Literature DB >> 23382274

Estimation of individual rodent water consumption from group consumption data for gestation, lactation, and postweaning life stages using linear regression models.

Elizabeth J Slone1, Linda K Teuschler, Laura L Aume, Michael G Narotsky, Jane Ellen Simmons, Robert A Lordo, Glenn E Rice.   

Abstract

In rodent bioassays where chemicals are administered in the drinking water, water consumption data for individual animals are needed to estimate chemical exposures accurately. If multiple animals share a common water source, as occurs in some studies, only the total amount of drinking water consumed by all animals utilizing the common source is directly measurable, and water consumption rates for individual animals are not available. In the Four Lab Study of the US Environmental Protection Agency, which included a multigenerational rodent bioassay, a complex mixture of drinking water disinfection by-products was delivered to multiple Sprague-Dawley rats from a common drinking water container. To estimate disinfection by-product mixture exposure for each animal, authors developed four log-linear regression models to allocate water consumption among rats sharing a common water container. The four models represented three animal lifestages: Gestation, Lactation, and Postweaning, with separate Postweaning models for male and female. Authors used data from six Sprague-Dawley rat bioassays to develop these models from available individual cage data for the Postweaning models, and available individual animal data for the Gestation and Lactation models. The r(2) values for the model fits were good, ranging from 0.67 to 0.92. The Gestation and Lactation models were generally quite accurate in predicting average daily water consumption whereas the Postweaning models were less robust. These models can be generalized for use in other reproductive and developmental bioassays where common water sources are used and data on the explanatory variables are available.

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Year:  2012        PMID: 23382274     DOI: 10.1093/ilar.53.1.99

Source DB:  PubMed          Journal:  ILAR J        ISSN: 1084-2020


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