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

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 i...

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Autores principales:	Alexander East, Daniel Dawson, Graham Glen, Kristin Isaacs, Kathie Dionisio, Paul S. Price, Elaine A. Cohen Hubal, Daniel A. Vallero
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	exposure assessment National Health and Nutrition Examination Survey (NHANES) exposome probabilistic exposure model vulnerable populations Combined Human Exposure Model (CHEM) Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/86debbffc06a463d9f2485fc690b6be6
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spelling	oai:doaj.org-article:86debbffc06a463d9f2485fc690b6be62021-11-25T19:08:16ZThe Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk10.3390/toxics91103032305-6304https://doaj.org/article/86debbffc06a463d9f2485fc690b6be62021-11-01T00:00:00Zhttps://www.mdpi.com/2305-6304/9/11/303https://doaj.org/toc/2305-6304Exposure 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.Alexander EastDaniel DawsonGraham GlenKristin IsaacsKathie DionisioPaul S. PriceElaine A. Cohen HubalDaniel A. ValleroMDPI AGarticleexposure assessmentNational Health and Nutrition Examination Survey (NHANES)exposomeprobabilistic exposure modelvulnerable populationsCombined Human Exposure Model (CHEM)Chemical technologyTP1-1185ENToxics, Vol 9, Iss 303, p 303 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	exposure assessment National Health and Nutrition Examination Survey (NHANES) exposome probabilistic exposure model vulnerable populations Combined Human Exposure Model (CHEM) Chemical technology TP1-1185
spellingShingle	exposure assessment National Health and Nutrition Examination Survey (NHANES) exposome probabilistic exposure model vulnerable populations Combined Human Exposure Model (CHEM) Chemical technology TP1-1185 Alexander East Daniel Dawson Graham Glen Kristin Isaacs Kathie Dionisio Paul S. Price Elaine A. Cohen Hubal Daniel A. Vallero The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
description	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.
format	article
author	Alexander East Daniel Dawson Graham Glen Kristin Isaacs Kathie Dionisio Paul S. Price Elaine A. Cohen Hubal Daniel A. Vallero
author_facet	Alexander East Daniel Dawson Graham Glen Kristin Isaacs Kathie Dionisio Paul S. Price Elaine A. Cohen Hubal Daniel A. Vallero
author_sort	Alexander East
title	The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
title_short	The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
title_full	The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
title_fullStr	The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
title_full_unstemmed	The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk
title_sort	residential population generator (rpgen): parameterization of residential, demographic, and physiological data to model intraindividual exposure, dose, and risk
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/86debbffc06a463d9f2485fc690b6be6
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The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

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