Intake calculation models

Two intake calculation models are now available, one for short-term (acute) intake calculations the other for long-term (chronic) intake calculations. These two models present updates of the previous versions, with new adult, vegetarian, elderly and more detailed child consumption data incorporated. As Excel spreadsheets, they are designed to be more user friendly than the previous versions and are available with accompanying guidance notes. 

In this step, the assessor qiuuitifies tlie magnitude, frequency and duration of exposure for each patliway identified in Step 2. Tliis step is most often conducted in two stages estimation of exposure concentrations and calculation of intakes. The later estimation is considered in Step 4. In tliis part of step 3. the exposure assessor determines the concentration of chemicals tliat will be contacted over the exposure period. E.xposure concentrations are estimated using monitoring data and/or chemical transport and environmental fate models. Modeling may be used to estimate future chemical concentrations in media tliat are currently contaminated or tliat may become contaminated, and current concentrations in media and/or at locations for which tliere are no monitoring data. The bulk of the material in tliis chapter is concerned witli tliis step. 

The model is designed to calculate the 241 Am intake that would produce the maximum allowed occupational radiation dose to all major organs, including the bone surfaces, bone marrow, and liver, but the conversion factors for other tissues and organs are published in the same tables. 

The USTUR (1994) model was developed to predict tissue doses and whole-body dose to people who may be exposed to americium. The model has been used to calculate Annual Limits of Intake (ALIs) for 241Am, and yielded similar, but lower limits than those estimated using the ICRP model (1989). 

The XtraFOOD model calculates as output the food intake and resulting contaminant intake, independently for age and gender categories. Exposure can be calculated as being representative for a population or separately for local and background intake. All these intakes are linked to the model output. Additional intakes are provided to add concentration data in non-farm-related foods (e.g. fruit juice, fish, etc.). 

EUSES. As in the case of USEtox model, the present model provides outputs such as human intake fraction of a certain substance for different exposure pathways. In the present case study, estimation of the human intake doses for Guiyu was calculated. These results were compared with the incidence and severity of the effects (dose-response assessment). 

The EDI of phthalates in China, Germany, Taiwan, and US populations are shown in Table 7. The calculation was based on phthalate metabolite (primary and secondary) concentrations, the model of David [137] and the excretion fractions according to various authors [23,28,143,144]. DEHP median values are very close or clearly exceed the TDIs and RfD values (Table 4). The median values for the rest of PAEs are below levels determined to be safe for daily exposures estimated by the US (RfD), the EU and Japan (TDI) (Table 4). However, the upper percentiles of DBP and DEHP urinary metabolite concentrations suggested that for some people, these daily phthalate intakes might be substantially higher than previously assumed and exceed the RfD and TDIs. 

The outcome of low-dose extrapolation is the resulting lifetime cancer risk associated with estimated exposure for a particular population. A wide range of models have been developed for low-dose extrapolation of animal data to calculate a tolerable intake for an acceptable risk, often set at one extra cancer per million exposed persons (see Section 6.2.4 for acceptable risk). 

In addition, existing databases where environmental media and biomonitoring data are collected (such as NHEXAS) could be further studied to estimate exposure and explore the relationships between biomarker concentration and exposure. That information can be used to apportion chemical intake into the different exposure pathways to assist in interpreting population variability, to calculate exposure by combining environmental measurements with survey information to verify estimates of exposure from pharmacokinetic models, and to identify research needs on the basis of discrepancies between estimates obtained from the exposure-pathways analysis and biomonitoring results. 

Further interpretation of urinary biomonitoring data has been attempted with pharmacokinetic simulations by using a relatively simple one-compartment model to convert urinary concentrations to intake doses (Rigas et al. 2001 Shurdut et al. 1998 Barr 2005). The key assumption needed for back-calculation of intake dose from urinary concentration is that 70% of the dose is excreted in the urine as TCP over a relatively short period. 

Pharmacokinetic calculations yielded estimates of chlorpyrifos intake of 0.05-1 pg/kg per day in the general population. The model estimates compare favorably with pathway analysis estimates of aggregate chlorpyrifos exposure from numerous dose routes, including indoor inhalation, dermal contact, and food ingestion (Shurdut et al. 1998 Pang et al. 2002). The calculated exposure doses ranged from 0.02 to 1 pg/kg per day. Further... 

One problem encountered when assessing exposure of human populations to contaminated land is spatial heterogeneity of pollution. To overcome this problem, Gay and Korre (2006) propose the combinations of spatial statistical methods for mapping soil concentrations, and probabilistic human health risk assessment methods. They applied geostatistical methods to map As concentrations in soil. Subsequently, an age-stratified human population was mapped across the contaminated area, and the intake of As by individuals was calculated using a modified version of the Contaminated Land Exposure Assessment (CLEA) model. This approach allowed a... 

Example 2 (continued). In the cohort study conducted by Chao et al. (2005), RRs to measure the association between meat consumption and the risk of colorectal or rectal cancer were calculated using a regression model. Part of the study focused on long-term meat consumption, which was assessed by measuring meat consumption in 1982 and in 1992/1993. Individuals who were in the highest quintile of meat intake in both 1982 and 1992/1993 were compared to individuals in the lowest quintile for both those time periods. Long-term consumption of red meat (high intake)... 

The UEL for reproductive and developmental toxicity is derived by applying uncertainty factors to the NOAEL, LOAEL, or BMDL. To calculate the UEL, the selected UF is divided into the NOAEL, LOAEL, or BMDL for the critical effect in the most appropriate or sensitive mammalian species. This approach is similar to the one used to derive the acute and chronic reference doses (RfD) or Acceptable Daily Intake (ADI) except that it is specific for reproductive and developmental effects and is derived specifically for the exposure duration of concern in the human. The evaluative process uses the UEL both to avoid the connotation that it is the RfD or reference concentration (RfC) value derived by EPA or the ADI derived for food additives by the Food and Drug Administration, both of which consider all types of noncancer toxicity data. Other approaches for more quantitative dose-response evaluations can be used when sufficient data are available. When more extensive data are available (for example, on pharmacokinetics, mechanisms, or biological markers of exposure and effect), one might use more sophisticated quantitative modeling approaches (e.g., a physiologically based pharmacokinetic or pharmacodynamic model) to estimate low levels of risk. Unfortunately, the data sets required for such modeling are rare. 

When calculating chronic dietary exposure, the deterministic models use point values for both food consumption and residue concentration, thereby yielding a point estimate of dietary exposure. In the US, the initial chronic dietary exposure estimate is the Theoretical Maximum Residue Contribution (TMRC) and is analogous to the Theoretical Maximum Daily Intake (TMDI) used to estimate chronic dietary exposure in the EU. Both the TMRC and the TMDI are relatively conservative estimates of dietary expostire. The TMRC is calculated as the product of the mean consumption value and the US pesticide tolerance [6]. In the EU, the TMDI is calculated as the product of the mean consumption value and the Maximum Residue Limit (MRL) [7]. The objective of both calculations is essentially identical to calculate an estimate of the central tendency of the dietary exposure. Both calculated values use the central tendency dietary exposure estimate as the estimate of chronic (long-term) dietary exposure and calculate it using mean consumption data and the maximum residue permitted on the commodity. 

According to the empirical model (Figure 8) the calculated curve of the cumulative C-radioactivity in feces is plotted together with the data points in Figure 7 (lower curve). A fraction, which might be due to the large sampling intervals in the first period after intake of the label, was excreted from the intermediate compartment X3 but could not be detected. 

The model used allows the calculation of the total body pool. As shown in Table I, the total body pool varies with ascorbate intake and ranges between about 10 and 20 mg/kg body weight. 

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