Major national human biomonitoring programs in chemical exposure assessment

Judy Choi; Thit Aarøe Mørck; Anke Joas; Lisbeth E. Knudsen; Judy Choi; Thit Aarøe Mørck; Anke Joas; Lisbeth E. Knudsen

doi:10.3934/environsci.2015.3.782

AIMS Environmental Science

2015, Volume 2, Issue 3: 782-802. doi: 10.3934/environsci.2015.3.782

Previous Article Next Article

Review Special Issues

Major national human biomonitoring programs in chemical exposure assessment

1.
BiPRO GmbH, Munich, Germany;
2.
Department of Public Health, University of Copenhagen, Copenhagen, Denmark

Received: 30 April 2015 Accepted: 21 July 2015 Published: 25 January 2015

Human biomonitoring (HBM) programs have been established in several countries around the world in order to monitor the levels of chemical exposures in the general population and qualify health risk assessment of national and international interest. Study design, population, sample collection, and chemical analysis must be considered when comparing and interpreting the results. In this review, the objectives and brief descriptions of the major national HBM programs in North America, Europe, and Asia are provided. Similarities and differences observed from a comparative analysis among these programs, including the stratification of data according to age, sex, socioeconomic background, etc. as well as the identification of chemical exposure associated with food intake, are discussed. Overall, although there are some discrepancies in the study designs among the reviewed national HBM programs, results from the programs can provide useful information such as chemical levels found within the general population of a country that can be compared. Furthermore, the results can be used by regulatory authorities or the government to enforce legislations in order to reduce the exposure of chemicals into the human body.

Keywords:

Citation: Judy Choi, Thit Aarøe Mørck, Anke Joas, Lisbeth E. Knudsen. Major national human biomonitoring programs in chemical exposure assessment[J]. AIMS Environmental Science, 2015, 2(3): 782-802. doi: 10.3934/environsci.2015.3.782

Related Papers:

[1]	Tyler Cassidy, Morgan Craig, Antony R. Humphries . Equivalences between age structured models and state dependent distributed delay differential equations. Mathematical Biosciences and Engineering, 2019, 16(5): 5419-5450. doi: 10.3934/mbe.2019270
[2]	Asma Alshehri, John Ford, Rachel Leander . The impact of maturation time distributions on the structure and growth of cellular populations. Mathematical Biosciences and Engineering, 2020, 17(2): 1855-1888. doi: 10.3934/mbe.2020098
[3]	Emad Attia, Marek Bodnar, Urszula Foryś . Angiogenesis model with Erlang distributed delays. Mathematical Biosciences and Engineering, 2017, 14(1): 1-15. doi: 10.3934/mbe.2017001
[4]	Katarzyna Pichór, Ryszard Rudnicki . Stochastic models of population growth. Mathematical Biosciences and Engineering, 2025, 22(1): 1-22. doi: 10.3934/mbe.2025001
[5]	Kalyan Manna, Malay Banerjee . Stability of Hopf-bifurcating limit cycles in a diffusion-driven prey-predator system with Allee effect and time delay. Mathematical Biosciences and Engineering, 2019, 16(4): 2411-2446. doi: 10.3934/mbe.2019121
[6]	Yoichi Enatsu, Yukihiko Nakata . Stability and bifurcation analysis of epidemic models with saturated incidence rates: An application to a nonmonotone incidence rate. Mathematical Biosciences and Engineering, 2014, 11(4): 785-805. doi: 10.3934/mbe.2014.11.785
[7]	Zhongcai Zhu, Xiaomei Feng, Xue He, Hongpeng Guo . Mirrored dynamics of a wild mosquito population suppression model with Ricker-type survival probability and time delay. Mathematical Biosciences and Engineering, 2024, 21(2): 1884-1898. doi: 10.3934/mbe.2024083
[8]	Juan Wang, Chunyang Qin, Yuming Chen, Xia Wang . Hopf bifurcation in a CTL-inclusive HIV-1 infection model with two time delays. Mathematical Biosciences and Engineering, 2019, 16(4): 2587-2612. doi: 10.3934/mbe.2019130
[9]	Xinran Zhou, Long Zhang, Tao Zheng, Hong-li Li, Zhidong Teng . Global stability for a class of HIV virus-to-cell dynamical model with Beddington-DeAngelis functional response and distributed time delay. Mathematical Biosciences and Engineering, 2020, 17(5): 4527-4543. doi: 10.3934/mbe.2020250
[10]	Yijun Lou, Bei Sun . Stage duration distributions and intraspecific competition: a review of continuous stage-structured models. Mathematical Biosciences and Engineering, 2022, 19(8): 7543-7569. doi: 10.3934/mbe.2022355

Abstract

References

[1]	Choi J, Mørck TA, Polcher A, et al. (2015) Review of the state of the art of human biomonitoring for chemical substances and its application to human exposure assessment for food safety. EFSA supporting publications 2015: EN-724. Available from: www.efsa.europa.eu/publications.
[2]	Knudsen LE, Hundeboll N, Merlo DF (2012) Chapter 1: Introduction to Human Biomonitoring; Knudsen LE, Merlo DF, editors. Cambridge, UK: The Royal Society of Chemistry.
[3]	Angerer J, Ewers U, Wilhelm M (2007) Human biomonitoring: state of the art. Int J Hyg Environ Health 210: 201-228. doi: 10.1016/j.ijheh.2007.01.024
[4]	Needham LL, Barr DB, Calafat AM (2005) Characterizing children’s exposures: beyond NHANES. Neurotoxicology 26: 547-553. doi: 10.1016/j.neuro.2004.09.006
[5]	Needham LL, Calafat AM, Barr DB (2007) Uses and issues of biomonitoring. Int J Hyg Environ Health 210: 229-238. doi: 10.1016/j.ijheh.2006.11.002
[6]	World Health Organization (2015) Human biomonitoring: facts and figures. Copenhagen: WHO regional office for Europe. Available from: http://www.euro.who.int/en/media-centre/events/events/2015/04/ehp-mid-term-review/publications/human-biomonitoring-facts-and-figures
[7]	Bocca B, Pino A, Alimonti A (2013) Metals as biomarkers of the environmental human exposure. EDP science 1: 3.
[8]	Schulz C, Wilhelm M, Heudorf U, et al. (2012) Reprint of “Update of the reference and HBM values derived by the German Human Biomonitoring Commission”. Int J Hyg Environ Health 215: 150-158. doi: 10.1016/j.ijheh.2012.01.003
[9]	Hays SM, Aylward LL (2012) Interpreting human biomonitoring data in a public health risk context using Biomonitoring Equivalents. Int J Hyg Environ Health 215: 145-148. doi: 10.1016/j.ijheh.2011.09.011
[10]	Pedersen M, Merlo DF, Knudsen LE (2007) Ethical issues related to biomonitoring studies on children. Int J Hyg Environ Health 210: 479-482. doi: 10.1016/j.ijheh.2007.01.013
[11]	Vikstrom AC, Warholm M, Paulsson B, et al. (2012) Hemoglobin adducts as a measure of variations in exposure to acrylamide in food and comparison to questionnaire data. Food Chem Toxicol 50: 2531-2539. doi: 10.1016/j.fct.2012.04.004
[12]	Esteban M, Schindler B, Jiménez-Guerrero J, et al. (2014) Mercury analysis in hair: Comparability and quality assessment within the transnational COPHES/DEMOCOPHES project. Environ Res: In press.
[13]	Castano A, Cutanda F, Esteban M, et al. (2015) Fish consumption patterns and hair mercury levels in children and their mothers in 17 EU countries. Environ Res: In press.
[14]	Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey, 2015. Available from: http://www.cdc.gov/nchs/nhanes.htm.
[15]	Moshfegh AJ, Rhodes DG, Baer DJ, et al. (2008) The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr 88: 324-332.
[16]	Dwyer J, Picciano MF, Raiten DJ, et al. (2003) Collection of Food and Dietary Supplement Intake Data: What We Eat in America-NHANES. J Nutr 133: 590S-600S.
[17]	Centers for Disease Control and Prevention, National Report on Human Exposure to Environmental Chemicals, 2015. Available from: http://www.cdc.gov/exposurereport.
[18]	Statistics Canada, Canadian Health Measures Survey (CHMS), 2014. Available from: http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=5071
[19]	Health Canada, The Canadian Health Measures Survey, 2013. Available from: http://www.hc-sc.gc.ca/ewh-semt/contaminants/human-humaine/chms-ecms-eng.php.
[20]	Health Canada, Third Report on Human Biomonitoring of Environmental Chemicals in Canada — Results of the Canadian Health Measures Survey Cycle 3 (2012-2013), 2015. Available from: http://www.hc-sc.gc.ca/ewh-semt/pubs/contaminants/chms-ecms-cycle3/index-eng.php.
[21]	German Federal Environmental Agency, German Environmental Survey, GerES, 2014. Available from: http://www.umweltbundesamt.de/en/topics/health/assessing-environmentally-related-health-risks/german-environmental-survey-geres.
[22]	Schulz C, Seiwert M, Babisch W, et al. (2012) Overview of the study design, participation and field work of the German Environmental Survey on Children 2003-2006 (GerES IV). Int J Hyg Environ Health 215: 435-448. doi: 10.1016/j.ijheh.2012.02.002
[23]	Becker K, Seiwert M, Casteleyn L, et al. (2014) A systematic approach for designing a HBM pilot study for Europe. Int J Hyg Environ Health 217: 312-322. doi: 10.1016/j.ijheh.2013.07.004
[24]	Den Hond E, Govarts E, Willems H, et al. (2015) First steps toward harmonized human biomonitoring in Europe: demonstration project to perform human biomonitoring on a European scale. Environ Health Perspect 123: 255-263.
[25]	Schoeters G, Den Hond E, Colles A, et al. (2012) Concept of the Flemish human biomonitoring programme. Int J Hyg Environ Health 215: 102-108. doi: 10.1016/j.ijheh.2011.11.006
[26]	Flemish Center of Expertise for Environment and Health, Vlaams Humaan Biomonitoringsprogramma 2007-2011—Resultatenrapport: deel referentie biomonitoring, 2010. Available from: http://www.milieu-en-gezondheid.be/resultaten/referentiebiomonitoring.
[27]	French Institute for Public Health Surveillance, French Nutrition and Health Survey: the “ENNS Survey, 2006” - Nutritional situation in France according to public health objective indicators and recommendations of the French Nutrition and Health Programme (PNNS) - Summary of results, 2007. Available from: http://www.invs.sante.fr/content/download/20471/123869/version/1/file/enns_summary_results_2007_en.pdf.
[28]	Fréry N, Saoudi A, Garnier R, et al. (2010) Exposure of the French population to environmental pollutants—Environmental components of the French National Survey on Nutrition and Health -Initial results. French institute for public health surbeillange. Available from: http://opac.invs.sante.fr/doc_num.php?explnum_id=6867.
[29]	Pérez-Gómez B, Pastor-Barriuso R, Cervantes-Amat M, et al. (2013) BIOAMBIENT.ES study protocol: Rationale and design of a cross-sectional human biomonitoring survey in Spain. Environ Sci Pollut Res Int 20: 1193-1202.
[30]	Cañas AI, Cervantes-Amat M, Esteban M, et al. (2014) Blood lead levels in a representative sample of the Spanish adult population: The BIOAMBIENT.ES project. Int J Hyg Environ Health 217: 452-459. doi: 10.1016/j.ijheh.2013.09.001
[31]	Alimonti A, Bocca B, Mattei D, et al. (2011) Programme for biomonitoring the Italian population exposure (PROBE): internal dose of metals. Available from: www.iss.it/binary/publ/cont/11_9_web.pdf.
[32]	Bocca B, Mattei D, Pino A, et al. (2010) Italian network for human biomonitoring of metals: preliminary results from two Regions. Ann Ist Super Sanita 46: 259-265.
[33]	Cerna M, Krskova A, Cejchanova M, et al. (2012) Human biomonitoring in the Czech Republic: an overview. Int J Hyg Environ Health 215: 109-119. doi: 10.1016/j.ijheh.2011.09.007
[34]	Puklova V, Krskova A, Cerna M, et al. (2010) The mercury burden of the Czech population: An integrated approach. Int J Hyg Environ Health 213: 243-251. doi: 10.1016/j.ijheh.2010.02.002
[35]	Mikeš O, Cupr P, Kohut L, et al. (2012) Fifteen years of monitoring of POPs in the breast milk, Czech Republic, 1994-2009: trends and factors. Environ Sci Pollut Res Int 19: 1936-1943. doi: 10.1007/s11356-012-0798-z
[36]	The Czech Republic National Institute of Public Health, Environmental Health Monitoring, Available from: http://www.szu.cz/topics/environmental-health/environmental-health-monitoring?lang=2.
[37]	Lee JW, Lee CK, Moon CS, et al. (2012) Korea National Survey for Environmental Pollutants in the Human Body 2008: heavy metals in the blood or urine of the Korean population. Int J Hyg Environ Health 215: 449-457. doi: 10.1016/j.ijheh.2012.01.002
[38]	Lee K-M, Kho Y, Chun JB, et al. (2011) Urinary levels of phthalate metabolites in Korean population: KorSEP data, 2009. Available from: http://khis.khu.ac.kr:9090/SummonRecord/FETCH-kiss_primary_32297243.
[39]	Sul D, Ahn R, Im H, et al. (2012) Korea National Survey for Environmental Pollutants in the human body 2008: 1-hydroxypyrene, 2-naphthol, and cotinine in urine of the Korean population. Environ Res 118: 25-30. doi: 10.1016/j.envres.2012.07.010
[40]	De Felip E, Bianchi F, Bove C, et al. (2014) Priority persistent contaminants in people dwelling in critical areas of Campania Region, Italy (SEBIOREC biomonitoring study). Sci Total Environ 487: 420-435. doi: 10.1016/j.scitotenv.2014.04.016
[41]	Region Skåne, Aktuellt om PFAS [News about PFAS], 2015. Available from: http://www.skane.se/sv/Webbplatser/Labmedicin_Skane/Verksamhetsomraden/Arbets--och-miljomedicin/Aktuellt-om-PFAS/.
[42]	Kucera J, Bencko V, Sabbioni E, et al. (1995) Review of trace elements in blood, serum and urine for the Czech and Slovak populations and critical evaluation of their possible use as reference values. Sci Total Environ 166: 211-234. doi: 10.1016/0048-9697(95)04425-Z
[43]	Landrigan PJ, Etzel RA (2014) Textbook of Children's Environmental Health; Landrigan PJ, Etzel RA, editors: Oxford University Press. 608 p.
[44]	World Health Organization, Possible developmental early effects of endocrine disupters on child health, 2012. Available from: http://www.who.int/iris/bitstream/10665/75342/1/9789241503761_eng.pdf.
[45]	Becker K, Müssig-Zufika M, Conrad A, et al. (2008) German Environmental Survey for Children 2003/06-GerES IV, Human Biomonitoring-Levels of selected substances in blood and urine of children in Germany. Available from: http://www.umweltbundesamt.de/en/publikationen/german-environmental-survey-for-children-200306.
[46]	National Academy of Sciences (1993) Pesticides in the diets of infants and children. Washington DC, USA: National Academies Press.
[47]	Barker DJ (2004) The developmental origins of adult disease. J Am Coll Nutr 23: 588S-595S. doi: 10.1080/07315724.2004.10719428
[48]	Ginsberg G, Hattis D, Sonawane B, et al. (2002) Evaluation of Child/Adult Pharmacokinetic Differences from a Database Derived from the Therapeutic Drug Literature. Toxicol Sci 66: 185-200. doi: 10.1093/toxsci/66.2.185
[49]	Becker K, Goen T, Seiwert M, et al. (2009) GerES IV: phthalate metabolites and bisphenol A in urine of German children. Int J Hyg Environ Health 212: 685-692. doi: 10.1016/j.ijheh.2009.08.002
[50]	Calafat AM, Wong LY, Silva MJ, et al. (2011) Selecting adequate exposure biomarkers of diisononyl and diisodecyl phthalates: data from the 2005-2006 National Health and Nutrition Examination Survey. Environ Health Perspect 119: 50-55.
[51]	Kolossa-Gehring M, Becker K, Conrad A, et al. (2008) Exposure of Children to Chemicals, Biological Factors and Noise—the German Environmental Survey on Children (Geres IV). Epidemiology 19: S288.
[52]	Huang W, Caudill SP, Grainger J, et al. (2006) Levels of 1-hydroxypyrene and other monohydroxy polycyclic aromatic hydrocarbons in children: a study based on U.S. reference range values. Toxicol Lett 163: 10-19.
[53]	Li Z, Sandau CD, Romanoff LC, et al. (2008) Concentration and profile of 22 urinary polycyclic aromatic hydrocarbon metabolites in the US population. Environ Res 107: 320-331. doi: 10.1016/j.envres.2008.01.013
[54]	Lunder S, Hovander L, Athanassiadis I, et al. (2010) Significantly higher polybrominated diphenyl ether levels in young U.S. children than in their mothers. Environ Sci Technol 44: 5256-5262.
[55]	Toms LML, Calafat AM, Kato K, et al. (2009) Polyfluoroalkyl chemicals in pooled blood serum from infants, children, and adults in Australia. Environ Sci Technol 43: 4194-4199. doi: 10.1021/es900272u
[56]	Fischer D, Hooper K, Athanasiadou M, et al. (2006) Children Show Highest Levels of Polybrominated Diphenyl Ethers in a California Family of Four: A Case Study. Environ Health Perspect 114: 1581-1584. doi: 10.1289/ehp.8554
[57]	Risher JF, Todd GD, Meyer D, et al. (2010) The elderly as a sensitive population in environmental exposures: making the case. Rev Environ Contam Toxicol 207: 95-157.
[58]	Croes K, De Coster S, De Galan S, et al. (2014) Health effects in the Flemish population in relation to low levels of mercury exposure: from organ to transcriptome level. Int J Hyg Environ Health 217: 239-247. doi: 10.1016/j.ijheh.2013.06.004

This article has been cited by:

1.	D. Breda, O. Diekmann, M. Gyllenberg, F. Scarabel, R. Vermiglio, Pseudospectral Discretization of Nonlinear Delay Equations: New Prospects for Numerical Bifurcation Analysis, 2016, 15, 1536-0040, 1, 10.1137/15M1040931
2.	Deborah Lacitignola, Handling Hysteresis in a Referral Marketing Campaign with Self-Information. Hints from Epidemics, 2021, 9, 2227-7390, 680, 10.3390/math9060680
3.	A. M. Elaiw, A. D. Al Agha, A reaction–diffusion model for oncolytic M1 virotherapy with distributed delays, 2020, 135, 2190-5444, 10.1140/epjp/s13360-020-00188-z
4.	Janejira Tranthi, Thongchai Botmart, Wajaree Weera, Piyapong Niamsup, A New Approach for Exponential Stability Criteria of New Certain Nonlinear Neutral Differential Equations with Mixed Time-Varying Delays, 2019, 7, 2227-7390, 737, 10.3390/math7080737
5.	Daniel Câmara De Souza, Morgan Craig, Tyler Cassidy, Jun Li, Fahima Nekka, Jacques Bélair, Antony R. Humphries, Transit and lifespan in neutrophil production: implications for drug intervention, 2018, 45, 1567-567X, 59, 10.1007/s10928-017-9560-y
6.	Dimitri Breda, Giulia Menegon, Monica Nonino, Delay equations and characteristic roots: stability and more from a single curve, 2018, 14173875, 1, 10.14232/ejqtde.2018.1.89
7.	Luca Gori, Luca Guerrini, Mauro Sodini, Time delays, population, and economic development, 2018, 28, 1054-1500, 055909, 10.1063/1.5024397
8.	DEPENDENCE OF STABILITY OF NICHOLSON'S BLOWFLIES EQUATION WITH MATURATION STAGE ON PARAMETERS, 2017, 7, 2156-907X, 670, 10.11948/2017042
9.	Deborah Lacitignola, Giuseppe Saccomandi, Managing awareness can avoid hysteresis in disease spread: an application to coronavirus Covid-19, 2021, 144, 09600779, 110739, 10.1016/j.chaos.2021.110739
10.	Mats Gyllenberg, Francesca Scarabel, Rossana Vermiglio, Equations with infinite delay: Numerical bifurcation analysis via pseudospectral discretization, 2018, 333, 00963003, 490, 10.1016/j.amc.2018.03.104
11.	Fuad ALHAJ OMAR, PERFORMANCE COMPARISON OF PID CONTROLLER AND FUZZY LOGIC CONTROLLER FOR WATER LEVEL CONTROL WITH APPLYING TIME DELAY, 2021, 2147-9364, 858, 10.36306/konjes.976918
12.	维沈, Dynamic Analysis of Population Models with Time-Delay Coefficients, 2022, 11, 2324-7991, 3164, 10.12677/AAM.2022.115335
13.	Hao Shen, Yongli Song, Hao Wang, Bifurcations in a diffusive resource-consumer model with distributed memory, 2023, 347, 00220396, 170, 10.1016/j.jde.2022.11.044
14.	Libor Pekar, Qingbin Gao, Spectrum Analysis of LTI Continuous-Time Systems With Constant Delays: A Literature Overview of Some Recent Results, 2018, 6, 2169-3536, 35457, 10.1109/ACCESS.2018.2851453
15.	Lőrinc Márton, Control of Multi-Agent Systems with Distributed Delay, 2023, 56, 24058963, 8542, 10.1016/j.ifacol.2023.10.014
16.	Noemi Zeraick Monteiro, Rodrigo Weber dos Santos, Sandro Rodrigues Mazorche, Bridging the gap between models based on ordinary, delayed, and fractional differentials equations through integral kernels, 2024, 121, 0027-8424, 10.1073/pnas.2322424121
17.	Michael Malisoff, Frederic Mazenc, Local Halanay's inequality with application to feedback stabilization, 2024, 0, 2156-8472, 0, 10.3934/mcrf.2024026
18.	Mingzhu Qu, Hideaki Matsunaga, Exact stability criteria for linear differential equations with discrete and distributed delays, 2024, 0022247X, 128663, 10.1016/j.jmaa.2024.128663
19.	Francesca Scarabel, Rossana Vermiglio, Equations with Infinite Delay: Pseudospectral Discretization for Numerical Stability and Bifurcation in an Abstract Framework, 2024, 62, 0036-1429, 1736, 10.1137/23M1581133
20.	Sabrina H. Streipert, Gail S.K. Wolkowicz, Derivation and dynamics of discrete population models with distributed delay in reproduction, 2024, 00255564, 109279, 10.1016/j.mbs.2024.109279
21.	Yonghui Xia, Jianglong Xiao, Jianshe Yu, A diffusive plant-sulphide model: spatio-temporal dynamics contrast between discrete and distributed delay, 2024, 0956-7925, 1, 10.1017/S095679252400069X

Reader Comments

Your name:*

Email:*
© 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)