A Multi-Individual Pharmacokinetic Model Framework for Interpreting Time Trends of Persistent Chemicals in Human Populations: Application to a Postban Situation

• DOI: 10.1289/ehp.0900648
• Publication Date: 2009-05-01T01:40:18Z
• Authors: Roland Ritter; Martin Scheringer; Matthew MacLeod; Urs Schenker; Konrad Hungerbühler
• Keywords: exposure science; Research; modeling; persistent organic pollutants; biomonitoring; DDT; exposure science; modeling; persistent organic pollutants; Models, Theoretical; 01 natural sciences; DDT; 3. Good health; 13. Climate action; biomonitoring; Humans; Environmental Pollutants; Half-Life; 0105 earth and related environmental sciences

Human milk and blood are monitored to detect time trends of persistent organic pollutants (POPs) in humans. It is current practice use log-linear regression fit series averaged cross-sectional biomonitoring data, here referred as trend data (CSTD).The goals our study clarify the interpretation half-lives derived from fitting exponential functions declining CSTD provide a method estimating human elimination collected postban situation.We developed multi-individual pharmacokinetic model framework present analytical solutions for period. For this case, quantitatively describes relationships among half-life reduction body burdens POPs CSTD, describing decline daily intake, body.The under conditions exposure independent kinetics. We case DDT (dichlorodiphenyltrichloroethane) show that can be combined with obtained total diet studies estimate kinetics humans background conditions.CSTD quantitative information about The full utility these has not been exploited so far. An efficient informative monitoring strategy banned would coordinate sampling consistent sets young adults studies.