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Sources of Uncertainty and Current Practices for Addressing Them: Exposure Perspective,Clarence W. Murray, III, Ph.D.Center for Food Safety and Applied NutritionJune 15, 2011,Outline,Definition of termsDietary exposure modelSources of uncertainty in a dietary exposure assessment Chemical concentration and current practices to address uncertainty Food consumption and current practices to address uncertaintyConclusions,Uncertainty,The imperfect knowledge concerning the present or future state of an organism, system, or (sub)population under consideration.,Variability,The heterogeneity of values over time, space or different members of a population. Variability implies real difference among members of that population.,Dietary Exposure Assessment,The qualitative and/or quantitative evaluation of the likely intake of chemicals (including nutrients) via food, beverage, drinking water, and food supplements.,Yields dietary exposure estimates for a total population or a specific subpopulation (Conc) - Analytical results for a chemical that is measured in a specific food (Food Consumption) - food consumption data is most likely obtained from the most recent National Health and Nutrition Examination Survey (NHANES) or from the Continuing Survey of Food Intakes by Individuals (CSFII).,Dietary Exposure,I,(Conc),(Food Consumption),X,Pr(x)dx,i,Dietary Exposure Model,Sources of Uncertainty in Dietary Exposure Assessment,Chemical concentration dataFood consumption data,Sources of Uncertainty in Dietary Exposure Assessment,Chemical concentration dataFood consumption data,Sources of Uncertainty in Chemical Concentration Data,Sources of uncertainty:Analytical measurements resulting in non-detect values for the chemical concentration in foods.Summary statistics used to describe the chemical concentration in foods.,Sources of Uncertainty in Chemical Concentration Data,Sources of uncertainty:Analytical measurements resulting in non-detect values for the chemical concentration in foods.Summary statistics used to describe the chemical concentration in foods.,Non-Detects in Chemical Concentration,Problem:Analytical techniques are unable to measure chemical concentrations below its limit of detection. Non-detect analytical result does not imply that the chemical is not present in the sample.,Non-Detects in Chemical Concentration,Current practices for addressing the uncertainty from non-detects:Substitution MethodModeling Detected Values,Substitution Method,Non-detects are substituted with the following values:Non-detect = 0Non-detect = Limit of detectionNon-detect = Limit of detectionUpper and lower bounds are derived,Example: Substitution Method,Example: Perchlorate analyses in shredded wheat cereal FDAs Total Diet Study (TDS) (TDS food # 73),Taken from: /Food/FoodSafety/FoodContaminantsAdulteration/ChemicalContaminants/Perchlorate/ucm077615.htm,Modeling Detected Values,Non-detect values are removed from the data setDetected values are modeled with distributionsProbability tree is used to decide which model provides the best fit for the data,Example: Modeling Detected Values,Carrington et al. in press,Sources of Uncertainty in Chemical Concentration Data,Sources of uncertainty:Analytical measurements resulting in non-detect values for the chemical concentration in foods.Summary statistics used to describe the chemical concentration in foods.,Summary Statistics for Chemical Concentration,Problem :In some cases, the full description of the data sets are unavailable. Limited information may lead to unsubstantiated assumption in the selection of the appropriate distribution model to describe the summary statistics.,Summary Statistics for Chemical Concentration,One current practice for addressing the uncertainty from summary statistics:Characterize summary statistics with multiple distribution models,The summary statistics are fitted to multiple distribution models.Use parameter information from a surrogate empirical distribution to model the parameter values for the multiple distribution models.,Characterization of Summary Statistics with Multiple Distribution Models,Example: Characterization of Summary Statistics with Multiple Distribution Models,Lognormal and gamma distributions were used to model the summarystatistics from the National Marine Fisheries Survey data for tilefish, butterfish, and mackerel. Uniform distribution from shark, tuna, and swordfish were used to represent the magnitude of the shape parameter in the tilefish, butterfish, and mackerel distributions.,Carrington and Bolger, Risk Analysis, Vol. 22, No. 4, 2002,Sources of Uncertainty in Dietary Exposure Assessment,Chemical concentration dataFood consumption data,Food Consumption Data,Source of uncertainty:Typically, food consumption data is characterized as the variability of a population consumption for a specific food; however uncertainty arises in this data when a long-term characterization of a specific food is required.,Food Consumption Data,Problem:Short term surveys have the tendency to misrepresent infrequent consumers of a food because the survey does not count a consumer who did not eat a specific food during the survey.Short term survey may project higher consumption for an infrequent consumer of a food.As a result the short term survey may underestimate the numbers of eaters and overestimate the daily consumption for eaters for longer periods of time since the survey fails to count many consumers who consume a product infrequently.,Food Consumption Data,Current practices for addressing uncertainty in food consumption data:Simple Fractional AdjustmentFrequency-Based Adjustment,Simple Fractional Adjustment,LT (p),=,ST,1 (1 p) / CR),CR,LT () long-term consumption distribution,ST short-term consumption distribution,CR Consumer ratio ( the long-term to short-term consumer population),(,),Carrington and Bolger, Toxicological and Industrial Health 2001;17: 176-179,Simple Fractional Adjustment,Carrington and Bolger, Toxicological and Industrial Health 2001;17: 176-179,Frequency-Based Adjustment,LTS,=,STS * 365,CR (/DS),LTS projected annual servings ( the long-term estimate),STS daily servings (from the short-term survey),CR Consumer ratio ( the long-term to short-term consumer population),- inversely related to consumption frequency,- determines the shape of the function,Carrington and Bolger, Toxicological and Industrial Health 2001;17: 176-179,Frequency-Based Adjustment,Carrington and Bolger, Toxicological and Industrial Health 2001;17: 176-179,Conclusions,Uncer