of the short-term climate impacts of stove emissions. Our results indicate that healthand climate impacts span 2 orders of magnitude among the technologies considered.Indoor air pollution is heavily impacted by combustion per<strong>for</strong>mance and ventilation;climate impacts are influenced by combustion per<strong>for</strong>mance and fuel properties includingbiomass renewability. Emission components not included in current carbontrading schemes, such as black carbon particles and carbon monoxide, contribute alarge proportion of the total climate impact. Multiple ‘improved’ stove options analyzedin this paper yield roughly equivalent climate benefits but have different impactson indoor air pollution. Improvements to biomass stoves can improve indoor airquality, which nonetheless remains significantly higher than <strong>for</strong> stoves that use liquidand gaseous hydrocarbons. LPG- and kerosene-fueled stoves have unrivaled air qualitybenefits and their climate impacts are also lower than all but the cleanest stovesusing renewable biomass. Recent data from in-use testing of cookstoves in rural Indiaare also presented.P.42 Griffith WC, Guerrette ZN, Moreira EG, Thompson B, Coronado GD,Vigoren EM, Faustman EM; griffith@uw.eduUniversity of Washington, Fred Hutchinson Cancer Research Center, State University of LondrinaGENE-ENVIRONMENT INTERACTIONS IN EXPOSURE-RESPONSEBETWEEN ORGANOPHOSPHATE PESTICIDE EXPOSURES ANDTHE PHENOTYPIC ANCHOR OF ACETYL-CHOLINESTERASE IN-HIBITION IN FARMWORKERSOur studies in the Yakima valley of Washington state follow 100 farmworkers(orchard workers) and 100 non-farmworkers to investigate potential exposuresto organophosphate pesticides (OPs) by collecting urine samples, blood samples,and home and vehicle dust samples. We assayed the urine samples <strong>for</strong> the 6 diakylnon-specific metabolites of OPs and used a Bayesian Markov chain Monte Carlomethod to estimate the multivariate joint distribution of the metabolites. Since urinesamples were collected on three days we could separate within person variability andobtain more precise estimates of between person variability. We found that DMTP,a metabolite of dimethyl OPs, had the highest concentration in urine compared toother metabolites of OPs, and that azinphosmethyl, a dimethyl OP had the highestconcentration in home and vehicle dust compared to other OPs. In addition, we collecteddata on the inhibition of acetyl-cholinesterase (AChE), a neurotransmitter thatis used as a biomarker in EPA and Washington state standards to remove pesticidehandlers from work. AChE inhibition significantly increased with the concentrationof DMTP. To investigate gene-environment interactions on the exposure responsebetween DMTP and the phenotypic anchor of AChE inhibition we obtainedgenotypes on 80 subjects <strong>for</strong> cytochrome P450 (CYP450) metabolizing enzymes. Wefound that a single nucleotide polymorphism of CYP450 3A5 (6986A>G, rs776746)significantly changed the slope with the heterozygote having an intermediate effect to108the two homozygotes. In the past gene-environment interactions have been difficultto interpret not because of the lack of genetic in<strong>for</strong>mation but rather the lack ofrobust exposure in<strong>for</strong>mation. These results illustrate the importance of gene-environmentinteractions <strong>for</strong> prediction of risk. (Supported by grants P01 ES009601, P30ES007033 from NIEHS and RD-834514, RD-831709, RD-832733 from US EPA.Contents are authors’ responsibility.)P.50 Gu W, Cole D, Hoekstra M; vhg8@cdc.govFederal governmentUSE OF RANDOM FOREST FOR ESTIMATION OF SIGNIFICANT EX-POSURES IN CASE CONTROL STUDIES OF FOODBORNE DISEASESFoodborne diseases are a major public health concern in the U.S., causing anestimated 48 million illnesses annually. Estimating the disease burden attributable tospecific foods is essential <strong>for</strong> development of targeted intervention programs. Casecontrolstudies have been used to identify significant exposures and calculate populationattributable fractions using logistic regression models. However, logistic regressionmay become unreliable in the presence of many correlated exposure variablesand missing values in data, especially where the number of ascertained exposures iscomparable to the number of observations. The technique of random <strong>for</strong>est possessesdesirable properties to accommodate interactions between covariates and missingness.We investigated the per<strong>for</strong>mances of logistic regression and random <strong>for</strong>est invariable selection and prediction using data from a case-control study of Escherichiacoli O157 conducted by the CDC Foodborne Diseases Active Surveillance Network(FoodNet) in 1996. Data obtained from adults (age>19 years) was used, resultingin analysis of 71 cases and 135 matched controls. Univariate logistic regression wasused to evaluate over 100 exposure variables to select plausible candidates <strong>for</strong> variableselection by stepwise logistic regression models. R package randomForest was usedto construct an ensemble of 500 trees <strong>for</strong> estimation of variable importance, withsimultaneous imputation of missing values. We found that the two methods identifieddifferent significant exposure variables. For example, the settings of pink hamburgerexposure were differently identified by random <strong>for</strong>est (restaurant) and logistic regression(home). Accuracy of prediction was examined by cross validation. Random<strong>for</strong>est improved predictive accuracy by 20 percent (measured by AUC under ROC)compared to logistic model. In conclusion, our results suggest that random <strong>for</strong>estprovides a more rigorous tool than conventional logistic regression in estimation andprediction of significant exposures <strong>for</strong> case control studies with missing values andcorrelated covariates.
T2-E.4 Guidotti TL; tee.guidotti@gmail.comMedical Advisory ServicesENTERPRISE- AND WORKPLACE-LEVEL RISK MANAGEMENT ANDTHE DEMING CYCLE<strong>Risk</strong> management in the workplace is a <strong>for</strong>m of process improvement and canbe managed as such. Influenced by the UK Health and Safety Executive and theinternational popularity of the “control banding” approach to managing commonhazards, occupational health and safety professionals have adopted a risk managementapproach. (The terminology is somewhat different than in mainstream risk science.)The general approach of enterprise-based risk assessment and managementwhich underlies control banding and other specific applications and the general approachof quality improvement (and many other management techniques) are basedon a common theory of process improvement codified by the American statisticianW. Edwards Deming (1900 - 1993). This connection is not explicit in the occupationalhealth management literature and is rarely mentioned in the process improvementliterature. The risk cycle reduces to the familiar “Deming Cycle” of qualityimprovement [Plan -> Do -> Study -> Act], which is already management policy atmany employers. The Deming cycle can be used to integrate risk management acrossdomains and to align safety management with overall management. Enterprise-levelrisk assessment and management can be readily integrated into enterprise quality improvementand Six Sigma by making links to the Deming Cycle. Worksite-level riskassessment and management, which can appear complicated to the uninitiated, canbe easily reported in “Deming” terms <strong>for</strong> rapid management comprehension. Corporatepolicies regarding continuous process improvement can be harmonized withpolicies on occupational health protection and safety, realizing practical gains. Occupationalhealth protection measures and outcomes could even be developed as “keyper<strong>for</strong>mance indicators” <strong>for</strong> the entire organization, since they reflect adherence tothe Deming model and are summary indicators of risk-related per<strong>for</strong>mance. Recognizingthis link may open opportunities <strong>for</strong> making gains in occupational health andrisk management in large organizations.T3-D.1 Guikema SD, LaRocca S; larocca@jhu.eduJohns Hopkins UniversityEFFECTS OF NETWORK TOPOLOGY ON VULNERABILITY DURINGTARGETED ATTACKSIn addition to protecting infrastructure systems against traditional threats suchas natural disasters, it is becoming increasingly important to strengthen such systemsagainst intentional attacks (i.e. terrorism). In this talk, we compare the effects ofnetwork topology on system reliability when subjected to various types of targeted attacks.Using a large set of random networks encompassing a wide range of sizes andtopological characteristics representative of real-world networks, we simulate networkelement failures. We examine the cases of attacks based on nodal degree (initial andrecalculated) and nodal betweenness (initial and recalculated). We develop statisticalmodels relating initial topological characteristics of the networks to network per<strong>for</strong>manceafter attacks. This work provides insights into the types of networks mostresilient to various types of targeted attacks.W2-C.2 Gulledge B; bill_gulledge@americanchemistry.comAmerican Chemistry CouncilEPA’S ENDOCRINE DISRUPTOR SCREENING PROGRAM: LESSONSFROM AN INERT SUBSTANCE CONSORTIUMEPA developed the EDSP in response to a Congressional mandate passed in1996 “to determine whether certain substances may have an effect in humans that issimilar to an effect produced by naturally occurring estrogen, or such effects as [EPA]may designate”(21 U.S.C. 346a(p)). EPA’s EDSP consists of two tiers: Tier 1 focuseson evaluating chemicals <strong>for</strong> interaction with the estrogen, androgen and thyroid systems,and Tier 2 focuses on determining adverse effects. As part of the EDSP, EPAissues test orders to collect certain test data on selected chemical substances. In general,EPA intends to use the data collected under the EDSP, along with other in<strong>for</strong>mation,to determine if a chemical may pose a risk to human health or the environmentdue to disruption of the endocrine system. The determination that a chemical doesor is not likely to have the potential to interact with the endocrine system will be madeon a weight-of-evidence basis, taking into account data from the Tier 1 assays and/orother scientifically relevant in<strong>for</strong>mation. Chemicals that go through Tier 1 screeningand are found to have the potential to interact with the estrogen, androgen, or thyroidhormone systems will proceed to the next stage of EDSP where EPA will determinewhich, if any, of the Tier 2 tests are necessary based on the available data. Data froma Tier 1 screening battery are presented and provided in a weight-of-evidence summary.Problems and issues encountered in per<strong>for</strong>ming the required Tier 1 assays aredescribed. Recommendations <strong>for</strong> improvements in Tier 1 and Tier 2 are provided.<strong>Final</strong>ly, perspectives on EPA implementation of the EDSP <strong>for</strong> List 2 chemicals areprovided.W2-D.4 Guo Z, Haimes YY; zg9a@virginia.eduUniversity of VirginiaA SYSTEMIC APPROACH TO BRIDGE SENSING AND MONITORINGSYSTEMSHighway bridges constitute an important part of transportation infrastructureand the lifelines of commerce. The condition of highway bridges is continuouslydeteriorating due to the lack of appropriate maintenance, with 26% of America’sbridges are structurally deficient or functionally obsolete. Bridge inspection evaluatesbridge conditions and provides in<strong>for</strong>mation <strong>for</strong> efficient planning of maintenanceand repair activities. Increasingly, automated structural monitoring sensor systems109
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SECOND FLOOR Floor MapConvention Ce