The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

• Published in: Toxics (Basel) Vol. 9; no. 11; p. 303
• Main Authors: East, Alexander, Dawson, Daniel, Glen, Graham, Isaacs, Kristin, Dionisio, Kathie, Price, Paul S., Hubal, Elaine A. Cohen, Vallero, Daniel A.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 12.11.2021; MDPI
• Subjects: Age; Behavior; Blood volume; Body weight; Cardiac output; Chemicals; Combined Human Exposure Model (CHEM); Demographics; Demography; exposome; Exposure; exposure assessment; Heart rate; Households; Income; Mathematical models; Modelling; National Health and Nutrition Examination Survey (NHANES); Nutrition; Parameterization; Parameters; Physiology; Polls & surveys; probabilistic exposure model; Subgroups; Toluene; Variation; vulnerable populations; United States > US
• ISSN: 2305-6304; 2305-6304
• DOI: 10.3390/toxics9110303

Exposure to chemicals is influenced by associations between the individual’s location and activities as well as demographic and physiological characteristics. Currently, many exposure models simulate individuals by drawing distributions from population-level data or use exposure factors for single individuals. The Residential Population Generator (RPGen) binds US surveys of individuals and households and combines the population with physiological characteristics to create a synthetic population. In general, the model must be supported by internal consistency; i.e., values that could have come from a single individual. In addition, intraindividual variation must be representative of the variation present in the modeled population. This is performed by linking individuals and similar households across income, location, family type, and house type. Physiological data are generated by linking census data to National Health and Nutrition Examination Survey data with a model of interindividual variation of parameters used in toxicokinetic modeling. The final modeled population data parameters include characteristics of the individual’s community (region, state, urban or rural), residence (size of property, size of home, number of rooms), demographics (age, ethnicity, income, gender), and physiology (body weight, skin surface area, breathing rate, cardiac output, blood volume, and volumes for body compartments and organs). RPGen output is used to support user-developed chemical exposure models that estimate intraindividual exposure in a desired population. By creating profiles and characteristics that determine exposure, synthetic populations produced by RPGen increases the ability of modelers to identify subgroups potentially vulnerable to chemical exposures. To demonstrate application, RPGen is used to estimate exposure to Toluene in an exposure modeling case example.