Lesa L Aylward1, Evan Green2, Miquel Porta3, Leisa-Maree Toms4, Elly Den Hond5, Christine Schulz6, Magda Gasull3, Jose Pumarega3, André Conrad6, Marike Kolossa-Gehring6, Greet Schoeters5, Jochen F Mueller7. 1. Summit Toxicology LLP, Falls Church, VA, USA; National Research Centre for Environmental Toxicology (ENTOX), University of Queensland, Brisbane, Queensland, Australia. Electronic address: laylward@summittoxicology.com. 2. Statistics Canada, Ottawa, Ontario, Canada. 3. Hospital del Mar Institute of Medical Research - IMIM, Barcelona, CIBER en Epidemiología y Salud Pública, Universitat Autònoma de Barcelona, Spain. 4. Queensland University of Technology, Brisbane, Queensland, Australia. 5. Flemish Institute of Technology (VITO), Mol, Belgium. 6. Federal Environment Agency (UBA), Berlin, Dessau-Roßlau, Germany. 7. National Research Centre for Environmental Toxicology (ENTOX), University of Queensland, Brisbane, Queensland, Australia.
Abstract
BACKGROUND: Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. METHODS: Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2',4,4' tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). RESULTS: Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. CONCLUSIONS: Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.
BACKGROUND: Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. METHODS: Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2',4,4' tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). RESULTS: Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. CONCLUSIONS: Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.
Authors: Daniel Carrizo; Sarah F Brennan; Olivier P Chevallier; Jayne Woodside; Kevin M Cooper; Marie M Cantwell; Geraldine Cuskelly; Christopher T Elliott Journal: Environ Sci Pollut Res Int Date: 2017-08-12 Impact factor: 4.223
Authors: A L Heffernan; K English; Lml Toms; A M Calafat; L Valentin-Blasini; P Hobson; S Broomhall; R S Ware; P Jagals; P D Sly; J F Mueller Journal: Environ Sci Pollut Res Int Date: 2016-09-10 Impact factor: 4.223
Authors: Emily Mosites; Ernesto Rodriguez; Samuel P Caudill; Thomas W Hennessy; James Berner Journal: Int J Circumpolar Health Date: 2020-12 Impact factor: 1.228