Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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SRA 2013 Annual Meeting Abstracts W3-E.3 Le, HQ*; Lander, DR; Starks, SE; Kreckmann, KH; Symons, JM; DuPont Epidemiology Program (1,3,4,5), DuPont Haskell Global Centers (2); hien.q.le@dupont.com Evaluation of population-based biomonitoring data for risk assessment: An environmental-wide association study approach Background: A biomonitoring equivalent (BE) is the concentration of a chemical or its metabolite in a biological matrix that is estimated from an existing exposure guidance value, such as the U.S. EPA reference dose (RfD). A BE allows evaluation of population-based biomonitoring data relative to estimates from chemical risk assessments. An environmental-wide association study (EWAS), a data-mining method adopted from the genome-wide association study, provides an epidemiologic screening tool that can comprehensively evaluate multiple health outcomes, including self-reported medical conditions and diseases as well as clinical parameters, for potential associations with a biomarker expressed as its BE value. Methods: We evaluated over 120 health outcomes for associations with two selected substances: blood benzene and urinary arsenic for adults in the 2005-06 National Health and Nutrition Examination Survey. Logistic regression models included each substance classified as a dichotomous outcome (above or below the BE) and were adjusted for age, sex, race, smoking, and socioeconomic status. Estimated odds ratios (OR) indicated the association between those with elevated BE values relative to those with concentrations at or below BE values. Results: 2,179 adults (>19 years of age) with biomarker concentrations for benzene and arsenic were included in the analyses. The proportions of adults with blood benzene and urinary arsenic that exceeded BE values were 13% and 68%, respectively. Benzene was positively associated with elevated albumin (OR=2.91, p
SRA 2013 Annual Meeting Abstracts T2-E.4 Levy, JI*; Fabian, MP; Peters, JL; Korrick, SA; Boston University School of Public Health; Channing Division of Network Medicine, Brigham and Women's Hospital; jonlevy@bu.edu Geographic and demographic patterns of health risks associated with chemical and non-chemical stressor exposures in a low-income community Evaluating environmental health risks in communities requires models characterizing geographic and demographic patterns of exposure to multiple stressors, with dose-response models that account for the effects of joint exposures and can be applied to all community residents. In this study, we used simulation methods and structural equation models (SEMs) to construct integrated models of exposure and health risk for a low-income community (New Bedford, Massachusetts) facing multiple chemical and non-chemical stressors. We focused on ADHD-like behavior and blood pressure, two outcomes of interest in New Bedford. We first constructed simulated microdata with multivariate characteristics for all New Bedford residents, applying probabilistic reweighting using simulated annealing to data from the American Community Survey. We then developed exposure models using exposure and demographic data from the Behavioral Risk Factor Surveillance System, the National Health and Nutrition Examination Survey, and a long-standing birth cohort in New Bedford, and applied these models to the microdata to predict exposures to multiple stressors associated with health outcomes of interest. Finally, we developed SEMs of the simultaneous relationships among exposure predictors represented in the microdata, chemical and non-chemical stressor exposures, and health outcomes. SEMs for ADHD-like behavior and blood pressure indicated that multiple demographic variables (e.g., income, country of origin, education) predicted both exposures and outcomes, and that multiple chemical and non-chemical stressors were directly associated with outcomes. Linkage of our SEMs with our exposure models yielded spatially and demographically refined characterization of high-risk subpopulations. This combination of statistical and simulation methods provides a foundation for community-based cumulative risk assessment studies that leverage epidemiological findings. T1-J.3 Lew, N*; Nardinelli, C; Schick, A; Ashley, E; U.S. Food and Drug Administration; Office of Management and Budget; nellie.lew@fda.hhs.gov A Retrospective Cost-Benefit Analysis of the Bar Code Rule With an objective to reduce the number of medication administration errors that occur in hospitals and other healthcare settings each year, FDA published a final regulation in 2004 that requires pharmaceutical manufacturers to place linear bar codes on certain human drug and biological products. At a minimum, the linear barcode must contain the drug’s National Drug Code (NDC) number, which represents the product’s identifying information. The intent was that bar codes would be part of a system where healthcare professionals would use bar code scanning equipment and software to electronically verify against a patient’s medication regimen that the correct medication is being given to the patient before it is administered. By requiring commercial drug product packages and unit-dose blister packages to carry bar code labels, it was anticipated that the rule would stimulate widespread adoption of bar code medication administration (BCMA) technology among hospitals and other facilities, thereby generating public health benefits in the form of averted medication errors. We use the 2004 prospective regulatory impact analysis as the basis to reassess the costs and benefits of the bar code rule. Employing the most recent data available on actual adoption rates of bar code medication administration technology since 2004 and other key determinants of the costs and benefits, we examine the impacts of the bar code rule since its implementation and identify changes in technology that have occurred. In this retrospective study, we also use alternative models of health information technology diffusion to improve estimates of counterfactual scenarios against which we compare the effects of the bar code rule. M2-B.2 Lewis, RJ*; Money, C; Boogaard, PJ; ExxonMobil Biomedical Sciences, Inc.; r.jeffrey.lewis@exxonmobil.com Judging the Quality of Evidence for REACH An approach has been developed for how the quality of human data can be systematically assessed and categorized. The approach mirrors that applied for animal data quality considerations (Klimisch scores), in order that human data can be addressed in a complementary manner to help facilitate transparent (and repeatable) weight of evidence comparisons. The definition of quality proposed accounts for both absolute quality and interpretability, thereby enabling consistent and trasparent incorporation of data into human health risk assessments. Using examples, the presentation will illustrate how the scheme can be applied for weight of evidence comparisons, building from a systematic assessment of available data quality and adequacy. The utility of the scheme for describing data reliability, especially when contributing entries to the IUCLID database, will also be shown. T3-D.1 Li, X*; Lovell, RA; Proescholdt, TA; Benz, SA; McChesney, DG; Division of Animal Feeds, Office of Surveillance and Compliance, Center for Veterinary Medicine, Food and Drug Administration; xin.li@fda.hhs.gov Surveillance of Salmonella Prevalence in Pet Food, Pet Treats and Pet Nutritional Supplements by the United States Food and Drug Administration in 2002 – 2012 The Center for Veterinary Medicine, FDA, conducted a surveillance study to monitor the trend of Salmonella contamination in pet food, pet treats and pet nutritional supplements. The samples were randomly collected from pet food, pet treats and pet nutritional supplements in interstate commerce and at United States ports of entry for surveillance purposes. These samples were tested for the presence of Salmonella. There were 2,026 samples collected in 2002-2012, and 100 were positive for Salmonella (4.94%). This total included 524 pet food samples, of which 28 were positive for Salmonella (5.34%); 1,328 pet treat samples, with 61 were positive for Salmonella (4.59%); and 174 pet nutritional supplement samples, with 11 were positive for Salmonella (6.32%). A significant overall reduction in Salmonella prevalence (p ≤ 0.05) in all three types of samples was observed in the samples collected in 2012 (2.21%) compared to the samples collected in 2002 (12.40%). This study does not include the results of samples collected from follow up to consumer complaints and violations or Salmonella outbreak investigations associated with pet food, pet treats and pet nutritional supplements, which average approximately 30 additional positive Salmonella cases for the past three years (2010-2012). The findings of the FDA Salmonella surveillance study provide Salmonella prevalence information that can be used to address Salmonella contamination problems. The findings can also be used to educate pet owners when handling pet food, pet treats and pet nutritional supplements at home to prevent salmonellosis. December 8-11, 2013 - Baltimore, MD
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Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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