were collected from the households visited during a consumption survey and from markets in Jimma zone, southwestern Ethiopia. The residues of total DDT and its metabolites were analyzed using the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method combined with dispersive solid phase extraction cleanup (d-SPE). Deterministic and probabilistic methods of analysis were applied to determine the consumer exposure of infants to total DDT. The results from the exposure assessment were compared with the health based guidance value in this case the provisional tolerable daily intake (PTDI). All maize samples (n=127) were contaminated by DDT, with a mean concentration of 1.770 mg/kg, which was far above the maximum residue limit (MRL). The mean and 97.5 percentile (P 97.5) estimated daily intake of total DDT for consumers were respectively 0.011 and 0.309 mg/kg bw/day for deterministic and 0.011 and 0.083 mg/kg bw/day for probabilistic exposure assessment. For total infant population (consumers and non-consumers), the 97.5 percentile estimated daily intake were 0.265 and 0.032 mg/kg bw/day from the deterministic and probabilistic exposure assessments, respectively. Health risk estimation revealed that, the mean and 97.5 percentile for consumers, and 97.5 percentile estimated daily intake of total DDT for total population were above the PTDI. Therefore, in Ethiopia, the use of maize as complementary food for infants may pose a health risk due to DDT residue. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of vibration produced by the grinders used in the shipbuilding industry of Korea.

PubMed

Park, Hee-Sok; Yim, Sang-Hyuk

2007-04-01

The objective of this study is to estimate the prevalence of finger blanching among the workers in a shipyard of Korea using the dose-response relationship suggested by ISO 5349. The characteristics of vibration exposure produced by six types of grinders were investigated. Vibration measurement was made under the real work conditions. Exposure time was estimated by questionnaire and direct observation. In addition, cold provocation tests were performed, and the results from the tests were compared with the estimated prevalence. As a result, 4 hour-energy-equivalent frequency-weighted accelerations of the finishing grinding (FG) and the prepainting grinding (PG) jobs were 6.23 m/s(2) and 13.39 m/s(2), respectively. The mean exposure time for holding the grinders was 4.64 h per day. Using the ISO 5349 method, it was predicted that after exposure to vibration for 10.79 yr, about a half of the FG workers could develop finger blanching. For the PG workers, the corresponding predicted latency was 5.02 yr. A discrepancy was found between the results from the ISO relationship and those from the cold provocation tests. A linear regression model was suggested employing vibration acceleration and vibration exposure time as explanatory variables for vascular dysfunction.

Urinary Biomarker, Dermal, and Air Measurement Results for 2,4-D and Chlorpyrifos Farm Applicators in the Agricultural Health Study

PubMed Central

Thomas, Kent; Dosemeci, Mustafa; Hoppin, Jane A.; Sheldon, Linda; Croghan, Carry; Gordon, Sydney; Jones, Martin; Reynolds, Stephen; Raymer, James; Akland, Gerald; Lynch, Charles F.; Knott, Charles; Sandler, Dale P.; Blair, Aaron; Alavanja, Michael

2010-01-01

Epidemiologic studies increasingly rely on improved exposure assessments to characterize pesticide exposures in agricultural populations. A subset of private pesticide applicators in the AHS epidemiological cohort was monitored around the time of their agricultural use of 2,4-D and chlorpyrifos to assess exposure levels and potential exposure factors. Measurements included pre- and post-application urine samples, and patch, hand wipe, and personal air samples. Broadcast or hand spray application methods were used by applicators for 2,4-D products. Chlorpyrifos products were applied using spray applications and in-furrow application of granular products. Geometric mean (GM) values for 69 2,4-D applicators were 7.8 and 25 µg/L in pre- and post-application urine, respectively (p < 0.05 for difference); 0.39 mg for estimated hand loading; 2.9 mg for estimated body loading; and 0.37 µg/m3 for concentration in personal air. Significant correlations were found between all media for 2,4-D. GM values for 17 chlorpyrifos applicators were 11 µg/L in both pre- and post-application urine for the 3,5,6-trichloro-2-pyridinol metabolite, 0.28 mg for body loading, and 0.49 µg/m3 for air concentration. Only 53% of the chlorpyrifos applicators had measureable hand loading results; their median hand loading was 0.02 mg. Factors associated with differences in 2,4-D measurements included application method and glove use; and, for hand spray applicators, use of adjuvants, equipment repair, duration of use, and contact with treated vegetation. Spray applications of liquid chlorpyrifos products were associated with higher measurements than in-furrow granular product applications. This study provides information on exposures and possible exposure determinants for several application methods commonly used by farmers in the cohort and will provide information to assess and refine exposure classification in the Agricultural Health Study. Results may also be of use in pesticide safety education for reducing exposures to applied pesticides. PMID:19240759

A MULTI-RESIDUE METHOD FOR THE ANALYSIS OF INSECTICIDES COLLECTED ON COTTON SURFACE WIPES

EPA Science Inventory

A method was developed for the extraction, clean-up, and analysis of multiple pesticides from cotton wipe media used in human exposure studies to collect residues from residential hard surfaces. Measurements of pesticides are critical for estimating dermal and indirect ingestion ...

Asbestos exposure--quantitative assessment of risk

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

Hughes, J.M.; Weill, H.

Methods for deriving quantitative estimates of asbestos-associated health risks are reviewed and their numerous assumptions and uncertainties described. These methods involve extrapolation of risks observed at past relatively high asbestos concentration levels down to usually much lower concentration levels of interest today--in some cases, orders of magnitude lower. These models are used to calculate estimates of the potential risk to workers manufacturing asbestos products and to students enrolled in schools containing asbestos products. The potential risk to workers exposed for 40 yr to 0.5 fibers per milliliter (f/ml) of mixed asbestos fiber type (a permissible workplace exposure limit under considerationmore » by the Occupational Safety and Health Administration (OSHA) ) are estimated as 82 lifetime excess cancers per 10,000 exposed. The risk to students exposed to an average asbestos concentration of 0.001 f/ml of mixed asbestos fiber types for an average enrollment period of 6 school years is estimated as 5 lifetime excess cancers per one million exposed. If the school exposure is to chrysotile asbestos only, then the estimated risk is 1.5 lifetime excess cancers per million. Risks from other causes are presented for comparison; e.g., annual rates (per million) of 10 deaths from high school football, 14 from bicycling (10-14 yr of age), 5 to 20 for whooping cough vaccination. Decisions concerning asbestos products require participation of all parties involved and should only be made after a scientifically defensible estimate of the associated risk has been obtained. In many cases to date, such decisions have been made without adequate consideration of the level of risk or the cost-effectiveness of attempts to lower the potential risk. 73 references.« less

Estimation of respirable dust exposure among coal miners in South Africa.

PubMed

Naidoo, Rajen; Seixas, Noah; Robins, Thomas

2006-06-01

The use of retrospective occupational hygiene data for epidemiologic studies is useful in determining exposure-outcome relationships, but the potential for exposure misclassification is high. Although dust sampling in the South African coal industry has been a legal requirement for several decades, these historical data are not readily adequate for estimating past exposures. This study describes the respirable coal mine dust levels in three South African coal mines over time. Each of the participating mining operations had well-documented dust sampling information that was used to describe historical trends in dust exposure. Investigator-collected personal dust samples were taken using standardized techniques from the face, backbye (underground jobs not at the coal face), and surface from 50 miners at each mine, repeated over three sampling cycles. Job histories and exposure information was obtained from a sample of 684 current miners and 188 ex-miners. Linear models were developed to estimate the exposure levels associated with work in each mine, exposure zone, and over time using a combination of operator-collected historical data and investigator-collected samples. The estimated levels were then combined with work history information to calculate cumulative exposure metrics for the miner cohort. The mean historical and investigator-collected respirable dust levels were within international norms and South African standards. Silica content of the dust samples was also below the 5% regulatory action level. Mean respirable dust concentrations at the face, based on investigator-collected samples, were 0.9 mg/m(3), 1.3 mg/m(3), and 1.9 mg/m(3) at Mines 1, 2, and 3, respectively. The operator-collected samples showed considerable variability across exposure zones, mines, and time, with the annual means at the face ranging from 0.4 mg/m(3) to 2.9 mg/m(3). Statistically significant findings were found between operator- and investigator-collected dust samples. Model-based arithmetic mean dust estimates at the face were 1.2 mg/m(3), 2.0 mg/m(3), and 0.9 mg/m(3) for Mines 1, 2, and 3, respectively. Using these levels, the mean cumulative exposure for the cohort was 56.8 mg-years/m(3). Current miners had a mean cumulative exposure of 66.5 mg-years/m(3), compared with ex-miners of 26.8 mg-years/m(3). Improvements in dust management or the use of different sampling equipment could account for the significant differences seen between operator- and investigator-collected data. Regression modeling for estimating mean dust levels over time using combined historical and investigator-collected data seems a reasonable method and useful in constructing models to describe cumulative exposures in a cohort of current and ex-miners.

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.

Association between Activity Space Exposure to Food Establishments and Individual Risk of Overweight

PubMed Central

Kestens, Yan; Lebel, Alexandre; Chaix, Basile; Clary, Christelle; Daniel, Mark; Pampalon, Robert; Theriault, Marius; p Subramanian, S. V.

2012-01-01

Objective Environmental exposure to food sources may underpin area level differences in individual risk for overweight. Place of residence is generally used to assess neighbourhood exposure. Yet, because people are mobile, multiple exposures should be accounted for to assess the relation between food environments and overweight. Unfortunately, mobility data is often missing from health surveys. We hereby test the feasibility of linking travel survey data with food listings to derive food store exposure predictors of overweight among health survey participants. Methods Food environment exposure measures accounting for non-residential activity places (activity spaces) were computed and modelled in Montreal and Quebec City, Canada, using travel surveys and food store listings. Models were then used to predict activity space food exposures for 5,578 participants of the Canadian Community Health Survey. These food exposure estimates, accounting for daily mobility, were used to model self-reported overweight in a multilevel framework. Median Odd Ratios were used to assess the proportion of between-neighborhood variance explained by such food exposure predictors. Results Estimates of food environment exposure accounting for both residential and non-residential destinations were significantly and more strongly associated with overweight than residential-only measures of exposure for men. For women, residential exposures were more strongly associated with overweight than non-residential exposures. In Montreal, adjusted models showed men in the highest quartile of exposure to food stores were at lesser risk of being overweight considering exposure to restaurants (OR = 0.36 [0.21–0.62]), fast food outlets (0.48 [0.30–0.79]), or corner stores (0.52 [0.35–0.78]). Conversely, men experiencing the highest proportion of restaurants being fast-food outlets were at higher risk of being overweight (2.07 [1.25–3.42]). Women experiencing higher residential exposures were at lower risk of overweight. Conclusion Using residential neighbourhood food exposure measures may underestimate true exposure and observed associations. Using mobility data offers potential for deriving activity space exposure estimates in epidemiological models. PMID:22936974

A case‐control study of airways obstruction among construction workers

PubMed Central

Welch, Laura; Ringen, Knut; Quinn, Patricia; Chen, Anna; Haas, Scott

2015-01-01

Background While smoking is the major cause of chronic obstructive pulmonary disease (COPD), occupational exposures to vapors, gases, dusts, and fumes (VGDF) increase COPD risk. This case‐control study estimated the risk of COPD attributable to occupational exposures among construction workers. Methods The study population included 834 cases and 1243 controls participating in a national medical screening program for older construction workers between 1997 and 2013. Qualitative exposure indices were developed based on lifetime work and exposure histories. Results Approximately 18% (95%CI = 2–24%) of COPD risk can be attributed to construction‐related exposures, which are additive to the risk contributed by smoking. A measure of all VGDF exposures combined was a strong predictor of COPD risk. Conclusions Construction workers are at increased risk of COPD as a result of broad and complex effects of many exposures acting independently or interactively. Control methods should be implemented to prevent worker exposures, and smoking cessation should be promoted. Am. J. Ind. Med. 58:1083–1097, 2015. © 2015 The Authors. American Journal of Industrial Medicine Published by Wiley Periodicals, Inc. PMID:26123003

The burden of cancer attributable to modifiable risk factors: the Australian cancer-PAF cohort consortium.

PubMed

Arriaga, Maria E; Vajdic, Claire M; Canfell, Karen; MacInnis, Robert; Hull, Peter; Magliano, Dianna J; Banks, Emily; Giles, Graham G; Cumming, Robert G; Byles, Julie E; Taylor, Anne W; Shaw, Jonathan E; Price, Kay; Hirani, Vasant; Mitchell, Paul; Adelstein, Barbara-Ann; Laaksonen, Maarit A

2017-06-14

To estimate the Australian cancer burden attributable to lifestyle-related risk factors and their combinations using a novel population attributable fraction (PAF) method that accounts for competing risk of death, risk factor interdependence and statistical uncertainty. 365 173 adults from seven Australian cohort studies. We linked pooled harmonised individual participant cohort data with population-based cancer and death registries to estimate exposure-cancer and exposure-death associations. Current Australian exposure prevalence was estimated from representative external sources. To illustrate the utility of the new PAF method, we calculated fractions of cancers causally related to body fatness or both tobacco and alcohol consumption avoidable in the next 10 years by risk factor modifications, comparing them with fractions produced by traditional PAF methods. Over 10 years of follow-up, we observed 27 483 incident cancers and 22 078 deaths. Of cancers related to body fatness (n=9258), 13% (95% CI 11% to 16%) could be avoided if those currently overweight or obese had body mass index of 18.5-24.9 kg/m 2 . Of cancers causally related to both tobacco and alcohol (n=4283), current or former smoking explains 13% (11% to 16%) and consuming more than two alcoholic drinks per day explains 6% (5% to 8%). The two factors combined explain 16% (13% to 19%): 26% (21% to 30%) in men and 8% (4% to 11%) in women. Corresponding estimates using the traditional PAF method were 20%, 31% and 10%. Our PAF estimates translate to 74 000 avoidable body fatness-related cancers and 40 000 avoidable tobacco- and alcohol-related cancers in Australia over the next 10 years (2017-2026). Traditional PAF methods not accounting for competing risk of death and interdependence of risk factors may overestimate PAFs and avoidable cancers. We will rank the most important causal factors and their combinations for a spectrum of cancers and inform cancer control activities. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Mortality and cancer incidence in ammonium perfluorooctanoate production workers

PubMed Central

Raleigh, Katherine K; Alexander, Bruce H; Olsen, Geary W; Ramachandran, Gurumurthy; Morey, Sandy Z; Church, Timothy R; Logan, Perry W; Scott, Laura L F; Allen, Elizabeth M

2014-01-01

Objective To evaluate mortality and cancer incidence in a cohort of ammonium perfluorooctanoate (APFO) exposed workers. Methods We linked a combined cohort (n=9027) of employees from APFO and non-APFO production facilities in Minnesota to the National Death Index and to cancer registries of Minnesota and Wisconsin. Industrial hygiene data and expert evaluation were used to create a task-based job exposure matrix to estimate APFO exposure. Standardised mortality ratios were estimated using Minnesota population rates. HRs and 95% CIs for time-dependent cumulative APFO exposure were estimated with an extended Cox model. A priori outcomes of interest included cancers of the liver, pancreas, testes, kidney, prostate and breast, and mortality from cardiovascular, cerebrovascular and chronic renal diseases. Results Mortality rates in the APFO-exposed cohort were at or below the expected, compared with Minnesota. The HR for dying from the cancer and non-cancer outcomes of interest did not show an association with APFO exposure. Similarly, there was little evidence that the incident cancers were associated with APFO exposure. Compared to the non-exposed population, modestly elevated, but quite imprecise HRs were observed in the higher-exposure quartiles for bladder cancer (HR=1.66, 95% CI 0.86 to 3.18) and pancreatic cancer (HR=1.36, 95% CI 0.59 to 3.11). No association was observed between APFO exposure and kidney, prostate or breast cancers. Conclusions This analysis did not support an association between occupational APFO exposure and the evaluated health endpoints, however, the study had limited power to evaluate some conditions of interest. PMID:24832944

Combining Propensity Score Methods and Complex Survey Data to Estimate Population Treatment Effects

ERIC Educational Resources Information Center

Stuart, Elizabeth A.; Dong, Nianbo; Lenis, David

2016-01-01

Complex surveys are often used to estimate causal effects regarding the effects of interventions or exposures of interest. Propensity scores (Rosenbaum & Rubin, 1983) have emerged as one popular and effective tool for causal inference in non-experimental studies, as they can help ensure that groups being compared are similar with respect to a…

Childhood Secondhand Smoke Exposure and ADHD-Attributable Costs to the Health and Education System

ERIC Educational Resources Information Center

Max, Wendy; Sung, Hai-Yen; Shi, Yanling

2014-01-01

Background: Children exposed to secondhand smoke (SHS) have higher rates of behavioral and cognitive effects, including attention deficit hyperactivity disorder (ADHD), but the costs to the health care and education systems have not been estimated. We estimate these costs for school-aged children aged 5-15. Methods: The relative risk (RR) of ADHD…

Sampling design by the core-food approach for the Taiwan total diet study on veterinary drugs.

PubMed

Chen, Chien-Chih; Tsai, Ching-Lun; Chang, Chia-Chin; Ni, Shih-Pei; Chen, Yi-Tzu; Chiang, Chow-Feng

2017-06-01

The core-food (CF) approach, first adopted in the United States in the 1980s, has been widely used by many countries to assess the exposure to dietary hazards at a population level. However, the reliability of exposure estimates (C × CR) depends critically on sampling methods designed for the detected chemical concentrations (C) of each CF to match with the corresponding consumption rate (CR) estimated from the surveyed intake data. In order to reduce the uncertainty of food matching, this study presents a sampling design scheme, namely the subsample method, for the 2016 Taiwan total diet study (TDS) on veterinary drugs. We first combined the four sets of national dietary recall data that covered the entire age strata (1-65+ years), and aggregated them into 307 CFs by their similarity in nutritional values, manufacturing and cooking methods. The 40 CFs pertinent to veterinary drug residues were selected for this study, and 16 subsamples for each CF were designed by weighing their quantities in CR, product brands, manufacturing, processing and cooking methods. The calculated food matching rates of each CF from this study were 84.3-97.3%, which were higher than those obtained from many previous studies using the representative food (RF) method (53.1-57.8%). The subsample method not only considers the variety of food processing and cooking methods, but also it provides better food matching and reduces the uncertainty of exposure assessment.

Development of quantitative exposure data for a pooled exposure-response analysis of 10 silica cohorts.

PubMed

Mannetje, Andrea 't; Steenland, Kyle; Checkoway, Harvey; Koskela, Riitta-Sisko; Koponen, Matti; Attfield, Michael; Chen, Jingqiong; Hnizdo, Eva; DeKlerk, Nicholas; Dosemeci, Mustafa

2002-08-01

Comprehensive quantitative silica exposure estimates over time, measured in the same units across a number of cohorts, would make possible a pooled exposure-response analysis for lung cancer. Such an analysis would help clarify the continuing controversy regarding whether silica causes lung cancer. Existing quantitative exposure data for 10 silica-exposed cohorts were retrieved from the original investigators. Occupation- and time-specific exposure estimates were either adopted/adapted or developed for each cohort, and converted to milligram per cubic meter (mg/m(3)) respirable crystalline silica. Quantitative exposure assignments were typically based on a large number (thousands) of raw measurements, or otherwise consisted of exposure estimates by experts (for two cohorts). Median exposure level of the cohorts ranged between 0.04 and 0.59 mg/m(3) respirable crystalline silica. Exposure estimates were partially validated via their successful prediction of silicosis in these cohorts. Existing data were successfully adopted or modified to create comparable quantitative exposure estimates over time for 10 silica-exposed cohorts, permitting a pooled exposure-response analysis. The difficulties encountered in deriving common exposure estimates across cohorts are discussed. Copyright 2002 Wiley-Liss, Inc.

Estimating Inorganic Arsenic Exposure from U.S. Rice and Total Water Intakes

PubMed Central

Mantha, Madhavi; Yeary, Edward; Trent, John; Creed, Patricia A.; Kubachka, Kevin; Hanley, Traci; Shockey, Nohora; Heitkemper, Douglas; Caruso, Joseph; Xue, Jianping; Rice, Glenn; Wymer, Larry

2017-01-01

Background: Among nonoccupationally exposed U.S. residents, drinking water and diet are considered primary exposure pathways for inorganic arsenic (iAs). In drinking water, iAs is the primary form of arsenic (As), while dietary As speciation techniques are used to differentiate iAs from less toxic arsenicals in food matrices. Objectives: Our goal was to estimate the distribution of iAs exposure rates from drinking water intakes and rice consumption in the U.S. population and ethnic- and age-based subpopulations. Methods: The distribution of iAs in drinking water was estimated by population, weighting the iAs concentrations for each drinking water utility in the Second Six-Year Review data set. To estimate the distribution of iAs concentrations in rice ingested by U.S. consumers, 54 grain-specific, production-weighted composites of rice obtained from U.S. mills were extracted and speciated using both a quantitative dilute nitric acid extraction and speciation (DNAS) and an in vitro gastrointestinal assay to provide an upper bound and bioaccessible estimates, respectively. Daily drinking water intake and rice consumption rate distributions were developed using data from the What We Eat in America (WWEIA) study. Results: Using these data sets, the Stochastic Human Exposure and Dose Simulation (SHEDS) model estimated mean iAs exposures from drinking water and rice were 4.2μg/day and 1.4μg/day, respectively, for the entire U.S. population. The Tribal, Asian, and Pacific population exhibited the highest mean daily exposure of iAs from cooked rice (2.8μg/day); the mean exposure rate for children between ages 1 and 2 years in this population is 0.104μg/kg body weight (BW)/day. Conclusions: An average consumer drinking 1.5 L of water daily that contains between 2 and 3 ng iAs/mL is exposed to approximately the same amount of iAs as a mean Tribal, Asian, and Pacific consumer is exposed to from rice. https://doi.org/10.1289/EHP418 PMID:28572075

A CRITICAL ASSESSMENT OF BIODOSIMETRY METHODS FOR LARGE-SCALE INCIDENTS

PubMed Central

Swartz, Harold M.; Flood, Ann Barry; Gougelet, Robert M.; Rea, Michael E.; Nicolalde, Roberto J.; Williams, Benjamin B.

2014-01-01

Recognition is growing regarding the possibility that terrorism or large-scale accidents could result in potential radiation exposure of hundreds of thousands of people and that the present guidelines for evaluation after such an event are seriously deficient. Therefore, there is a great and urgent need for after-the-fact biodosimetric methods to estimate radiation dose. To accomplish this goal, the dose estimates must be at the individual level, timely, accurate, and plausibly obtained in large-scale disasters. This paper evaluates current biodosimetry methods, focusing on their strengths and weaknesses in estimating human radiation exposure in large-scale disasters at three stages. First, the authors evaluate biodosimetry’s ability to determine which individuals did not receive a significant exposure so they can be removed from the acute response system. Second, biodosimetry’s capacity to classify those initially assessed as needing further evaluation into treatment-level categories is assessed. Third, we review biodosimetry’s ability to guide treatment, both short- and long-term, is reviewed. The authors compare biodosimetric methods that are based on physical vs. biological parameters and evaluate the features of current dosimeters (capacity, speed and ease of getting information, and accuracy) to determine which are most useful in meeting patients’ needs at each of the different stages. Results indicate that the biodosimetry methods differ in their applicability to the three different stages, and that combining physical and biological techniques may sometimes be most effective. In conclusion, biodosimetry techniques have different properties, and knowledge of their properties for meeting the different needs for different stages will result in their most effective use in a nuclear disaster mass-casualty event. PMID:20065671

The Dynamic Photometric Stereo Method Using a Multi-Tap CMOS Image Sensor.

PubMed

Yoda, Takuya; Nagahara, Hajime; Taniguchi, Rin-Ichiro; Kagawa, Keiichiro; Yasutomi, Keita; Kawahito, Shoji

2018-03-05

The photometric stereo method enables estimation of surface normals from images that have been captured using different but known lighting directions. The classical photometric stereo method requires at least three images to determine the normals in a given scene. However, this method cannot be applied to dynamic scenes because it is assumed that the scene remains static while the required images are captured. In this work, we present a dynamic photometric stereo method for estimation of the surface normals in a dynamic scene. We use a multi-tap complementary metal-oxide-semiconductor (CMOS) image sensor to capture the input images required for the proposed photometric stereo method. This image sensor can divide the electrons from the photodiode from a single pixel into the different taps of the exposures and can thus capture multiple images under different lighting conditions with almost identical timing. We implemented a camera lighting system and created a software application to enable estimation of the normal map in real time. We also evaluated the accuracy of the estimated surface normals and demonstrated that our proposed method can estimate the surface normals of dynamic scenes.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring

PubMed Central

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D.; Larson, Timothy V.; Keller, Joshua P.; Kaufman, Joel D.

2016-01-01

Introduction: Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. Objectives: We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. Methods: We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children’s Health Study (CHS), and the Inhalable Particulate Network (IPN). Results: In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84–0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00–0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Conclusions: Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38–46; http://dx.doi.org/10.1289/EHP131 PMID:27340825

Is Mommy Talking to Daddy or to Me? Exploring Parental Estimates of Child Language Exposure Using the Multilingual Infant Language Questionnaire

ERIC Educational Resources Information Center

Liu, Liquan; Kager, René

2017-01-01

Language input is a key factor in bi-/multilingual research. It roots in the definition of bi-/multilingualism and influences infant cognitive development since and even before birth. The methods used to assess language exposure among bi-/multilingual infants vary across studies. This paper discusses the parental report patterns of the…

Effects of Mass Media Campaign Exposure Intensity and Durability on Quit Attempts in a Population-Based Cohort Study

ERIC Educational Resources Information Center

Wakefield, M. A.; Spittal, M. J.; Yong, H-H.; Durkin, S. J.; Borland, R.

2011-01-01

Objective: To assess the extent to which intensity and timing of televised anti-smoking advertising emphasizing the serious harms of smoking influences quit attempts. Methods: Using advertising gross rating points (GRPs), we estimated exposure to tobacco control and nicotine replacement therapy (NRT) advertising in the 3, 4-6, 7-9 and 10-12 months…

[Nanomaterials--proposals of occupational exposure limits in the world and hygiene standards in Poland].

PubMed

Swidwińska-Gajewska, Anna Maria; Czerczak, Sławomir

2013-01-01

Currently, there are no legally binding workplace exposure limits for substances in the form of nanoobjects. There are different ap proaches to risk assessment and determination of occupational exposure limits. The purpose of this article is to compare exposure levels in the work environment proposed by international organizations and world experts, as well as the assumptions and methods used for their estimation. This paper presents the proposals of the National Institute for Public Health and the Environment in the Netherlands (RIVM), the New Energy and Industrial Technology Development Organization in Japan (NEDO) and the National Institute for Occupational Safety and Health in the USA (NIOSH). The authors also discuss the reports on the levels for carbon nanotubes (Baytubes and Nanocyl) proposed by Pauluhn and Luizi, the derived no-effect levels (DNEL) complying with the REACH Regulation, proposed by experts under the 7th Framework Programme of the European Commission, coordinated by Professor Vicki Stone (ENRHES), and alternative estimation levels for poorly soluble particles by Pauluhn. The issue was also raised whether the method of determining maximum admissible concentrations in the work environment, currently used in Poland, is adequate for nanoobjects. Moreover, the introduction of nanoreference values, as proposed by RIVM, the definition of a new fraction for particles of 1-100 nm, taking into account the surface area and activity of the particles, and an adequate estimation of uncertainty factors seem to be worth considering. Other important, if not key issues are the appropriate measurement (numerical concentration, surface concentration, particle size distribution), as well as the methodology and equipment accessibility to all employers responsible for a reliable risk assessment of exposure to nanoparticles in the work environment.

Assessing risks and preventing disease from environmental chemicals.

PubMed

Dunnette, D A

1989-01-01

In the last 25 years there has been considerable concern expressed about the extent to which chemical agents in the ambient and work environments are contributing to the causation of disease. This concern is a logical extension of our increased knowledge of the real and potential effects of environmental chemicals and the methodological difficulties in applying new knowledge that could help prevent environmentally induced disease. Chemical risk assessment offers an approach to estimating risks and involves consideration of relevant information including identification of chemical hazards, evaluation of the dose-response relationship, estimation of exposure and finally, risk characterization. Particularly significant uncertainties which are inherent in use of this and other risk models include animal-human and low dose-high dose extrapolation and estimation of exposure. Community public health risks from exposure to environmental chemicals appear to be small relative to other public health risks based on information related to cancer trends, dietary intake of synthetic chemicals, assessment data on substances such as DDT and "dioxin," public health effects of hazardous waste sites and contextual considerations. Because of inherent uncertainty in the chemical risk assessment process, however, we need to apply what methods are available in our efforts to prevent disease induced by environmental chemicals. There are a number of societal strategies which can contribute to overall reduction of risk from environmental chemicals. These include acquisition of information on environmental risk including toxicity, intensity and extensity of exposure, biological monitoring, disease surveillance, improvement in epidemiological methods, control of environmental chemical exposures, and dissemination of hazardous chemical information. Responsible environmental risk communication and information transfer appear to be among the most important of the available strategies for preventing disease induced by chemicals in the environment.

Early efforts in modeling the incubation period of infectious diseases with an acute course of illness.

PubMed

Nishiura, Hiroshi

2007-05-11

The incubation period of infectious diseases, the time from infection with a microorganism to onset of disease, is directly relevant to prevention and control. Since explicit models of the incubation period enhance our understanding of the spread of disease, previous classic studies were revisited, focusing on the modeling methods employed and paying particular attention to relatively unknown historical efforts. The earliest study on the incubation period of pandemic influenza was published in 1919, providing estimates of the incubation period of Spanish flu using the daily incidence on ships departing from several ports in Australia. Although the study explicitly dealt with an unknown time of exposure, the assumed periods of exposure, which had an equal probability of infection, were too long, and thus, likely resulted in slight underestimates of the incubation period. After the suggestion that the incubation period follows lognormal distribution, Japanese epidemiologists extended this assumption to estimates of the time of exposure during a point source outbreak. Although the reason why the incubation period of acute infectious diseases tends to reveal a right-skewed distribution has been explored several times, the validity of the lognormal assumption is yet to be fully clarified. At present, various different distributions are assumed, and the lack of validity in assuming lognormal distribution is particularly apparent in the case of slowly progressing diseases. The present paper indicates that (1) analysis using well-defined short periods of exposure with appropriate statistical methods is critical when the exact time of exposure is unknown, and (2) when assuming a specific distribution for the incubation period, comparisons using different distributions are needed in addition to estimations using different datasets, analyses of the determinants of incubation period, and an understanding of the underlying disease mechanisms.

Evaluation of polyurethane foam passive air sampler (PUF) as a tool for occupational PAH measurements.

PubMed

Strandberg, Bo; Julander, Anneli; Sjöström, Mattias; Lewné, Marie; Koca Akdeva, Hatice; Bigert, Carolina

2018-01-01

Routine monitoring of workplace exposure to polycyclic aromatic hydrocarbons (PAHs) is performed mainly via active sampling. However, active samplers have several drawbacks and, in some cases, may even be unusable. Polyurethane foam (PUF) as personal passive air samplers constitute good alternatives for PAH monitoring in occupational air (8 h). However, PUFs must be further tested to reliably yield detectable levels of PAHs in short exposure times (1-3 h) and under extreme occupational conditions. Therefore, we compared the personal exposure monitoring performance of a passive PUF sampler with that of an active air sampler and determined the corresponding uptake rates (Rs). These rates were then used to estimate the occupational exposure of firefighters and police forensic specialists to 32 PAHs. The work environments studied were heavily contaminated by PAHs with (for example) benzo(a)pyrene ranging from 0.2 to 56 ng m -3 , as measured via active sampling. We show that, even after short exposure times, PUF can reliably accumulate both gaseous and particle-bound PAHs. The Rs-values are almost independent of variables such as the concentration and the wind speed. Therefore, by using the Rs-values (2.0-20 m 3 day -1 ), the air concentrations can be estimated within a factor of two for gaseous PAHs and a factor of 10 for particulate PAHs. With very short sampling times (1 h), our method can serve as a (i) simple and user-friendly semi-quantitative screening tool for estimating and tracking point sources of PAH in micro-environments and (ii) complement to the traditional active pumping methods. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Dupuytren's contracture and occupational exposure to hand-transmitted vibration

PubMed Central

Palmer, Keith T; D'Angelo, Stefania; Syddall, Holly; Griffin, Michael J; Cooper, Cyrus; Coggon, David

2014-01-01

Aims The relation between Dupuytren's contracture and occupational exposure to hand-transmitted vibration (HTV) has frequently been debated. We explored associations in a representative national sample of workers with well-characterised exposure to HTV. Methods We mailed a questionnaire to 21 201 subjects aged 16–64 years, selected at random from the age-sex registers of 34 general practices in Great Britain and to 993 subjects chosen randomly from military pay records, asking about occupational exposure to 39 sources of HTV and about fixed flexion contracture of the little or ring finger. Analysis was restricted to men at work in the previous week. Estimates were made of average daily vibration dose (A(8) root mean squared velocity (rms)) over that week. Associations with Dupuytren's contracture were estimated by Poisson regression, for lifetime exposure to HTV and for exposures in the past week >A(8) of 2.8 ms−2 rms. Estimates of relative risk (prevalence ratio (PR)) were adjusted for age, smoking status, social class and certain manual activities at work. Results In all 4969 eligible male respondents supplied full information on the study variables. These included 72 men with Dupuytren's contracture, 2287 with occupational exposure to HTV and 409 with A(8)>2.8 ms−2 in the past week. PRs for occupational exposure to HTV were elevated 1.5-fold. For men with an A(8)>2.8 ms−2 in the past week, the adjusted PR was 2.85 (95% CI 1.37 to 5.97). Conclusions Our findings suggest that risk of Dupuytren's contracture is more than doubled in men with high levels of weekly exposure to HTV. PMID:24449599

Modeling of occupational exposure to accidentally released manufactured nanomaterials in a production facility and calculation of internal doses by inhalation

PubMed Central

Vaquero-Moralejo, Celina; Jaén, María; Lopez De Ipiña Peña, Jesús; Neofytou, Panagiotis

2016-01-01

Background Occupational exposure to manufactured nanomaterials (MNMs) and its potential health impacts are of scientific and practical interest, as previous epidemiological studies associate exposure to nanoparticles with health effects, including increased morbidity of the respiratory and the circulatory system. Objectives To estimate the occupational exposure and effective internal doses in a real production facility of TiO2 MNMs during hypothetical scenarios of accidental release. Methods Commercial software for geometry and mesh generation, as well as fluid flow and particle dispersion calculation, were used to estimate occupational exposure to MNMs. The results were introduced to in-house software to calculate internal doses in the human respiratory tract by inhalation. Results Depending on the accidental scenario, different areas of the production facility were affected by the released MNMs, with a higher dose exposure among individuals closer to the particles source. Conclusions Granted that the study of the accidental release of particles can only be performed by chance, this numerical approach provides valuable information regarding occupational exposure and contributes to better protection of personnel. The methodology can be used to identify occupational settings where the exposure to MNMs would be high during accidents, providing insight to health and safety officials. PMID:27670588

Considerations for estimating microbial environmental data concentrations collected from a field setting

PubMed Central

Silvestri, Erin E; Yund, Cynthia; Taft, Sarah; Bowling, Charlena Yoder; Chappie, Daniel; Garrahan, Kevin; Brady-Roberts, Eletha; Stone, Harry; Nichols, Tonya L

2017-01-01

In the event of an indoor release of an environmentally persistent microbial pathogen such as Bacillus anthracis, the potential for human exposure will be considered when remedial decisions are made. Microbial site characterization and clearance sampling data collected in the field might be used to estimate exposure. However, there are many challenges associated with estimating environmental concentrations of B. anthracis or other spore-forming organisms after such an event before being able to estimate exposure. These challenges include: (1) collecting environmental field samples that are adequate for the intended purpose, (2) conducting laboratory analyses and selecting the reporting format needed for the laboratory data, and (3) analyzing and interpreting the data using appropriate statistical techniques. This paper summarizes some key challenges faced in collecting, analyzing, and interpreting microbial field data from a contaminated site. Although the paper was written with considerations for B. anthracis contamination, it may also be applicable to other bacterial agents. It explores the implications and limitations of using field data for determining environmental concentrations both before and after decontamination. Several findings were of interest. First, to date, the only validated surface/sampling device combinations are swabs and sponge-sticks on stainless steel surfaces, thus limiting availability of quantitative analytical results which could be used for statistical analysis. Second, agreement needs to be reached with the analytical laboratory on the definition of the countable range and on reporting of data below the limit of quantitation. Finally, the distribution of the microbial field data and statistical methods needed for a particular data set could vary depending on these data that were collected, and guidance is needed on appropriate statistical software for handling microbial data. Further, research is needed to develop better methods to estimate human exposure from pathogens using environmental data collected from a field setting. PMID:26883476

Environment, cancer and inequalities-The urgent need for prevention.

PubMed

Vineis, Paolo; Fecht, Daniela

2018-06-11

The proportion of total deaths attributable to environmental factors is estimated to be 23% of global deaths and 22% of global disability-adjusted life years (DALYs) according to one review. These estimates encompass all environmental agents including infectious agents but excluding behavioural factors. The authors of the review also estimated that 16% (95% CI: 7-41%) of cancer deaths are attributable to environmental risk factors (and 36% [95% CI: 17-52%] for lung cancer). In this article, we focus on the reasons why epidemiology is often unable to account for the whole burden of environmental carcinogens. The experience of air pollution is particularly instructive. While in the 1970s and early 1980s, air pollution was considered as a relatively marginal exposure in terms of attributable risks, the most recent estimate is that it accounts for 7.6% of global deaths and 4.2% of global DALYs world-wide (with East and South Asia accounting for 59% of the total). According to a review, ambient fine particulate matter air pollution contributed to 17.1% of ischaemic heart disease, 14.2% of cerebrovascular disease, 16.5% of lung cancer, 24.7% of low respiratory infections, and 27.1% of COPD mortality in 2015. Estimates for cancer as a whole are not available. The change in appreciation of the role of air pollution has been mainly due to the refinement of exposure assessment methods and the new generations of longitudinal studies. Mechanistic evidence via omic technologies is now rapidly increasing, thus lending credibility to previous epidemiological ('black box') associations. Much less is known about other environmental contaminants, some of which are widespread and pervasive, thus suggesting the need for the same rigourous methods as those applied to air pollution. Finally, a crucial issue remains inequality across different population groups, with uneven exposure to hazards and acquired susceptibilities due to multiple concomitant exposures and poorer health status. Copyright © 2018. Published by Elsevier Ltd.

75 FR 42170 - Final Regulatory Guide: Issuance, Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-20

..., techniques that the staff uses in evaluating specific problems or postulated accidents, and data that the... (EDEX) radiation exposures. These methods provide a conservative estimate of the EDEX and may be used to...

Estimating Fallout Building Attributes from Architectural Features and Global Earthquake Model (GEM) Building Descriptions

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

Dillon, Michael B.; Kane, Staci R.

A nuclear explosion has the potential to injure or kill tens to hundreds of thousands (or more) of people through exposure to fallout (external gamma) radiation. Existing buildings can protect their occupants (reducing fallout radiation exposures) by placing material and distance between fallout particles and individuals indoors. Prior efforts have determined an initial set of building attributes suitable to reasonably assess a given building’s protection against fallout radiation. The current work provides methods to determine the quantitative values for these attributes from (a) common architectural features and data and (b) buildings described using the Global Earthquake Model (GEM) taxonomy. Thesemore » methods will be used to improve estimates of fallout protection for operational US Department of Defense (DoD) and US Department of Energy (DOE) consequence assessment models.« less

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

PubMed

Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

2012-07-01

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Occupational exposure to cleaning products and asthma in hospital workers.

PubMed

Dumas, Orianne; Donnay, Carole; Heederik, Dick J J; Héry, Michel; Choudat, Dominique; Kauffmann, Francine; Le Moual, Nicole

2012-12-01

Cleaning products may cause work-related asthma, but information regarding the specific exposures involved is scarce. We aimed to determine the associations between asthma and occupational exposure to cleaning agents in hospital workers. Analyses were conducted in 179 (136 women) hospital workers and a reference population of 545 subjects (18-79 years) from the French case-control and familial Epidemiological study on the Genetics and Environment of Asthma (2003-2007). Exposures to cleaning agents were estimated using three methods: self-report, expert assessment and an asthma-specific job-exposure matrix (JEM). Associations between cleaning products and current asthma were evaluated by logistic regressions, stratified by sex and adjusted for age and smoking status. According to expert assessment, 55% of male and 81% of female hospital workers were exposed to cleaning/disinfecting tasks weekly (p<0.001). No association was observed between cleaning/disinfecting tasks and current asthma in men or in women whatever the assessment method used. In women, exposure to decalcifiers (expert assessment) was associated with current asthma (OR (95% CI):2.38 (1.06 to 5.33)). In hospital workers classified as exposed according to both the expert assessment and the JEM, additional associations were observed for exposure to ammonia (3.05 (1.19 to 7.82)) and to sprays with moderate/high intensity (2.87 (1.02 to 8.11)). Female hospital workers are often exposed to numerous cleaning products, some of which were markedly associated with current asthma. Low numbers prevented a meaningful analysis in men. Objective and more accurate estimates of occupational exposure to cleaning products are needed to better understand the adverse effects of cleaning products.

Fault tree analysis for exposure to refrigerants used for automotive air conditioning in the United States.

PubMed

Jetter, J J; Forte, R; Rubenstein, R

2001-02-01

A fault tree analysis was used to estimate the number of refrigerant exposures of automotive service technicians and vehicle occupants in the United States. Exposures of service technicians can occur when service equipment or automotive air-conditioning systems leak during servicing. The number of refrigerant exposures of service technicians was estimated to be 135,000 per year. Exposures of vehicle occupants can occur when refrigerant enters passenger compartments due to sudden leaks in air-conditioning systems, leaks following servicing, or leaks caused by collisions. The total number of exposures of vehicle occupants was estimated to be 3,600 per year. The largest number of exposures of vehicle occupants was estimated for leaks caused by collisions, and the second largest number of exposures was estimated for leaks following servicing. Estimates used in the fault tree analysis were based on a survey of automotive air-conditioning service shops, the best available data from the literature, and the engineering judgement of the authors and expert reviewers from the Society of Automotive Engineers Interior Climate Control Standards Committee. Exposure concentrations and durations were estimated and compared with toxicity data for refrigerants currently used in automotive air conditioners. Uncertainty was high for the estimated numbers of exposures, exposure concentrations, and exposure durations. Uncertainty could be reduced in the future by conducting more extensive surveys, measurements of refrigerant concentrations, and exposure monitoring. Nevertheless, the analysis indicated that the risk of exposure of service technicians and vehicle occupants is significant, and it is recommended that no refrigerant that is substantially more toxic than currently available substitutes be accepted for use in vehicle air-conditioning systems, absent a means of mitigating exposure.

Radiation dose estimation for marine mussels following exposure to tritium: Best practice for use of the ERICA tool in ecotoxicological studies.

PubMed

Dallas, Lorna J; Devos, Alexandre; Fievet, Bruno; Turner, Andrew; Lyons, Brett P; Jha, Awadhesh N

2016-05-01

Accurate dosimetry is critically important for ecotoxicological and radioecological studies on the potential effects of environmentally relevant radionuclides, such as tritium ((3)H). Previous studies have used basic dosimetric equations to estimate dose from (3)H exposure in ecologically important organisms, such as marine mussels. This study compares four different methods of estimating dose to adult mussels exposed to 1 or 15 MBq L(-1) tritiated water (HTO) under laboratory conditions. These methods were (1) an equation converting seawater activity concentrations to dose rate with fixed parameters; (2) input into the ERICA tool of seawater activity concentrations only; (3) input into the ERICA tool of estimated whole organism concentrations (woTACs), comprising dry activity plus estimated tissue free water tritium (TFWT) activity (TFWT volume × seawater activity concentration); and (4) input into the ERICA tool of measured whole organism activity concentrations, comprising dry activity plus measured TFWT activity (TFWT volume × TFWT activity concentration). Methods 3 and 4 are recommended for future ecotoxicological experiments as they produce values for individual animals and are not reliant on transfer predictions (estimation of concentration ratio). Method 1 may be suitable if measured whole organism concentrations are not available, as it produced results between 3 and 4. As there are technical complications to accurately measuring TFWT, we recommend that future radiotoxicological studies on mussels or other aquatic invertebrates measure whole organism activity in non-dried tissues (i.e. incorporating TFWT and dry activity as one, rather than as separate fractions) and input this data into the ERICA tool. Copyright © 2016 Elsevier Ltd. All rights reserved.

Preliminary Upper Estimate of Peak Currents in Transcranial Magnetic Stimulation at Distant Locations from a TMS Coil

PubMed Central

Makarov, Sergey N.; Yanamadala, Janakinadh; Piazza, Matthew W.; Helderman, Alex M.; Thang, Niang S.; Burnham, Edward H.; Pascual-Leone, Alvaro

2016-01-01

Goals Transcranial magnetic stimulation (TMS) is increasingly used as a diagnostic and therapeutic tool for numerous neuropsychiatric disorders. The use of TMS might cause whole-body exposure to undesired induced currents in patients and TMS operators. The aim of the present study is to test and justify a simple analytical model known previously, which may be helpful as an upper estimate of eddy current density at a particular distant observation point for any body composition and any coil setup. Methods We compare the analytical solution with comprehensive adaptive mesh refinement-based FEM simulations of a detailed full-body human model, two coil types, five coil positions, about 100,000 observation points, and two distinct pulse rise times, thus providing a representative number of different data sets for comparison, while also using other numerical data. Results Our simulations reveal that, after a certain modification, the analytical model provides an upper estimate for the eddy current density at any location within the body. In particular, it overestimates the peak eddy currents at distant locations from a TMS coil by a factor of 10 on average. Conclusion The simple analytical model tested in the present study may be valuable as a rapid method to safely estimate levels of TMS currents at different locations within a human body. Significance At present, safe limits of general exposure to TMS electric and magnetic fields are an open subject, including fetal exposure for pregnant women. PMID:26685221

Cancer and non-cancer health effects from food contaminant exposures for children and adults in California: a risk assessment

PubMed Central

2012-01-01

Background In the absence of current cumulative dietary exposure assessments, this analysis was conducted to estimate exposure to multiple dietary contaminants for children, who are more vulnerable to toxic exposure than adults. Methods We estimated exposure to multiple food contaminants based on dietary data from preschool-age children (2–4 years, n=207), school-age children (5–7 years, n=157), parents of young children (n=446), and older adults (n=149). We compared exposure estimates for eleven toxic compounds (acrylamide, arsenic, lead, mercury, chlorpyrifos, permethrin, endosulfan, dieldrin, chlordane, DDE, and dioxin) based on self-reported food frequency data by age group. To determine if cancer and non-cancer benchmark levels were exceeded, chemical levels in food were derived from publicly available databases including the Total Diet Study. Results Cancer benchmark levels were exceeded by all children (100%) for arsenic, dieldrin, DDE, and dioxins. Non-cancer benchmarks were exceeded by >95% of preschool-age children for acrylamide and by 10% of preschool-age children for mercury. Preschool-age children had significantly higher estimated intakes of 6 of 11 compounds compared to school-age children (p<0.0001 to p=0.02). Based on self-reported dietary data, the greatest exposure to pesticides from foods included in this analysis were tomatoes, peaches, apples, peppers, grapes, lettuce, broccoli, strawberries, spinach, dairy, pears, green beans, and celery. Conclusions Dietary strategies to reduce exposure to toxic compounds for which cancer and non-cancer benchmarks are exceeded by children vary by compound. These strategies include consuming organically produced dairy and selected fruits and vegetables to reduce pesticide intake, consuming less animal foods (meat, dairy, and fish) to reduce intake of persistent organic pollutants and metals, and consuming lower quantities of chips, cereal, crackers, and other processed carbohydrate foods to reduce acrylamide intake. PMID:23140444

Evaluation of the Webler-Brown model for estimating tetrachloroethylene exposure from vinyl-lined asbestos-cement pipes

PubMed Central

Spence, Lisa A; Aschengrau, Ann; Gallagher, Lisa E; Webster, Thomas F; Heeren, Timothy C; Ozonoff, David M

2008-01-01

Background From May 1968 through March 1980, vinyl-lined asbestos-cement (VL/AC) water distribution pipes were installed in New England to avoid taste and odor problems associated with asbestos-cement pipes. The vinyl resin was applied to the inner pipe surface in a solution of tetrachloroethylene (perchloroethylene, PCE). Substantial amounts of PCE remained in the liner and subsequently leached into public drinking water supplies. Methods Once aware of the leaching problem and prior to remediation (April-November 1980), Massachusetts regulators collected drinking water samples from VL/AC pipes to determine the extent and severity of the PCE contamination. This study compares newly obtained historical records of PCE concentrations in water samples (n = 88) with concentrations estimated using an exposure model employed in epidemiologic studies on the cancer risk associated with PCE-contaminated drinking water. The exposure model was developed by Webler and Brown to estimate the mass of PCE delivered to subjects' residences. Results The mean and median measured PCE concentrations in the water samples were 66 and 0.5 μg/L, respectively, and the range extended from non-detectable to 2432 μg/L. The model-generated concentration estimates and water sample concentrations were moderately correlated (Spearman rank correlation coefficient = 0.48, p < 0.0001). Correlations were higher in samples taken at taps and spigots vs. hydrants (ρ = 0.84 vs. 0.34), in areas with simple vs. complex geometry (ρ = 0.51 vs. 0.38), and near pipes installed in 1973–1976 vs. other years (ρ = 0.56 vs. 0.42 for 1968–1972 and 0.37 for 1977–1980). Overall, 24% of the variance in measured PCE concentrations was explained by the model-generated concentration estimates (p < 0.0001). Almost half of the water samples had undetectable concentrations of PCE. Undetectable levels were more common in areas with the earliest installed VL/AC pipes, at the beginning and middle of VL/AC pipes, at hydrants, and in complex pipe configurations. Conclusion PCE concentration estimates generated using the Webler-Brown model were moderately correlated with measured water concentrations. The present analysis suggests that the exposure assessment process used in prior epidemiological studies could be improved with more accurate characterization of water flow. This study illustrates one method of validating an exposure model in an epidemiological study when historical measurements are not available. PMID:18518975

Migration protocol to estimate metal exposure from mouthing copper and tin alloy objects

PubMed Central

2014-01-01

Background Low blood lead levels previously thought to pose no health risks may have an adverse impact on the cognitive development of children. This concern has given rise to new regulatory restrictions upon lead metal containing products intended for child use. However few reliable experimental testing methods to estimate exposure levels from these materials are available. Methods The present work describes a migration test using a mimetic saliva fluid to estimate the chronic exposure of children to metals such as lead while mouthing metallic objects. The surrogate saliva medium was composed of: 150 mM NaCl, 0.16% porcine Mucin and 5 mM buffer MOPS, adjusted to pH 7.2. Alloys samples, in the form of polished metallic disc of known surface area, were subjected to an eight hours test. Results Two whitemetal alloys Sn/Pb/Sb/Cu and three brass alloys Cu/Zn/Pb were tested using the saliva migration protocol. In the case of the whitemetal alloys, first order release kinetics resulting in the release of 0.03 and 0.51 μg lead/cm2 after 8 hours of tests were observed, for lead contents of 0.05-0.07% and 5.5%, respectively. Brasses exhibited linear incremental release rates of 0.043, 0.175 and 0.243 μg lead/cm2h for lead contents of 0.1-0.2%, 1.7-2.2% and 3.1-3.5%, respectively. The linear regression analysis of lead release rates relative to Pb content in brasses yielded a slope of 0.08 μg lead/cm2h%Pb (r2 = 0.92). Lead release rates were used to estimate the mean daily mouthing exposure of a child to lead, according to age-specific estimates of mouthing time behavior. Calculated daily intakes were used as oral inputs for the IEUBK toxicokinetic model, predicting only marginal changes in blood lead levels (0.2 μg lead/dL or less) for children aged 0.5 to 1 years old exposed to either class of alloy. Conclusions The results of this study as a whole support the use of migration data of metal ions, rather than total metal content, to estimate health risk from exposure to metals and metal alloys substances in children. PMID:25113236

Using cell phone location to assess misclassification errors in air pollution exposure estimation.

PubMed

Yu, Haofei; Russell, Armistead; Mulholland, James; Huang, Zhijiong

2018-02-01

Air pollution epidemiologic and health impact studies often rely on home addresses to estimate individual subject's pollution exposure. In this study, we used detailed cell phone location data, the call detail record (CDR), to account for the impact of spatiotemporal subject mobility on estimates of ambient air pollutant exposure. This approach was applied on a sample with 9886 unique simcard IDs in Shenzhen, China, on one mid-week day in October 2013. Hourly ambient concentrations of six chosen pollutants were simulated by the Community Multi-scale Air Quality model fused with observational data, and matched with detailed location data for these IDs. The results were compared with exposure estimates using home addresses to assess potential exposure misclassification errors. We found the misclassifications errors are likely to be substantial when home location alone is applied. The CDR based approach indicates that the home based approach tends to over-estimate exposures for subjects with higher exposure levels and under-estimate exposures for those with lower exposure levels. Our results show that the cell phone location based approach can be used to assess exposure misclassification error and has the potential for improving exposure estimates in air pollution epidemiology studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Occupational health surveillance: a means to identify work-related risks.

PubMed

Froines, J R; Dellenbaugh, C A; Wegman, D H

1986-09-01

The lack of successful disease surveillance methods has resulted in few reliable estimates of workplace-related disease. Hazard surveillance--the ongoing assessment of chemical use and worker exposure to the chemicals--is presented as a way to supplement occupational disease surveillance. Existing OSHA (Occupational Safety and Health Administration) and NIOSH (National Institute for Occupational Health) data systems are adapted to this function to characterize the distribution and type of hazardous industry in Los Angeles County. A new method is developed for ranking potentially hazardous industries in the county using actual exposure measurements from federal OSHA compliance inspections. The strengths of the different systems are presented along with considerations of industrial employment and types of specific chemical exposures. Applications for information from hazard surveillance are discussed in terms of intervention, monitoring exposure control, planning, research, and as a complement to disease surveillance.

Adult and adolescent exposure to tobacco and alcohol content in contemporary YouTube music videos in Great Britain: a population estimate

PubMed Central

Cranwell, Jo; Opazo-Breton, Magdalena; Britton, John

2016-01-01

Background We estimate exposure of British adults and adolescents to tobacco and alcohol content from a sample of popular YouTube music videos. Methods British viewing figures were generated from 2 representative online national surveys of adult and adolescent viewing of the 32 most popular videos containing content. 2068 adolescents aged 11–18 years (1010 boys, 1058 girls), and 2232 adults aged 19+years (1052 male, 1180 female) completed the surveys. We used the number of 10 s intervals in the 32 most popular videos containing content to estimate the number of impressions. We extrapolated gross and per capita impressions for the British population from census data and estimated numbers of adults and adolescents who had ever watched the sampled videos. Results From video release to the point of survey, the videos delivered an estimated 1006 million gross impressions of alcohol (95% CI 748 to 1264 million), and 203 million of tobacco (95% CI 151 to 255 million), to the British population. Per capita exposure was around 5 times higher for alcohol than for tobacco, and nearly 4 times higher in adolescents, who were exposed to an average of 52.1 (95% CI 43.4 to 60.9) and 10.5 (95% CI 8.8 to 12.3) alcohol and tobacco impressions, respectively, than in adults (14.1 (95% CI 10.2 to 18.1) and 2.9 (95% CI 2.1 to 3.6)). Exposure rates were higher in girls than in boys. Conclusions YouTube music videos deliver millions of gross impressions of alcohol and tobacco content. Adolescents are exposed much more than adults. Music videos are a major global medium of exposure to such content. PMID:26767404

Estimated dose rates to members of the public from external exposure to patients with {sup 131}I thyroid treatment

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

Dewji, S., E-mail: dewjisa@ornl.gov; Bellamy, M.; Leggett, R.

Purpose: Estimated dose rates that may result from exposure to patients who had been administered iodine-131 ({sup 131}I) as part of medical therapy were calculated. These effective dose rate estimates were compared with simplified assumptions under United States Nuclear Regulatory Commission Regulatory Guide 8.39, which does not consider body tissue attenuation nor time-dependent redistribution and excretion of the administered {sup 131}I. Methods: Dose rates were estimated for members of the public potentially exposed to external irradiation from patients recently treated with {sup 131}I. Tissue attenuation and iodine biokinetics were considered in the patient in a larger comprehensive effort to improvemore » external dose rate estimates. The external dose rate estimates are based on Monte Carlo simulations using the Phantom with Movable Arms and Legs (PIMAL), previously developed by Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission. PIMAL was employed to model the relative positions of the {sup 131}I patient and members of the public in three exposure scenarios: (1) traveling on a bus in a total of six seated or standing permutations, (2) two nursing home cases where a caregiver is seated at 30 cm from the patient’s bedside and a nursing home resident seated 250 cm away from the patient in an adjacent bed, and (3) two hotel cases where the patient and a guest are in adjacent rooms with beds on opposite sides of the common wall, with the patient and guest both in bed and either seated back-to-back or lying head to head. The biokinetic model predictions of the retention and distribution of {sup 131}I in the patient assumed a single voiding of urinary bladder contents that occurred during the trip at 2, 4, or 8 h after {sup 131}I administration for the public transportation cases, continuous first-order voiding for the nursing home cases, and regular periodic voiding at 4, 8, or 12 h after administration for the hotel room cases. Organ specific activities of {sup 131}I in the thyroid, bladder, and combined remaining tissues were calculated as a function of time after administration. Exposures to members of the public were considered for {sup 131}I patients with normal thyroid uptake (peak thyroid uptake of ∼27% of administered {sup 131}I), differentiated thyroid cancer (DTC, 5% uptake), and hyperthyroidism (80% uptake). Results: The scenario with the patient seated behind the member of the public yielded the highest dose rate estimate of seated public transportation exposure cases. The dose rate to the adjacent room guest was highest for the exposure scenario in which the hotel guest and patient are seated by a factor of ∼4 for the normal and differentiated thyroid cancer uptake cases and by a factor of ∼3 for the hyperthyroid case. Conclusions: It was determined that for all modeled cases, the DTC case yielded the lowest external dose rates, whereas the hyperthyroid case yielded the highest dose rates. In estimating external dose to members of the public from patients with {sup 131}I therapy, consideration must be given to (patient- and case-specific) administered {sup 131}I activities and duration of exposure for a more complete estimate. The method implemented here included a detailed calculation model, which provides a means to determine dose rate estimates for a range of scenarios. The method was demonstrated for variations of three scenarios, showing how dose rates are expected to vary with uptake, voiding pattern, and patient location.« less

Diagnostics for Confounding of Time-varying and Other Joint Exposures.

PubMed

Jackson, John W

2016-11-01

The effects of joint exposures (or exposure regimes) include those of adhering to assigned treatment versus placebo in a randomized controlled trial, duration of exposure in a cohort study, interactions between exposures, and direct effects of exposure, among others. Unlike the setting of a single point exposure (e.g., propensity score matching), there are few tools to describe confounding for joint exposures or how well a method resolves it. Investigators need tools that describe confounding in ways that are conceptually grounded and intuitive for those who read, review, and use applied research to guide policy. We revisit the implications of exchangeability conditions that hold in sequentially randomized trials, and the bias structure that motivates the use of g-methods, such as marginal structural models. From these, we develop covariate balance diagnostics for joint exposures that can (1) describe time-varying confounding, (2) assess whether covariates are predicted by prior exposures given their past, the indication for g-methods, and (3) describe residual confounding after inverse probability weighting. For each diagnostic, we present time-specific metrics that encompass a wide class of joint exposures, including regimes of multivariate time-varying exposures in censored data, with multivariate point exposures as a special case. We outline how to estimate these directly or with regression and how to average them over person-time. Using a simulated example, we show how these metrics can be presented graphically. This conceptually grounded framework can potentially aid the transparent design, analysis, and reporting of studies that examine joint exposures. We provide easy-to-use tools to implement it.

ANALYSIS OF EPR AND FISH STUDIES OF RADIATION DOSES IN PERSONS WHO LIVED IN THE UPPER REACHES OF THE TECHA RIVER

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

Degteva, M. O.; Shagina, N. B.; Shishkina, Elena A.

Waterborne radioactive releases into the Techa River from the Mayak Production Association in Russia during 1949–1956 resulted in significant doses to about 30,000 persons who lived in downstream settlements. The residents were exposed to internal and external radiation. Two methods for reconstruction of the external dose are considered in this paper, electron paramagnetic resonance (EPR) measurements of teeth and fluorescence in situ hybridization (FISH) measurements of chromosome translocations in circulating lymphocytes. The main issue in the application of the EPR and FISH methods for reconstruction of the external dose for the Techa Riverside residents was strontium radioisotopes incorporated in teethmore » and bones that served as a source of confounding local exposures. In order to estimate and subtract doses from incorporated 89,90Sr, the EPR and FISH assays were supported by measurements of 90Sr-body burdens and estimates of 90Sr concentrations in dental tissues by the luminescence method. The resulting dose estimates derived from EPR and FISH measurements for residents of the upper Techa River were found to be consistent: the mean values vary from 510 – 550 mGy for the villages located close to the site of radioactive release to 130 – 160 mGy for the more distant villages. The upper bound of individual estimates for both methods is equal to 2.2 – 2.3 Gy. The EPR- and FISH-based dose estimates were compared with the doses calculated for the donors using the Techa River Dosimetry System (TRDS). The TRDS external dose assessments were based on the data on contamination of the Techa River floodplain, simulation of ai r kerma above the contaminated soil, age-dependent life-styles and individual residence histories. For correct comparison TRDS-based doses were calculated from two sources: external exposure from the contaminated environment and internal exposure from 137Cs incorporated in donors’ soft tissues. The TRDS-based absorbed doses in tooth enamel and muscle were in agreement with with EPR- and FISH-based estimates within uncertainty bounds. Basically, the agreement between the estimates has confirmed the validity of external doses calculated with the Techa River Dosimetry System.« less

Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States

PubMed Central

Morello-Frosch, Rachel; Mennitt, Daniel J.; Fristrup, Kurt; Ogburn, Elizabeth L.; James, Peter

2017-01-01

Background: Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution. Objectives: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation. Methods: We used a geospatial sound model to estimate census block group–level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006–2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. Results: Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3–47.8 dBA] and 42.3 dBA (IQR: 40.4–45.5 dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9 dBA (IQR: 44.7–48.5 dBA) and 44.0 dBA (IQR: 42.2–45.5 dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions. Conclusions: We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United States. https://doi.org/10.1289/EHP898 PMID:28749369

Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

PubMed

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

Incorporation of multiple cloud layers for ultraviolet radiation modeling studies

NASA Technical Reports Server (NTRS)

Charache, Darryl H.; Abreu, Vincent J.; Kuhn, William R.; Skinner, Wilbert R.

1994-01-01

Cloud data sets compiled from surface observations were used to develop an algorithm for incorporating multiple cloud layers into a multiple-scattering radiative transfer model. Aerosol extinction and ozone data sets were also incorporated to estimate the seasonally averaged ultraviolet (UV) flux reaching the surface of the Earth in the Detroit, Michigan, region for the years 1979-1991, corresponding to Total Ozone Mapping Spectrometer (TOMS) version 6 ozone observations. The calculated UV spectrum was convolved with an erythema action spectrum to estimate the effective biological exposure for erythema. Calculations show that decreasing the total column density of ozone by 1% leads to an increase in erythemal exposure by approximately 1.1-1.3%, in good agreement with previous studies. A comparison of the UV radiation budget at the surface between a single cloud layer method and a multiple cloud layer method presented here is discussed, along with limitations of each technique. With improved parameterization of cloud properties, and as knowledge of biological effects of UV exposure increase, inclusion of multiple cloud layers may be important in accurately determining the biologically effective UV budget at the surface of the Earth.

An approach to checking case-crossover analyses based on equivalence with time-series methods.

PubMed

Lu, Yun; Symons, James Morel; Geyh, Alison S; Zeger, Scott L

2008-03-01

The case-crossover design has been increasingly applied to epidemiologic investigations of acute adverse health effects associated with ambient air pollution. The correspondence of the design to that of matched case-control studies makes it inferentially appealing for epidemiologic studies. Case-crossover analyses generally use conditional logistic regression modeling. This technique is equivalent to time-series log-linear regression models when there is a common exposure across individuals, as in air pollution studies. Previous methods for obtaining unbiased estimates for case-crossover analyses have assumed that time-varying risk factors are constant within reference windows. In this paper, we rely on the connection between case-crossover and time-series methods to illustrate model-checking procedures from log-linear model diagnostics for time-stratified case-crossover analyses. Additionally, we compare the relative performance of the time-stratified case-crossover approach to time-series methods under 3 simulated scenarios representing different temporal patterns of daily mortality associated with air pollution in Chicago, Illinois, during 1995 and 1996. Whenever a model-be it time-series or case-crossover-fails to account appropriately for fluctuations in time that confound the exposure, the effect estimate will be biased. It is therefore important to perform model-checking in time-stratified case-crossover analyses rather than assume the estimator is unbiased.

Exposure to benzene in a pooled analysis of petroleum industry case-control studies.

PubMed

Glass, D C; Schnatter, A R; Tang, G; Armstrong, T W; Rushton, L

2017-11-01

Cases of lymphohematopoietic cancer from three petroleum industry cohorts, matched to controls from the respective cohort, were pooled into single study. Average benzene exposure was quantitatively estimated in ppm for each job based on measured data from the relevant country, adjusted for the specific time period, site and job exposure characteristics and the certainty of the exposure estimate scored. The probability of dermal exposure and of peak exposure was also assessed. Before risk was examined, an exposure estimate comparison and rationalisation exercise was performed across the studies to ensure accuracy and consistency of approach. This article evaluates the final exposure estimates and their use in the risk assessments. Overall benzene exposure estimates were low: 90% of participants accumulated less than 20 ppm-years. Mean cumulative exposure was estimated as 5.15 ppm-years, mean duration was 22 years, and mean exposure intensity was 0.2 ppm. 46% of participants were allocated a peak exposure (>3 ppm at least weekly). 40% of participants had a high probability of dermal exposure (based on the relative probability of at least weekly exposure). There were differences in mean intensity of exposure, probability of peak, and/or dermal exposure associated with job category, job site, and decade of exposure. Terminal Operators handling benzene-containing products were the most highly exposed group, followed by Tanker Drivers carrying gasoline. Exposures were higher around 1940-1950 and lower in more recent decades. Overall confidence in the exposure estimates was highest for recently held jobs and for white-collar jobs. We used sensitivity analyses, which included and excluded case-sets on the basis of exposure certainty scores, to inform the risk assessment. The above analyses demonstrated that the different patterns of exposure across the three studies are largely attributable to differences in jobs, site types, and time frames rather than study. This provides reassurance that the previous rationalisation of exposures achieved inter-study consistency and that the data could be confidently pooled.

Estimation of the dietary acrylamide exposure of the Polish population.

PubMed

Mojska, Hanna; Gielecińska, Iwona; Szponar, Lucjan; Ołtarzewski, Maciej

2010-01-01

The objective of our study was to determine acrylamide content in the Polish foods and to assess the average dietary acrylamide exposure of the Polish population. We analysed the acrylamide content in Polish food using GCQ-MS/MS method. The daily dietary acrylamide exposure was computed using a probabilistic approach for the total Polish population (1-96 years) and for the following age groups: 1-6, 7-18 and 19-96, using Monte Carlo simulation technique. To assess the Polish population exposure to acrylamide present in food, food consumption data was taken from the 'Household Food Consumption and Anthropometric Survey in Poland'. The mean content of acrylamide in tested 225 samples of foodstuffs taken randomly all over Poland, ranged widely from 11 to 3647 microg/kg of product. For the total Polish population (1-96 years) the estimated acrylamide mean exposure is 0.43 microg/kg of body weight per day. The main sources of dietary acrylamide in Polish population were as follow: bread--supplied 45% of total dietary acrylamide intake, French fries and potato crisps--23%, roasted coffee--19%. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

On estimation of time-dependent attributable fraction from population-based case-control studies.

PubMed

Zhao, Wei; Chen, Ying Qing; Hsu, Li

2017-09-01

Population attributable fraction (PAF) is widely used to quantify the disease burden associated with a modifiable exposure in a population. It has been extended to a time-varying measure that provides additional information on when and how the exposure's impact varies over time for cohort studies. However, there is no estimation procedure for PAF using data that are collected from population-based case-control studies, which, because of time and cost efficiency, are commonly used for studying genetic and environmental risk factors of disease incidences. In this article, we show that time-varying PAF is identifiable from a case-control study and develop a novel estimator of PAF. Our estimator combines odds ratio estimates from logistic regression models and density estimates of the risk factor distribution conditional on failure times in cases from a kernel smoother. The proposed estimator is shown to be consistent and asymptotically normal with asymptotic variance that can be estimated empirically from the data. Simulation studies demonstrate that the proposed estimator performs well in finite sample sizes. Finally, the method is illustrated by a population-based case-control study of colorectal cancer. © 2017, The International Biometric Society.

Formaldehyde Exposure and Lower Respiratory Infections in Infants: Findings from the PARIS Cohort Study

PubMed Central

Roda, Célina; Kousignian, Isabelle; Guihenneuc-Jouyaux, Chantal; Dassonville, Claire; Nicolis, Ioannis; Just, Jocelyne

2011-01-01

Background: Certain chemical pollutants can exacerbate lower respiratory tract infections (LRIs), a common childhood ailment. Although formaldehyde (FA) is one of the most common air pollutants found in indoor environments, its impact on infant health is uncertain. Objective: Our aim was to determine the impact of FA exposure on the LRI incidence during the first year of life of infants from the Pollution and Asthma Risk: an Infant Study (PARIS) birth cohort. Methods: FA was measured in a random sample of 196 infants’ dwellings, and exposure to this pollutant was estimated for 2,940 infants using predictive models based on measurements and data about potential determinants of FA levels. Health data were collected from parents by regular self-administered questionnaires. We used multivariate logistic regressions to estimate associations between FA exposure and the occurrence of LRI and wheezy LRI (wLRI), adjusting for potential confounders/risk factors. Results: During the first year of life, 45.8% of infants had at least one LRI, and LRI occurred simultaneously with wheezing in 48.7% of cases. The FA predictive models correctly classified 70% of dwellings as having high or low exposure, and we estimated that 43.3% of infants were exposed throughout the first year to levels of FA > 19.5 µg/m3. FA exposure was significantly associated with LRI and wLRI before and after adjustment for known LRI risk factors/confounders. For an interquartile increase in FA levels (12.4 μg/m3), we estimated a 32% [95% confidence interval (CI): 11, 55] and 41% (95% CI: 14, 74) increase in the incidence of LRI and wLRI, respectively. Conclusion: The findings of this study suggest that infants exposed to FA at an early age have an increased incidence of LRI. PMID:21810553

Estimating personal exposures from ambient air-pollution measures: Using meta-analysis to assess measurement error

PubMed Central

Holliday, Katelyn M; Avery, Christy L; Poole, Charles; McGraw, Kathleen; Williams, Ronald; Liao, Duanping; Smith, Richard L; Whitsel, Eric A

2014-01-01

Background Although ambient concentrations of particulate matter ≤10μm (PM10) are often used as proxies for total personal exposure, correlation (r) between ambient and personal PM10 concentrations varies. Factors underlying this variation and its effect on health outcome-PM exposure relationships remain poorly understood. Methods We conducted a random-effects meta-analysis to estimate effects of study, participant and environmental factors on r; used the estimates to impute personal exposure from ambient PM10 concentrations among 4,012 non-smoking, diabetic participants in the Women’s Health Initiative clinical trial; and then estimated the associations of ambient and imputed personal PM10 concentrations with electrocardiographic measures such as heart rate variability. Results We identified fifteen studies (in years 1990-2009) of 342 participants in five countries. The median r was 0.46 (range = 0.13 to 0.72). There was little evidence of funnel-plot asymmetry but substantial heterogeneity of r, which increased 0.05 (95% confidence interval [CI]= 0.01 to 0.09) per 10 μg/m3 increase in mean ambient PM10 concentration. Substituting imputed personal exposure for ambient PM10 concentrations shifted mean percent changes in electrocardiographic measures per 10μg/m3 increase in exposure away from the null and decreased their precision, e.g. −2.0% (95% CI= −4.6% to 0.7%) versus −7.9% (−15.9% to 0.9%) for the standard deviation of normal-to-normal RR interval duration. Conclusions Analogous distributions and heterogeneity of r in extant meta-analyses of ambient and personal PM2.5 concentrations suggest that observed shifts in mean percent change and decreases in precision may be generalizable across particle size. PMID:24220191

Characterization of Changes in Gene Expression and Biochemical Pathways at Low Levels of Benzene Exposure

PubMed Central

Thomas, Reuben; Hubbard, Alan E.; McHale, Cliona M.; Zhang, Luoping; Rappaport, Stephen M.; Lan, Qing; Rothman, Nathaniel; Vermeulen, Roel; Guyton, Kathryn Z.; Jinot, Jennifer; Sonawane, Babasaheb R.; Smith, Martyn T.

2014-01-01

Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings. PMID:24786086

Changes in Risk of Immediate Adverse Reactions to Iodinated Contrast Media by Repeated Administrations in Patients with Hepatocellular Carcinoma

PubMed Central

Fujiwara, Naoto; Tateishi, Ryosuke; Akahane, Masaaki; Taguri, Masataka; Minami, Tatsuya; Mikami, Shintaro; Sato, Masaya; Uchino, Kouji; Enooku, Kenichiro; Kondo, Yuji; Asaoka, Yoshinari; Yamashiki, Noriyo; Goto, Tadashi; Shiina, Shuichiro; Yoshida, Haruhiko; Ohtomo, Kuni; Koike, Kazuhiko

2013-01-01

Background To elucidate whether repeated exposures to iodinated contrast media increase the risk of adverse reaction. Materials and Methods We retrospectively reviewed 1,861 patients with hepatocellular carcinoma who visited authors’ institution, a tertiary referral center, between 2004 and 2008. We analyzed cumulative probability of adverse reactions and risk factors. We categorized all symptoms into hypersensitivity reactions, physiologic reactions, and other reactions, according to the American College of Radiology guidelines, and evaluated each category as an event. We estimated the association between hazard for adverse reactions and the number of cumulative exposures to contrast media. We also evaluated subsequent contrast media injections and adverse reactions. Results There were 23,684 contrast media injections in 1,729 patients. One hundred and thirty-two patients were excluded because they were given no contrast media during the study period. Adverse reactions occurred in 196 (0.83%) patients. The cumulative incidence at 10th, 20th, and 30th examination was 7.9%, 15.2%, and 24.1%, respectively. Presence of renal impairment was found to be one of risk factors for adverse reactions. The estimated hazard of overall adverse reaction gradually decreased until around 10th exposure and rose with subsequent exposures. The estimated hazard of hypersensitivity showed V-shaped change with cumulative number of exposures. The estimated hazard of physiologic reaction had a tendency toward decreasing and that of other reaction had a tendency toward increasing. Second adverse reaction was more severe than the initial in only one among 130 patients receiving subsequent injections. Conclusion Repeated exposures to iodinated contrast media increase the risk of adverse reaction. PMID:24098420

Inter-rater agreement for a retrospective exposure assessment of asbestos, chromium, nickel and welding fumes in a study of lung cancer and ionizing radiation.

PubMed

Seel, E A; Zaebst, D D; Hein, M J; Liu, J; Nowlin, S J; Chen, P

2007-10-01

A retrospective exposure assessment of asbestos, welding fumes, chromium and nickel (in welding fumes) was conducted at the Portsmouth Naval Shipyard for a nested case-control study of lung cancer risk from external ionizing radiation. These four contaminants were included because of their potential to confound or modify the effect of a lung cancer-radiation relationship. The exposure assessment included three experienced industrial hygienists from the shipyard who independently assessed exposures for 3519 shop/job/time period combinations. A consensus process was used to resolve estimates with large differences. Final exposure estimates were linked to employment histories of the 4388 study subjects to calculate their cumulative exposures. Inter-rater agreement analyses were performed on the original estimates to better understand the estimation process. Although concordance was good to excellent (78-99%) for intensity estimates and excellent (96-99%) for frequency estimates, overall simple kappa statistics indicated only slight agreement beyond chance (kappa < 0.2). Unbalanced distributions of exposure estimates partly contributed to the weak observed overall inter-rater agreement. Pairwise weighted kappa statistics revealed better agreement between two of the three panelists (kappa = 0.19-0.65). The final consensus estimates were similar to the estimates made by these same two panelists. Overall welding fume exposures were fairly stable across time at the shipyard while asbestos exposures were higher in the early years and fell in the mid-1970s. Mean cumulative exposure for all study subjects was 520 fiber-days cc(-1) for asbestos and 1000 mg-days m(-3) for welding fumes. Mean exposure was much lower for nickel (140 microg-days m(-3)) and chromium (45 microg-days m(-3)). Asbestos and welding fume exposure estimates were positively associated with lung cancer in the nested case-control study. The radiation-lung cancer relationship was attenuated by the inclusion of these two confounders. This exposure assessment provided exposure estimates that aided in understanding of the lung cancer-radiation relationship at the shipyard.

Violence and Drug Use in Rural Teens: National Prevalence Estimates from the 2003 Youth Risk Behavior Survey

ERIC Educational Resources Information Center

Johnson, Andrew O.; Mink, Michael D.; Harun, Nusrat; Moore, Charity G.; Martin, Amy B.; Bennett, Kevin J.

2008-01-01

Objectives: The purpose of this study was to compare national estimates of drug use and exposure to violence between rural and urban teens. Methods: Twenty-eight dependent variables from the 2003 Youth Risk Behavior Survey were used to compare violent activities, victimization, suicidal behavior, tobacco use, alcohol use, and illegal drug use…

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

Ghosh, Vinita J.; Schaefer, Charles; Kahnhauser, Henry

The National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory was shut down in September 2014. Lead bricks used as radiological shadow shielding within the accelerator were exposed to stray radiation fields during normal operations. The FLUKA code, a fully integrated Monte Carlo simulation package for the interaction and transport of particles and nuclei in matter, was used to estimate induced radioactivity in this shielding and stainless steel beam pipe from known beam losses. The FLUKA output was processed using MICROSHIELD® to estimate on-contact exposure rates with individually exposed bricks to help design and optimize the radiological survey process. Thismore » entire process can be modeled using FLUKA, but use of MICROSHIELD® as a secondary method was chosen because of the project’s resource constraints. Due to the compressed schedule and lack of shielding configuration data, simple FLUKA models were developed in this paper. FLUKA activity estimates for stainless steel were compared with sampling data to validate results, which show that simple FLUKA models and irradiation geometries can be used to predict radioactivity inventories accurately in exposed materials. During decommissioning 0.1% of the lead bricks were found to have measurable levels of induced radioactivity. Finally, post-processing with MICROSHIELD® provides an acceptable secondary method of estimating residual exposure rates.« less

The Burden of Rabies in Tanzania and Its Impact on Local Communities

PubMed Central

Sambo, Maganga; Cleaveland, Sarah; Ferguson, Heather; Lembo, Tiziana; Simon, Cleophas; Urassa, Honorati; Hampson, Katie

2013-01-01

Background Rabies remains a major public health threat in many parts of the world and is responsible for an estimated 55,000 human deaths annually. The burden of rabies is estimated to be around US$20 million in Africa, with the highest financial expenditure being the cost of post-exposure prophylaxis (PEP). However, these calculations may be substantial underestimates because the costs to households of coping with endemic rabies have not been investigated. We therefore aimed to estimate the household costs, health-seeking behaviour, coping strategies, and outcomes of exposure to rabies in rural and urban communities in Tanzania. Methods and Findings Extensive investigative interviews were used to estimate the incidence of human deaths and bite exposures. Questionnaires with bite victims and their families were used to investigate health-seeking behaviour and costs (medical and non-medical costs) associated with exposure to rabies. We calculated that an average patient in rural Tanzania, where most people live on less than US$1 per day, would need to spend over US$100 to complete WHO recommended PEP schedules. High costs and frequent shortages of PEP led to poor compliance with PEP regimens, delays in presentation to health facilities, and increased risk of death. Conclusion The true costs of obtaining PEP were twice as high as those previously reported from Africa and should be considered in re-evaluations of the burden of rabies. PMID:24244767

Lifetime exposure to arsenic in drinking water and bladder cancer: a population-based case–control study in Michigan, USA

PubMed Central

Slotnick, Melissa J.; AvRuskin, Gillian A.; Schottenfeld, David; Jacquez, Geoffrey M.; Wilson, Mark L.; Goovaerts, Pierre; Franzblau, Alfred; Nriagu, Jerome O.

2014-01-01

Objective Arsenic in drinking water has been linked with the risk of urinary bladder cancer, but the dose–response relationships for arsenic exposures below 100 µg/L remain equivocal. We conducted a population-based case–control study in southeastern Michigan, USA, where approximately 230,000 people were exposed to arsenic concentrations between 10 and 100 µg/L. Methods This study included 411 bladder cancer cases diagnosed between 2000 and 2004, and 566 controls recruited during the same period. Individual lifetime exposure profiles were reconstructed, and residential water source histories, water consumption practices, and water arsenic measurements or modeled estimates were determined at all residences. Arsenic exposure was estimated for 99% of participants’ person-years. Results Overall, an increase in bladder cancer risk was not found for time-weighted average lifetime arsenic exposure >10 µg/L when compared with a reference group exposed to <1 µg/L (odds ratio (OR) = 1.10; 95% confidence interval (CI): 0.65, 1.86). Among ever-smokers, risks from arsenic exposure >10 µg/L were similarly not elevated when compared to the reference group (OR = 0.94; 95% CI: 0.50, 1.78). Conclusions We did not find persuasive evidence of an association between low-level arsenic exposure and bladder cancer. Selecting the appropriate exposure metric needs to be thoughtfully considered when investigating risk from low-level arsenic exposure. PMID:20084543

A simulation study to quantify the impacts of exposure ...

EPA Pesticide Factsheets

BackgroundExposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health.MethodsZIP-code level estimates of exposure for six pollutants (CO, NOx, EC, PM2.5, SO4, O3) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error.Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs.ResultsSubstantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3–85% for population error, and 31–85% for total error. When CO, NOx or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copoll

The Value of Using Multiple Metrics to Evaluate PCB Exposure.

PubMed

Archer, Megan C; Harwood, Amanda D; Nutile, Samuel A; Hartz, Kara E Huff; Mills, Marc A; Garvey, Jim E; Lydy, Michael J

2018-04-01

Current methods for evaluating exposure in ecosystems contaminated with hydrophobic organic contaminants typically focus on sediment exposure. However, a comprehensive environmental assessment requires a more holistic approach that not only estimates sediment concentrations, but also accounts for exposure by quantifying other pathways, such as bioavailability, bioaccumulation, trophic transfer potential, and transport of hydrophobic organic contaminants within and outside of the aquatic system. The current study evaluated the ability of multiple metrics to estimate exposure in an aquatic ecosystem. This study utilized a small lake contaminated with polychlorinated biphenyls (PCBs) to evaluate exposure to multiple trophic levels as well as the transport of these contaminants within and outside of the lake. The PCBs were localized to sediments in one area of the lake, yet this area served as the source of PCBs to aquatic invertebrates, emerging insects, and fish and terrestrial spiders in the riparian ecosystem. The Tenax extractable and biota PCB concentrations indicated tissue concentrations were localized to benthic invertebrates and riparian spiders in a specific cove. Fish data, however, demonstrated that fish throughout the lake had PCB tissue concentrations, leading to wider exposure risk. The inclusion of PCB exposure measures at several trophic levels provided multiple lines of evidence to the scope of exposure through the aquatic and riparian food web, which aids in assessing risk and developing potential future remediation strategies.

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.