Contents lists available at ScienceDirect International Journal of Hygiene and Environmental Health journal homepage: www.elsevier.com/locate/ijheh Evaluation of human biomonitoring data in a health risk based context: An updated analysis of population level data from the Canadian Health Measures Survey Sarah Faurea,b, Nolwenn Noiselb, Kate Werrya, Subramanian Karthikeyana, Lesa L. Aylwardc,d, Annie St-Amanda,∗ a Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada bDepartment of Environmental and Occupational Health, University of Montreal, Montreal, Quebec, Canada c Summit Toxicology, LLP, Falls Church, VA, USA dQueensland Alliance for Environmental Health Sciences, University of Queensland, Brisbane, QLD, Australia A R T I C L E I N F O Keywords: Biomonitoring Environmental chemicals Biomonitoring equivalents CHMS Hazard quotient Cancer risk A B S T R A C T In order to characterize exposure of the Canadian population to environmental chemicals, a human biomoni- toring component has been included in the Canadian Health Measures Survey (CHMS). This nationally-re- presentative survey, launched in 2007 by the Government of Canada, has measured over 250 chemicals in approximately 30,000 Canadians during the last decade. The capacity to interpret these data at the population level in a health risk context is gradually improving with the development of biomonitoring screening values, such as biomonitoring equivalents (BE) and human biomonitoring (HBM) values. This study evaluates recent population level biomonitoring data from the CHMS in a health risk context using biomonitoring screening values. Nationally representative biomonitoring data for fluoride, selenium, molybdenum, arsenic, silver, thal- lium, cyfluthrin, 2,4-dichlorophenoxyacetic acid (2,4-D), 3-phenoxybenzoic acid (3-PBA), chlorpyrifos, delta- methrin, bisphenol A, triclosan, acrylamide, cadmium, perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), bromoform, chloroform, benzene, toluene, xylene, ethylbenzene, styrene and tetrachloroethylene were screened as part as this study. For non-cancer endpoints, hazard quotients (HQs) were calculated as the ratio of population level concentrations of a specific chemical at the geometric mean and 95th percentile to the corre- sponding biomonitoring screening value. Cancer risks were calculated at the 5th, 25th, 50th, 75th and 95th percentiles of the population concentration using BEs based on a risk specific dose. Most of the chemicals analyzed had HQs below 1 suggesting that levels of exposure to these chemicals are not a concern at the po- pulation level. However, HQs exceeded 1 in smokers for cadmium, acrylamide and benzene, as well as in the general population for inorganic arsenic, PFOS and PFOA, 3-PBA and fluoride. Furthermore, cancer risks for inorganic arsenic, acrylamide, and benzene at most population percentiles of exposure were elevated (> 10−5). Specifically, for inorganic arsenic in the general population, the HQ was 3.13 at the 95th percentile con- centration and the cancer risk was 3.4×10−4 at the 50th percentile of population concentrations. These results suggest that the levels of exposure in the Canadian population to some of the environmental chemicals assessed might be of concern. The results of this screening exercise support the findings of previous risk assessments and ongoing efforts to reduce risks from exposure to chemicals evaluated as part of this study. Although paucity of biomonitoring screening values for several environmental contaminants may be a limitation to this approach, our assessment contributes to the prioritization of a number of chemicals measured as part of CHMS for follow- up activities such as more detailed characterization of exposure sources. 1. Introduction Exposure of the general population to potentially harmful environmental chemicals is a growing global concern. Biomonitoring, the direct measurement of a biomarker (a chemical or its metabolites) in biological samples such as blood or urine, is an approach used to https://doi.org/10.1016/j.ijheh.2019.07.009 Received 16 May 2019; Received in revised form 19 July 2019; Accepted 20 July 2019 ∗ Corresponding author. 269 Laurier Ave., West Ottawa, Ontario, K1A 0K9, Canada. E-mail addresses: Sarah.faure@canada.ca (S. Faure), Nolwenn.noisel@umontreal.ca (N. Noisel), Kate.werry@canada.ca (K. Werry), Subramanian.karthikeyan@canada.ca (S. Karthikeyan), Laylward@summittoxicology.com (L.L. Aylward), Annie.st-amand@canada.ca (A. St-Amand). International Journal of Hygiene and Environmental Health 223 (2020) 267–280 1438-4639/ Crown Copyright © 2019 Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). T http://www.sciencedirect.com/science/journal/14384639 https://www.elsevier.com/locate/ijheh https://doi.org/10.1016/j.ijheh.2019.07.009 https://doi.org/10.1016/j.ijheh.2019.07.009 mailto:Sarah.faure@canada.ca mailto:Nolwenn.noisel@umontreal.ca mailto:Kate.werry@canada.ca mailto:Subramanian.karthikeyan@canada.ca mailto:Laylward@summittoxicology.com mailto:Annie.st-amand@canada.ca https://doi.org/10.1016/j.ijheh.2019.07.009 http://crossmark.crossref.org/dialog/?doi=10.1016/j.ijheh.2019.07.009&domain=pdf measure exposures to environmental chemicals (Angerer et al., 2011; Hays and Aylward, 2009). Human biomonitoring is included as a component of the Canadian Health Measures Survey (CHMS) to address the monitoring and surveillance component of the Government of Ca- nada's Chemicals Management Plan (Canada, 2006a; Eykelbosh et al., 2018). The CHMS is an ongoing nationally representative survey in- itiated in 2007 by Statistics Canada in partnership with Health Canada and the Public Health Agency of Canada. This survey collects health and wellness data on the general population, such as weight, height, physical fitness and markers of chronic and infectious disease (Eykelbosh et al., 2018; Haines et al., 2017). The biomonitoring com- ponent of the CHMS measures environmental chemicals in blood, urine and/or hair (Health Canada, 2017c). The biomonitoring data have been published as summary statistics for different age and sex groups in CHMS biomonitoring reports for cycle 1 (2007–2009), cycle 2 (2009–2011), cycle 3 (2012–2013) and cycle 4 (2014–2015) (Health Canada, 2010c, 2013, 2015b; 2017c). Collectively, the first four cycles of the CHMS have provided population-level data for over 250 en- vironmental chemicals in Canadians aged 3–79 years. Biomonitoring data are of significant value in exposure assessments as they provide evidence of internal exposure to a chemical from all sources, routes and pathways (Angerer et al., 2011; Clewell et al., 2008; Sexton et al., 2004). However, a lack of appropriate health-based screening values for the general population may impede the inter- pretation of these biological measures in a health risk context (Hays et al., 2007). Health-based screening values are derived from epide- miological data demonstrating a direct, quantitative relationship be- tween biomarker measurement and adverse health effects. Indeed, only a few substances (e.g. lead and mercury) have these health-based screening values because their development is highly resource and time intensive (Hays and Aylward, 2009). Consequently, the biomonitoring equivalent (BE) approach was developed by Hays et al. (2007) as an interim tool for interpreting population level biomonitoring data in a health risk context (Hays et al., 2007). A BE is the concentration of a biomarker of exposure for an environmental chemical in a biological medium (e.g. blood, urine) consistent with an existing exposure gui- dance value for that chemical (Hays et al., 2008a; LaKind et al., 2008). Exposure guidance values for non-cancer health effects include re- ference doses (RfD) from the U.S. Environmental Protection Agency (US EPA) and tolerable or acceptable daily intakes (TDI or ADI) from Health Canada. Cancer-based exposure guidance values include the risk-spe- cific dose (e.g. dose associated with a 10−4 cancer risk from Health Canada) based on oral cancer slope factor or inhalation unit risk de- rived for different chemicals. This study also utilized other screening values such as human biomonitoring-I (HBM-I) values from the German Human Biomonitoring Commission for thallium, perfluorooctane sul- fonate (PFOS) and perfluorooctanoic acid (PFOA) and biomonitoring guidance values (BGVs) for chlorpyrifos (Apel et al., 2017; Arnold et al., 2015; Steckling et al., 2018). HBM-I values are derived based on epi- demiological data on human toxicity and, more recently, using inter- nationally accepted TDI/RfD values or toxicologically well-founded points of departure observed in animal studies (Apel et al., 2017; Schulz et al., 2011). The BGVs for chlorpyrifos are not based upon existing exposure guidance values, but rather use physiologically based phar- macokinetic (PBPK) and pharmacodynamic models to predict levels of biomarkers that are an early indicator of adverse health effects (Arnold et al., 2015). In this article, we use the terminology “biomonitoring screening values” to encompass all of these values (BE, HBM-I, BGV). Biomonitoring screening values are tools that can be used for rapid screening of chemical biomonitoring data to identify exposures of concern and can contribute to ranking of chemical priorities for risk assessment and evaluation of risk management actions. Previously, St-Amand et al. (2014) screened the CHMS population- level data from 2007 to 2009 and 2009–2011 in a risk-based context using BE values. The study suggested that exposures to most of the environmental chemicals assessed, except for inorganic arsenic and cadmium, were below existing exposure guidance values. Since this initial study, additional cycles (2012–2013, 2014–2015) of CHMS data have been released providing more recent biomonitoring data for a number of chemicals included in St-Amand et al. (2014), and data for additional chemicals not measured in earlier cycles. New or updated exposure guidance values and/or biomonitoring screening values have also recently been published for some of the chemicals measured as part of the earlier cycles of CHMS (e.g., silver, fluoride, PFOS, and PFOA). Consequently, this study aims to provide an updated interpretation of population level CHMS biomonitoring data in a health risk based con- text using a set of biomonitoring screening values in order to identify chemicals for which current levels of exposure could be a concern. 2. Methods The following sections describe the criteria used in the selection of CHMS biomonitoring data for analysis, relevant biomonitoring screening values and, finally, the approach used in the risk-based screening of population-level biomonitoring data. 2.1. Selection of biomonitoring data Biomonitoring data from the CHMS are representative of the general population aged 6–79 years for 2007–2009, and 3–79 years for 2009–2011, 2012–2013 and 2014–2015. An overview of the biomoni- toring component of the CHMS as well as a complete list of chemicals measured between 2007 and 2015 are provided in Haines et al. (2017). All chemicals measured in the most recent cycle (2014–2015) with an existing biomonitoring screening value were included in this study, except for bromoform and tetrachloroethylene for which the cycle 3 (2012–2013) data were used due to a low detection rate or high coef- ficient of variation (CV) in Cycle 4. Chemicals measured in cycle 1 or 2 only and for which new biomonitoring screening values have been published since 2014 or for which an updated BE could be calculated based on a new exposure guidance value were also included in this study. These chemicals include cyfluthrin, deltamethrin, molybdenum, selenium, silver, thallium, 2,4-dichlorophenoxyacetic acid (2,4-D), 3- phenoxybenzoic acid (3-PBA), PFOS and PFOA. Biomonitoring screening values developed for non-cancer endpoints were compared to the geometric mean (GM) and 95th percentile (P95) concentrations from the CHMS for the general Canadian population (Tables 1–3) (Health Canada, 2013, 2015b; 2017c). For some chemi- cals, evaluation was conducted using age-specific data, when screening values were derived for specific age groups (fluoride and chlorpyrifos) or when bioaccumulation with age is expected due to long elimination half-lives of the biomarkers (cadmium, PFOA and PFOA). For some chemicals, evaluations were conducted for smokers and non-smokers when evidence shows impact of smoking on blood or urinary con- centrations as in the cases of acrylamide, cadmium, toluene, benzene, ethylbenzene, xylene and styrene (Health Canada, 2017c; Kirman et al., 2012). Statistical estimates for subpopulation of smokers and non- smokers as well as specific age-groups not available as part as CHMS biomonitoring reports were calculated de novo for this exercise. For calculation of cancer risk estimates, population percentiles (P5, P25, P50, P75, and P95) were calculated for smokers and non-smokers for benzene and acrylamide in blood, and for the total population for in- organic arsenic in urine (Table 4). Cancer risk analysis by smoking status was carried out for benzene and acrylamide based on evidence that biomonitoring data for these chemicals may be impacted by smoking (Health Canada, 2017c; Kirman et al., 2012). A urinary coti- nine concentration cut-off of 50 ng/ml was used to define smokers (≥50 ng/ml) and non-smokers (< 50 ng/ml) (SRNT, 2002). The gly- cidamide haemoglobin adduct (GAVal) biomarker may be more critical than the parent compound for carcinogenic properties and, therefore, was used to assess cancer risks associated with exposure of acrylamide (EPA, 2010). For the purpose of this analysis, concentration of S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 268 Ta bl e 1 N on -p er si st en te nv ir on m en ta lc he m ic al s: bi om ar ke rs ,e xp os ur e gu id an ce va lu es ,c or re sp on di ng bi om on ito ri ng sc re en in g va lu es an d bi om on ito ri ng da ta fr om th e Ca na di an H ea lth M ea su re s Su rv ey . Ch em ic al gr ou p Ch em ic al (B io m ar ke rs if di ffe re nt ) Ex po su re gu id an ce va lu es (t yp e; re fe re nc e) Bi om on ito ri ng sc re en in g va lu e, va lu e, re fe re nc e U ni t an d m at ri x CH M S da ta Cy cl e (y ea rs ) A ge gr ou p ye ar s n G M (9 5% CI ) P9 5 (9 5% CI ) M et al s an d tr ac e el em en ts A rs en ic ,i no rg an ic (s um iA s, D M A , M M A ) 0. 00 03 m g/ kg /d (R fD ;U S EP A , 19 91 a) BE :6 .4 H ay s et al .( 20 10 ) μg A s/ L in ur in e Cy cl e 4 (2 01 4– 20 15 ) 3– 79 25 67 5. 1 (4 .5 –5 .6 ) 20 (1 5– 25 ) Fl uo ri de 0. 10 5 m g/ kg /d (T D I; H ea lth Ca na da ,2 01 0b ) BE :3 –6 ye ar s: 1. 36 6– 10 ye ar s: 1. 5 10 –1 8 ye ar s: 2. 5 A yl w ar d et al .( 20 15 ) μg /L in ur in e Cy cl e 4 (2 01 4– 20 15 ) 3- 5 48 3 0. 42 (0 .3 3– 0. 54 ) 1. 6a (0 .6 6– 2. 5) 6- 11 53 3 0. 47 (0 .3 7– 0. 6) 1. 6 (1 .1 –2 ) 12 -1 9 48 1 0. 42 (0 .3 5– 0. 5) 1. 1 (0 .9 1– 1. 2) 20 -3 9 36 9 0. 46 (0 .3 5– 0. 6) 1. 4 (1 .1 –1 .7 ) 40 -5 9 36 8 0. 49 (0 .3 6– 0. 66 ) 1. 4 (1 .1 –1 .7 ) 60 –7 9 34 0 0. 51 (0 .4 3– 0. 61 ) 1. 8 (1 .2 –2 .4 ) M ol yb de nu m 0. 17 m g/ kg /d (N O A EL + U F; H ea lth Ca na da ,2 01 6) BE :7 51 6b H ay s et al .( 20 16 ) μg /L in ur in e Cy cl e 2 (2 00 9– 20 11 ) 3– 79 57 38 45 (4 2– 48 ) 17 0 (1 50 –1 90 ) Se le ni um 40 0 μg /L (U L; IO M ,2 00 0) BE :4 80 H ay s et al .( 20 14 ) μg /L in w ho le bl oo d Cy cl e 2 (2 00 9– 20 11 ) 6– 79 55 75 19 0 (1 90 –1 90 ) 24 0 (2 30 –2 50 ) Si lv er 0, 00 5 m g/ kg /d (R fD ;U S EP A , 19 91 b) BE :0 .4 A yl w ar d et al .( 20 16 ) μg /L in w ho le bl oo d Cy cl e 2 (2 00 9– 20 11 ) 20 –7 9 36 17 0. 07 0 (0 .0 56 –0 .0 86 ) 0. 30 (0 .2 5– 0. 35 ) Th al liu m N A H BM -I: 5 A pe le t al .( 20 17 ) μg /L in ur in e Cy cl e 2 (2 00 9– 20 11 ) 3– 79 63 11 0. 23 (0 .2 1– 0. 24 ) 0. 62 (0 .5 5– 0. 70 ) Pe st ic id es Cy flu th ri n (4 -F -3 -P BA ) 0. 00 5 m g/ kg /d (A D I; H ea lth Ca na da ,2 01 7g ) BE :4 6c H ay s et al .( 20 09 ) μg /L in ur in e Cy cl e 2 (2 00 9– 20 11 ) 3– 79 20 22 N A d 0. 11 a (0 .0 40 –0 .1 7) D el ta m et hr in (c is -D BC A ) 0. 00 3 m g/ kg /d (A D I; H ea lth Ca na da ,2 01 5a ) BE :2 0e A yl w ar d et al .( 20 11 ) μg /L in ur in e Cy cl e 2 (2 00 9– 20 11 ) 3– 79 25 35 0. 01 2 (0 .0 10 –0 .0 14 ) 0. 15 (0 .0 73 –0 .2 3) 2, 4- D ic hl or op he no xy ac et ic ac id 0. 21 m g/ kg /d (R fD ;U S EP A , 20 16 ) BE :3 –6 ye ar s: 70 00 f μg /L in ur in e Cy cl e 2 (2 00 9– 20 11 ) 3- 5 52 3 0. 26 (0 .2 3– 0. 30 ) 1. 1 (0 .8 1– 1. 4) 15 ye ar s + :1 0 50 0f A yl w ar d an d H ay s (2 01 5) 6– 79 20 28 N A d 1 (0 .8 6, 1. 2) Py re th ro id pe st ic id e, va ri ou s (3 -P BA ) 0. 00 1– 0. 25 m g/ kg /d (U S EP A Rf D ;s ee re fe re nc e in A yl w ar d et al ., 20 18 ) BE : 1. 7 (t ie r 1) 87 (t ie r 2) A yl w ar d et al .( 20 18 ) μg /L ur in e Cy cl e 2 (2 00 9– 20 11 ) 3– 79 19 94 0. 43 (0 .3 4– 0. 53 ) 5. 9a (2 .2 –9 .5 ) Ch lo rp yr ifo s (T CP y) N A BG V: 52 0 -I nf an t 21 00 -a du lt A rn ol d et al .( 20 15 ) μg /L ur in e Cy cl e 4 (2 01 4– 20 15 ) 3- 5 47 9 1. 3 (1 .1 –1 .5 ) 7. 3a (4 .5 –1 0) 6- 11 48 9 1. 6 (1 .3 –2 .1 ) N A g 12 -1 9 47 8 1. 5 (1 .3 –1 .7 ) 11 a (6 .3 –1 5) 20 -3 9 33 6 1. 3 (1 .1 –1 .5 ) 8. 4 (5 .9 –1 1) 40 -5 9 29 9 1. 3 (1 .1 –1 .7 ) N A g 60 –7 9 34 1 1. 4 (1 .2 –1 .7 ) 9. 7a (3 .8 –1 6) En vi ro nm en ta l ph en ol s Bi sp he no lA 0. 02 5 m g/ kg /d (p TD I; H ea lth Ca na da ,2 00 8) BE :1 00 0 Kr is hn an et al .( 20 10 a) μg /L ur in e Cy cl e 4 (2 01 4– 20 15 ) 3– 79 20 49 0. 93 (0 .8 7– 0. 99 ) 4. 5 (3 .9 –5 .2 ) Tr ic lo sa n 0. 08 m g/ kg /d (A D I; EC CC an d H C, 20 16 ) BE :1 78 3h Kr is hn an et al .( 20 10 b) μg /L ur in e Cy cl e 4 (2 01 4– 20 15 ) 3– 79 20 47 N A d 66 0a (3 70 –9 40 ) (c on tin ue d on ne xt pa ge ) S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 269 inorganic arsenic was calculated as the sum of inorganic-arsenic ex- posure related urinary metabolites, viz. arsenate, arsenite, dimethy- larsinic acid (DMA) and monomethylarsonic acid (MMA). Statistical estimates (GMs and percentiles of population concentra- tion) for which the CV was between 16.6% and 33.3% are considered to have high sampling variability and caution is recommended when using these data (Health Canada, 2017c). To indicate that these data should be used with caution, these estimates are flagged in data tables, and data points based upon these estimates are marked with the plus (+) symbol in figures. When the CV for an estimate is greater than 33.3%, the value is considered unreliable and is therefore not interpreted using the biomonitoring screening values. GMs were not calculated when greater than 40% of measurements were below the limit of detection (LOD) and, in these cases, the assessment is based solely on the P95. In the calculation of statistical estimates, values below LOD were assigned a value of LOD/2. The estimates were calculated using the Statistical Analysis System (SAS) software and SUDAAN® statistical software package. 2.2. Selection and updating of biomonitoring screening values The general methods for deriving BE and HBM-I values have pre- viously been described (Hays et al., 2008a; Apel et al., 2017), and chemical specific derivations of various biomonitoring screening values are as reported in publications referred to in Tables 1–4. 2.2.1. Biomonitoring equivalents In our analysis, BE values were preferred to other biomonitoring screening values when available. For the underlying exposure guidance values, preference was given to those from Health Canada, followed by those from the US EPA. However, in some cases, the exposure guidance value was chosen based on the most relevant route of exposure. Blood screening values derived using the BE approach are available for vo- latile organic compounds (VOCs) such as toluene and ethylbenzene. These blood screening values, derived in absence of specific PBPK model for several VOCs, are defined as the estimate of chemical specific steady-state blood concentrations associated with chronic oral and in- halation exposure at the corresponding US EPA RfD or Health Canada TDI concentrations (Aylward et al., 2010). Within this study, they are referred to as BE values. BE values based upon risk specific doses (RSD) from cancer risk assessments (i.e. BERSD) are available for acrylamide, arsenic and benzene. Since the St-Amand et al. (2014) study, an up- dated BE was published for 2,4-dichlorophenoxyacetic acid. In addi- tion, BE values were recalculated for chemicals where the underlying exposure guidance values (e.g. RfD, TDI/ADI) have been revised since the original screening value publication (see details in Tables 1–4). These chemicals include molybdenum, cyfluthrin, deltamethrin, tri- closan, GAVal, toluene, xylene and ethylbenzene. 2.2.2. Other biomonitoring screening values HBM-I values were used for thallium and for the perfluoroalkyl substances, perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) (Apel et al., 2017; Steckling et al., 2018). In the assessment of chlorpyrifos, the BGVs developed by Arnold et al. (2015) were used. These values represent the levels of urinary biomarker (3,5,6-trichloro- 2-pyridinol, TCPy) for chlorpyrifos at which 10% of red blood cell cholinesterase inhibition is predicted to occur in 95% of a population following acute oral exposure. 2.3. Calculation of hazard quotients For non-cancer endpoints, hazard quotients (HQ) were calculated as the ratio of the biomarker concentration, at the GM or P95, to the chemical-specific biomonitoring screening value: HQ= [biomarker] / biomonitoring screening value (1)Ta bl e 1 (c on tin ue d) Ch em ic al gr ou p Ch em ic al (B io m ar ke rs if di ffe re nt ) Ex po su re gu id an ce va lu es (t yp e; re fe re nc e) Bi om on ito ri ng sc re en in g va lu e, va lu e, re fe re nc e U ni t an d m at ri x CH M S da ta Cy cl e (y ea rs ) A ge gr ou p ye ar s n G M (9 5% CI ) P9 5 (9 5% CI ) A cr yl am id e A cr yl am id e (A A Va l) 0. 00 2 m g/ kg /d (R fD ;U S EP A , 20 10 ) BE :1 90 H ay s an d A yl w ar d (2 00 8) ; A yl w ar d et al .( 20 13 ) pm ol /g H b, w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 3– 79 (N S) 21 87 56 (5 1– 61 ) 11 0 (8 1– 14 0) 3– 79 (S ) 26 5 13 0 (1 10 –1 40 ) 29 0 (2 20 –3 60 ) A cr yl am id e (G A Va l) 0. 00 2 m g/ kg /d (R fD ;U S EP A , 20 10 ) BE :1 76 i H ay s an d A yl w ar d (2 00 8) pm ol /g H b, w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 3– 79 (N S) 21 87 52 (4 7– 58 ) 11 0 (9 3– 13 0) 3– 79 (S ) 26 5 10 0 (8 7– 11 0) 25 0 (1 80 –3 20 ) A bb re vi at io ns :2 ,4 -D :2 ,4 -D ic hl or op he no xy ac et ic ac id ,3 -P BA :3 -P he no xy be nz oi c ac id ,4 -F -3 -P BA :4 -F lu or o- 3- ph en ox yb en zo ic ac id ,A A Va l: A cr yl am id e he m og lo bi n va lin e te rm in al ad du ct s, A D I: A cc ep ta bl e da ily in ta ke , BE :B io m on ito ri ng eq ui va le nt ,B G V: Bi om on ito ri ng gu id an ce va lu es ,C H M S: Ca na di an H ea lth M ea su re s Su rv ey ,C I: Co nfi de nc e in te rv al ,c is -D BC A ,c is -3 -( 2, 2- D ib ro m ov in yl )- 2, 2- di m et hy lc yc lo pr op an e ca rb ox yl ic ac id , D M A :D im et hy la rs in ic ac id ,G A Va l: G ly ci da m id e he m og lo bi n va lin e te rm in al ad du ct s, G M :G eo m et ri c m ea n, H b: H em og lo bi n, H BM -I: H um an bi om on ito ri ng va lu e I, iA S: In or ga ni c ar se ni c, IO M :I ns tit ut e of M ed ec in e; M M A :M on om et hy la rs on ic ac id ,N A :N ot av ai la bl e, N S: N on -s m ok er s, P9 5: 95 th pe rc en til e, PO D :P oi nt of de pa rt ur e, pT D I: Pr ov is io nn al to le ra bl e da ily in ta ke ,R fD :R ef er en ce do se ,S :S m ok er s, TC Py :3 ,5 ,6 -T ri ch lo ro -2 - py ri di no l, TD I: To le ra bl e da ily in ta ke ,U F: U nc er ta in fa ct or ,U L: To le ra bl e up pe r in ta ke le ve ls . a D at a sh ou ld be us ed w ith ca ut io n as th e co effi ci en t of va ri at io n is be tw ee n 16 .6 % an d 33 .3 % . b A ne w BE w as ca lc ul at ed us in g a re ce nt N O A EL ad op te d by H ea lth Ca na da (H ea lth Ca na da ,2 01 6) ,m et ho do lo gy as de sc ri be d pr ev io us ly (H ay s et al ., 20 16 ), an d a U F of 10 0. c A ne w BE w as ca lc ul at ed us in g a re ce nt H ea lth Ca na da A D I( H ea lth Ca na da ,2 01 7g ), m et ho do lo gy as de sc ri be d pr ev io us ly (H ay s et al ., 20 09 ), an d a U F of 30 0 ap pl ie d to th e PO D . d If > 40 % of sa m pl es w er e be lo w th e lim it of de te ct io n, th e G M w as no tc al cu la te d. e A ne w BE w as ca lc ul at ed us in g a re ce nt H ea lth Ca na da A D I( H ea lth Ca na da ,2 01 5a ), m et ho do lo gy as de sc ri be d pr ev io us ly (A yl w ar d et al ., 20 11 ), an d a U F of 30 0 ap pl ie d to th e PO D . f Th e BE w as up da te d si nc e th e pr ev io us CH M S sc re en in g an al ys is (S t-A m an d et al ., 20 14 ) to re fle ct ch an ge s m ad e to th e U S EP A as se ss m en t. g D at a ar e to o un re lia bl e to be pu bl is he d. h A ne w BE w as ca lc ul at ed us in g a re ce nt EC CC an d H C A D I( EC CC an d H C, 20 16 ), m et ho do lo gy as de sc ri be d pr ev io us ly (K ri sh na n et al ., 20 10 b) ,a nd a U F of 30 0 ap pl ie d to th e PO D . i A ne w BE w as ca lc ul at ed us in g a re ce nt U S EP A Rf D (U S EP A ,2 01 0) ,m et ho do lo gy as de sc ri be d pr ev io us ly (H ay s an d A yl w ar d, 20 08 ) an d a U F of 10 ap pl ie d to th e PO D . S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 270 Ta bl e 2 Pe rs is te nt en vi ro nm en ta lc he m ic al s: bi om ar ke rs ,e xp os ur e gu id an ce va lu es ,c or re sp on di ng bi om on ito ri ng sc re en in g va lu es an d bi om on ito ri ng da ta fr om th e Ca na di an H ea lth M ea su re s Su rv ey . Ch em ic al gr ou p Ch em ic al Ex po su re gu id an ce va lu es (t yp e, re fe re nc e) Bi om on ito ri ng sc re en in g va lu e, va lu e, re fe re nc e U ni t an d m at ri x CH M S da ta Cy cl e (y ea rs ) A ge gr ou p, ye ar n G M (9 5% CI ) P9 5 (9 5% CI ) M et al s an d tr ac e el em en ts Ca dm iu m 0. 00 05 m g/ kg /d (R fD ; U S EP A ,1 98 9) BE :1 .7 H ay s et al .( 20 08 b) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 3- 5 (N S) 44 0 0. 08 2 (< LO D –0 .0 91 ) 0. 2 (0 .1 5– 0. 25 ) 6- 11 (N S) 90 9 0. 09 5 (0 .0 86 –0 .1 0) 0. 19 (0 .1 7– 0. 22 ) 12 -1 9 (N S) 86 3 0. 12 (0 .1 2– 0. 13 ) 0. 29 (0 .2 6– 0. 31 ) 20 -3 9 (N S) 77 5 0. 18 (0 .1 6– 0. 21 ) 0. 52 (0 .4 5– 0. 59 ) 40 -5 9 (N S) 80 9 0. 25 (0 .2 3– 0. 28 ) 0. 62 (0 .5 2– 0. 71 ) 60 -7 9 (N S) 84 0 0. 34 (0 .3 2– 0. 35 ) 0. 88 (0 .7 8– 0. 98 ) 12 -1 9 (S ) 80 0. 59 a (0 .4 –0 .8 8) 2. 8 (2 .0 –3 .7 ) 20 -3 9 (S ) 27 0 1. 8 (1 .4 –2 .4 ) 5. 2 (4 .1 –6 .4 ) 40 -5 9 (S ) 21 7 1. 8 (1 .4 –2 .3 ) 5. 4a (2 .9 –7 .8 ) 60 -7 9 (S ) 13 6 2 (1 .6 –2 .4 ) 5 (3 .6 –6 .3 ) Pe rfl uo ro al ky l su bs ta nc es Pe rfl uo ro oc ta ne su lfo na te (P FO S) PO D :1 –1 5 ng /m l H BM -I: 5 A pe le t al .( 20 17 ) μg /L in pl as m a Cy cl e 2 (2 00 9– 20 11 ) 12 –1 9 50 7 4. 6 (4 .0 –5 .2 ) 11 (9 .2 –1 3) 20 –3 9 36 2 6. 2 (5 .4 –7 .1 ) 19 a (9 .6 –2 9) 40 –5 9 33 4 6. 4 (5 .7 –7 .2 ) 16 (1 3– 19 ) 60 –7 9 32 1 9. 4 (8 .3 –1 1) 21 a (7 .5 –3 5) Pe rfl uo ro oc ta no ic ac id (P FO A ) PO D :1 –1 0 ng /m l H BM -I: 2 A pe le t al .( 20 17 ) μg /L in pl as m a Cy cl e 2 (2 00 9– 20 11 ) 12 –1 9 50 7 2. 1 (1 .9 –2 .3 ) 4. 1 (3 .6 –4 .5 ) 20 –3 9 36 2 2. 2 (1 .9 –2 .5 ) 5. 8 (3 .9 –7 .6 ) 40 –5 9 33 4 2. 2 (2 .0 –2 .4 ) 4. 4 (3 .9 –5 ) 60 –7 9 32 1 2. 8 (2 .4 –3 .2 ) 6. 4 (4 .6 –8 .1 ) A bb re vi at io ns :B E: Bi om on ito ri ng eq ui va le nt ,C H M S: Ca na di an H ea lth M ea su re s Su rv ey ,C I: Co nfi de nc e in te rv al ,G M :G eo m et ri c m ea n, H BM -I: H um an bi om on ito ri ng va lu e I, N S: N on -s m ok er s, P9 5: 95 th pe rc en til e, PF O A :P er flu or oo ct an oi c ac id ,P FO S: Pe rfl uo ro oc ta ne su lfo ni c ac id ,R fD :R ef er en ce do se ,S :S m ok er s. a D at a sh ou ld be us ed w ith ca ut io n as th e co effi ci en t of va ri at io n is be tw ee n 16 .6 % an d 33 .3 % . S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 271 Ta bl e 3 Vo la til e or ga ni c co m po un ds :b io m ar ke rs ,e xp os ur e gu id an ce va lu es ,c or re sp on di ng bi om on ito ri ng sc re en in g va lu es an d bi om on ito ri ng da ta fr om th e Ca na di an H ea lth M ea su re s Su rv ey . Ch em ic al Ex po su re gu id an ce va lu es (t yp e, re fe re nc e) BE va lu e, re fe re nc e U ni t an d m at ri x CH M S da ta Cy cl e (y ea rs ) ag e gr ou p, ye ar n G M (9 5% CI ) P9 5 (9 5% CI ) Br om of or m 0. 03 m g/ kg /d (R fD ;U S EP A ,2 00 5) 0. 13 A yl w ar d et al .( 20 08 ) μg /L w ho le bl oo d Cy cl e 3 (2 01 2– 20 13 ) 12 –7 9 24 96 N A a 0. 01 b (< LO D –0 .0 15 ) Ch lo ro fo rm 0. 01 m g/ kg /d (R fD ;U S EP A ,2 00 1) 0. 23 A yl w ar d et al .( 20 08 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 25 27 N A a 0. 04 3b (0 .0 22 –0 .0 64 ) Be nz en e 30 μg /m 3 (R fC ,U S EP A ,2 00 3) 0. 15 H ay s et al .( 20 12 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (N S) 18 96 0. 02 5b (0 .0 17 –0 .0 37 ) 0. 09 7 (0 .0 78 –0 .1 2) 12 –7 9 (S ) 40 0 0. 14 (0 .1 2– 0. 15 ) 0. 42 (0 .3 4– 0. 50 ) To lu en e 2. 3 m g/ m 3 (I nd oo rA ir G ui de lin e; H ea lth Ca na da ,2 01 1) 7. 16 c A yl w ar d et al .( 20 10 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (N S) 19 23 0. 09 8 (0 .0 72 –0 .1 3) 0. 33 b (0 .1 9– 0. 48 ) 12 –7 9 (S ) 40 3 0. 34 (0 .2 7– 0. 41 ) 0. 9 (0 .7 3– 1. 1) Et hy lb en ze ne 0. 02 2 m g/ kg /d (T D I, H ea lth Ca na da , 20 14 ) 0. 45 d A yl w ar d et al .( 20 10 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (N S) 20 34 0. 02 2 (0 .0 18 –0 .0 26 ) 0. 06 8 (0 .0 4– 0. 08 8) 12 –7 9 (S ) 41 2 0. 06 1 (0 .0 52 –0 .0 72 ) 0. 13 (0 .1 1– 0. 16 ) Xy le ne s 0. 18 m g/ m 3 (T C, H ea lth Ca na da ,1 99 6) 0. 5e A yl w ar d et al .( 20 10 ) Se e no te μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (N S) 19 67 40 2 0. 06 6 (0 .0 54 –0 .0 80 ) 0. 17 (0 .1 5– 0. 19 ) 0. 26 (0 .1 7– 0. 34 ) 0. 44 (0 .3 2– 0. 55 ) 12 –7 9 (S ) St yr en e 1 m g/ m 3 (R fC ,U S EP A ,1 99 2) 3 A yl w ar d et al .( 20 10 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (N S) 20 50 0. 04 8 (0 .0 37 –0 .0 63 ) 0. 1 (0 .0 83 –0 .1 2) 12 –7 9 (S ) 41 7 0. 09 3 (0 .0 77 –0 .1 1) 0. 19 (0 .1 5– 0. 23 ) Te tr ac hl or oe th yl en e 0. 36 m g/ m 3 (T C, H ea lth Ca na da ,1 99 6) 4 A yl w ar d et al .( 20 10 ) μg /L w ho le bl oo d Cy cl e 3 (2 01 2– 20 13 ) 12 –7 9 24 53 N A a 0. 17 b (0 .1 0– 0. 23 ) A bb re vi at io ns : BE : Bi om on ito ri ng eq ui va le nt , CH M S: Ca na di an H ea lth M ea su re s Su rv ey , CI : Co nfi de nc e in te rv al , G M : G eo m et ri c m ea n, N S: N on -s m ok er s, P9 5: 95 th pe rc en til e, Rf C: Re fe re nc e co nc en tr at io n, Rf D : Re fe re nc e do se ,S :S m ok er s, TC :T ol er ab le co nc en tr at io n, U F: U nc er ta in fa ct or . a If > 40 % of sa m pl es w er e be lo w th e lim it of de te ct io n, th e G M w as no t ca lc ul at ed . b D at a sh ou ld be us ed w ith ca ut io n as co effi ci en t of va ri at io n is be tw ee n 16 .6 % an d 33 .3 % . c A ne w BE w as ca lc ul at ed us in g a re ce nt H ea lth Ca na da A ir G ui da nc e va lu e (H ea lth Ca na da ,2 01 1) ,m et ho do lo gy as de sc ri be d pr ev io us ly (A yl w ar d et al ., 20 10 ) an d ap pl yi ng an U F of 10 to th e PO D . d A ne w BE w as ca lc ul at ed us in g a re ce nt H ea lth Ca na da TD I( H ea lth Ca na da ,2 01 4) ,m et ho do lo gy as de sc ri be d pr ev io us ly (A yl w ar d et al ., 20 10 ) an d ap pl yi ng an U F of 25 to th e PO D . e A ne w BE w as ca lc ul at ed us in g a re ce nt H ea lth Ca na da TC (H ea lth Ca na da ,1 99 6) ,m et ho do lo gy as de sc ri be d pr ev io us ly (A yl w ar d et al ., 20 10 ) an d ap pl yi ng an U F of 10 00 to th e PO D . S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 272 Ta bl e 4 Ca nc er re fe re nc e va lu e, co rr es po nd in g Bi om on ito ri ng Eq ui va le nt at ri sk sp ec ifi c do se s (B E R SD ) an d bi om on ito ri ng da ta fo r su bs ta nc es m ea su re d in th e Ca na di an H ea lth M ea su re s Su rv ey . Ch em ic al gr ou p Ch em ic al (b io m ar - ke r if di ffe re nt ) Ca nc er re fe re nc e va lu es (t yp e, re fe re nc e) BE R SD 1 × 10 -4 ri sk le ve l, re fe re nc e U ni t an d m at ri x CH M S da ta Cy cl e (y ea rs ) A ge gr ou p, ye ar n 5 th pe rc en til es 25 th pe rc en til es 50 th pe rc en til es 75 th pe rc en til es 95 th pe rc en til es A cr yl am id e A cr yl am id e (G A Va l) 0. 5 (m g/ kg /d )− 1 (O ra lc an ce r sl op e fa ct or , U S EP A ,2 01 0) 4. 88 a H ay s an d A yl w ar d (2 00 8) pm ol /g H b w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 3– 79 (S ) 26 5 39 (3 1– 47 ) 64 (4 7– 81 ) 97 (7 8– 12 0) 15 0 (1 20 –1 80 ) 25 0 (1 80 –3 20 ) 3– 79 (N S) 21 87 25 b (< LO D –3 7) 40 (3 7– 43 ) 51 (4 6– 56 ) 68 (6 0– 75 ) 11 0 (9 3– 13 0) M et al s an d tr ac e el em en ts A rs en ic (s um of iA s, M M A ,D M A ) 1. 8 (m g/ kg /d )-1 (O ra lc an ce r sl op e fa ct or , H ea lth Ca na da ,2 00 6) 1. 4c H ay s et al .( 20 10 ) μg A s/ L ur in e Cy cl e 4 (2 01 4– 20 15 ) 3– 79 25 67 1. 9b (0 .7 9– 3. 0) 3. 3 (3 .1 –3 .5 ) 4. 8 (4 .2 –5 .4 ) 8. 4 (7 .0 –9 .7 ) 20 (1 5– 26 ) VO Cs Be nz en e 2. 2 × 10 − 6 -7 .8 × 10 − 6 (μ g/ m 3 ) -1 (I nh al at io n U ni t Ri sk ,U S EP A ,2 00 0) 0. 05 8– 0. 20 d H ay s et al .( 20 12 ) μg /L w ho le bl oo d Cy cl e 4 (2 01 4– 20 15 ) 12 –7 9 (S ) 40 0 0. 02 9b (0 .0 18 –0 .0 98 ) 0. 09 8 (0 .0 81 –0 .1 1) 0. 14 (0 .0 98 –0 .1 8) 0. 21 (0 .1 7– 0. 25 ) 0. 42 (0 .3 4– 0. 45 ) 12 –7 9 (N S) 18 96 N A e 0. 01 3b (< LO D -0 .0 21 ) 0. 03 b (0 .0 12 –0 .0 40 ) 0. 04 8b (0 .0 29 –0 .0 68 ) 0. 09 7 (0 .0 78 –0 .1 2) A bb re vi at io ns :B E: Bi om on ito ri ng eq ui va le nt ,B M D L: Be nc hm ar k D os e Lo w er bo un d; CH M S: Ca na di an H ea lth M ea su re s Su rv ey ,C I: Co nfi de nc e in te rv al ,D M A :D im et hy la rs in ic ac id ,G A Va l: G ly ci da m id e he m og lo bi n va lin e te rm in al ad du ct s, H b: H em og lo bi n, iA S: In or ga ni c ar se ni c, M M A :M on om et hy la rs on ic ac id ,N S: N on -s m ok er s, S: Sm ok er s, VO Cs :V ol at ile or ga ni c co m po un ds . a A ne w BE R SD w as ca lc ul at ed us in g a re ce nt U S EP A or al ca nc er sl op e fa ct or (U S EP A ,2 01 0) ,m et ho do lo gy as de sc ri be d pr ev io us ly (H ay sa nd A yl w ar d, 20 08 ). A m or e re ce nt BM D L1 0 ad op te d by H ea lth Ca na da (H ea lth Ca na da ,2 01 2) as th e PO D re su lts in a BE R SD of 4. 39 pm ol /g H b, a va lu e cl os e to 4. 88 pm ol /g H b us ed in th is w or k, an d do es no t m od ify ri sk in te rp re ta tio n of po pu la tio n pe rc en til es . b D at a sh ou ld be us ed w ith ca ut io n as co effi ci en t of va ri at io n is be tw ee n 16 .6 % an d 33 .3 % . c A m or e re ce nt JE CF A BM D L0 .5 of 3 μg /k g/ d (J EC FA ,2 01 1) is ad op te d by H ea lth Ca na da in its Sc ie nt ifi c A ss es sm en ti n Su pp or to fa Lo w er To le ra nc e fo rA rs en ic in A pp le Ju ic e. U si ng th is BM D L re su lts in a BE RS D of 1. 45 μg A s/ L, a va lu e cl os e to 1. 4μ g A s/ L us ed in th is w or k, an d do es no t m od ify ri sk in te rp re ta tio n of po pu la tio n pe rc en til es . d H C (1 99 6) TC 05 = 15 m g/ m 3 . Th e ri sk -s pe ci fic do se at a 1 × 10 − 4 ri sk le ve li s 30 μg /m 3 , w ith in th e ra ng e of U S EP A fo r w hi ch th e ri sk -s pe ci fic do se at a 1 × 10 − 4 is 13 –4 5 μg /m 3 . e D at a is to o un re lia bl e to be pu bl is he d. S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 273 HQs near or exceeding a value of 1 suggest that exposure levels in the population are near or exceeding existing exposure guidance values. BE values based upon risk specific doses at a risk level of 1× 10−4 from cancer risk assessments (i.e. BERSD) were used in the calculation of cancer risk estimates corresponding to population exposures at the P5, P25, P50, P75 and P95 percentile using the equation below: Cancer risk = ([biomarker] / BERSD) x 10−4 (2) BERSD values provide an estimate of the steady-state concentrations in blood or urine that would result from chronic exposure, over a life- time, at the risk specific doses. Linear extrapolation was assumed in the calculation of cancer risk estimates. Cancer risks exceeding 1× 10−5 indicate that exposure levels may be exceeding the risk considered negligible by Health Canada (Health Canada, 2010a), and the substance involved should be considered as a priority for further evaluation. Large variation in the blood or urinary concentrations of chemicals can be expected over the course of a day (intra-individual) or between individuals for highly transient chemicals such as VOCs and those de- scribed as non-persistent in this study (e.g. fluoride has a half-life of urinary elimination of approximately 6 h) (Aylward et al., 2012, 2015; Gurusankar et al., 2017). Consequently, for these chemicals, the tails of the concentration distribution (i.e. P5 and P95) may not be indicative of long-term exposure levels but rather transitory periods of low or high exposures. An evaluation of the central tendency of the population (GM) is more relevant for these chemicals as it allows more meaningful interpretation of population exposures (Aylward et al., 2013). 3. Results Chemicals assessed using biomonitoring screening values based on non-cancer endpoints are shown in Table 1 (non-persistent chemicals), 2 (persistent chemicals) and 3 (volatile organic compounds). For each chemical, the tables present summary statistics from the CHMS for a relevant biomarker (parent chemical, metabolite or sum of metabo- lites), the exposure guidance value and the corresponding biomoni- toring screening value, and references. Cancer reference values for known carcinogens measured as part of the CHMS (e.g. oral cancer slope factors, inhalation unit risk) along with population statistics re- levant to the calculation of cancer risks are presented in Table 4. 3.1. Hazard quotients for non-cancer endpoints 3.1.1. Non-persistent chemicals The HQ values at the GM and P95 concentrations for non-persistent chemicals in the Canadian population are presented in Fig. 1. For this exercise, a chemical was defined as non-persistent when its elimination half-life is relatively short (e.g., less than a day for some chemicals excreted in urine, or somewhat longer as in the case of the blood bio- markers of acrylamide (i.e. concentration of acrylamide hemoglobin adducts limited by the rate of red blood cell turnover)). Of the 14 non- persistent chemicals assessed, only four had HQ values greater than one at P95, namely fluoride, inorganic arsenic, 3-PBA and acrylamide. The HQs for fluoride in 3–5 and 6–11 year olds, calculated using the age- specific BE value (Aylward et al., 2015), slightly exceeded 1 at the P95 (1.23 and 1.07, respectively, for the two age groups) but not at the GM. The P95 estimate for 3–5 year olds has been flagged for high variability and, as such, caution is required when using this data. No exceedances were observed in the older age groups. For inorganic arsenic, the cal- culated HQ for 3–79 year olds at the GM was near one (0.797) while the HQ at the P95 exceeded one (3.13). For 3-PBA, a common metabolite of various pyrethroid pesticides, two screening-level BE values have pre- viously been derived (Aylward et al., 2018). The tier 1 value of 1.7 μg/L in urine is highly conservative based on an assumption that all urinary 3-PBA is derived from an exposure to a pyrethroid pesticide with the most stringent exposure guidance value and the tier 2 value of 87 μg/L is less conservative but might be more realistic as it was derived based on a weighted relative exposure to different pyrethroid compounds (Aylward et al., 2018). For the tier 1 BE only, the HQ value exceeded 1 at the P95 (3.41, flagged for high variability) but not at the GM (0.25). Finally for acrylamide, which was assessed by comparing levels of two of its metabolites in blood, namely acrylamide haemoglobin adduct (AAVal) and glycidamide haemoglobin adduct (GAVal), HQs exceeded 1 for both biomarkers in smokers aged 3–79 years at the P95 (1.53 and 1.42, respectively for AAVal and GAVal). These exceedances were not seen in non-smokers for either biomarker. 3.1.2. Persistent chemicals The HQ for persistent chemicals is shown in Fig. 2. In this analysis, HQs for cadmium at both the GM and P95 increased with age and were higher in smokers than non-smokers. Age-dependent increases in cad- mium levels in the Canadian population have been noted previously for data from 2007 to 2009 and 2009–2011 of the CHMS (Garner and Levallois, 2016). For cadmium, non-smokers HQ values were below 1 while for smokers, HQ values exceeded 1 for all age groups at the GM (1.06–1.18) and P95 (1.65–3.18) with the exception of the GM for the youngest age group of 12–19 years included for these chemicals (0.35). The GM estimate for the aged group 12–19 years and the P95 estimate for the age groups 40–59 years are flagged for high variability and, as such, caution is required when using this data. For PFOA, HQs for all age groups were above 1 at the GM (1.05–1.40) and P95 (2.05–3.20). For PFOS, all HQs were above 1 at the GM (1.24–1.88), except the HQ for the youngest age group of 12–19 years (0.92). All HQs at the P95 (2.20–4.20) were above 1, with HQs for age groups 20–39 years and 60–79 years flagged for high variability. 3.1.3. Volatile organic compounds The HQ values at the GM and P95 for VOCs in the Canadian population are presented in Fig. 3. All eight of the VOCs screened in this study had an HQ value below 1at both the GM and P95 concentration with the exception of benzene in smokers. For this chemical, the HQ value at the GM for smokers approached 1 (0.93), and exceeded 1 at the P95 (2.80). 3.2. Cancer risks The cancer risks for various percentiles of concentration in the Canadian general population (P5, P25, P50, P75 and P95) for bio- markers of acrylamide, inorganic arsenic and benzene are presented in Fig. 4. Most of the cancer risks calculated for these compounds were above the range of 10−5 to 10−6 considered to be essentially negligible risk (Health Canada, 2010a). Cancer risks calculated at different con- centration percentiles for the acrylamide biomarker GAVal in non- smokers were close to 10−3 (ranging from 5.12×10−4 at P5, flagged with high variability, to 2.25×10−3 at P95). Cancer risks in smokers were higher (ranging from 7.99× 10−4 at P5 to 5.12×10−3 at P95). For inorganic arsenic, cancer risk estimates were above the negligible risk range at all percentiles of the population assessed (ranging from 1.4×10−4 at P5, flagged for high variability to 1.4× 10−3 at P95). Two BERSD were used for benzene corresponding to the lower bound and the upper bound of the cancer exposure guidance value range de- rived by the US EPA. For benzene in non-smokers, all of the cancer risks are above the range of negligible risks with the exception of the P25 (6.36×10−6) when evaluated with the BERSD at upper bound which is the less conservative value. Caution is required when interpreting the cancer risks for benzene in non-smokers calculated at the P25, P50 and P75 due to high variability in the biomonitoring data. For benzene in smokers, cancer risks exceeded the negligible range when evaluated with the upper bound BERSD (ranging from 1.42×10−5 at P5 and 2.06×10−4 at P95) and with the lower bound BERSD (ranging from 4.97×10−5 at P5 to 7.20×10−4 at P95). Caution is required when interpreting the cancer risks for benzene in smokers calculated at the P5 due to high variability in the biomonitoring data. S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 274 4. Discussion 4.1. Screening of biomonitoring data This study analyzed CHMS biomonitoring data from various cycles in a health risk-based context building on the work of St-Amand et al. (2014). The current study continues the risk screening using more re- cent biomonitoring data and updated biomonitoring screening values. For non-cancer endpoints, 17 of the 25 chemicals analyzed had HQs of less than 1 both at GM and P95 concentrations suggesting that exposure of the general population to these chemicals is occurring at levels below the current exposure guidance values. Specifically, the GM (or P95 when no GM is available) concentrations for eleven of these chemicals were 10–100 000 times lower than their respective BE values (HQs between 0.1 and 0.00001 for molybdenum, thallium, cyfluthrin, deltamethrin, chlorpyrifos, 2,4-D, BPA, bromoform, toluene, styrene, and tetrachloroethylene) and the HQs at the GM (or P95 when the GM is not available) for the other six chemicals fell between 1 and 0.1 (selenium, silver, triclosan, chloroform, xylenes and ethylbenzene). HQs exceeded 1 at the GM and/or P95 concentrations for eight Fig. 1. Non-persistent environmental chemicals: Hazard quotients calculated with existing biomonitoring screening values and biomonitoring data from the Canadian Health Measures Survey for biomarkers of exposure for metals and trace elements (arsenic, fluoride, molybdenum, thallium), pesticides and environmental phenols in urine and for metals and trace elements (selenium, silver) and acrylamide in whole blood measured in the general Canadian population from 2009 to 2011 or 2014–2015. Abbreviations: +: HQ is to be used with caution as coefficient of variation is between 16.6% and 33.3%, 2,4-D: 2,4-Dichlorophenoxyacetic acid, 3- PBA: 3-Phenoxybenzoic acid, AAVal: Acrylamide hemoglobin valine terminal adducts, BPA: Bisphenol A, GAVal: Glycidamide hemoglobin valine terminal adducts, GM: Geometric mean, P95: 95th Percentile. Fig. 2. Persistent environmental chemicals: Hazard quotients calculated with existing bio- monitoring screening values and biomonitoring data from the Canadian Health Measures Survey for biomoarkers of exposure for cadmium in whole blood and perfluoroalkyl substances in plasma measured in the general Canadian po- pulation from 2009 to 2011 or 2014–2015. Abbreviations: +: HQ is to be used with caution as coefficient of variation is between 16.6% and 33.3%, GM: Geometric mean, PFOA: Perfluorooctanoic acid, PFOS: Perfluorooctane sulfonate, P95: 95th Percentile. S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 275 Fig. 3. Volatile organic compounds (VOCs): Hazard quotients calculated with existing biomonitoring equivalents and biomonitoring data from the Canadian Health Measures Survey biomarkers of exposure for VOCs in whole blood measured in the general Canadian population aged 12–79 years from 2012 to 2013 or 2014–2015. Abbreviations: +: HQ is to be used with caution as coefficient of variation is between 16.6% and 33.3%, GM: Geometric mean, P95: 95th Percentile. Fig. 4. Cancer risk for biomarkers of exposure for benzene and acrylamide (GAVal) in whole blood and urinary inorganic arsenic (sum of iAs, MMA and DMA) from the Canadian Health Measures Survey based on cancer exposure gui- dance values from Health Canada and U.S. EPA. BERSD used for benzene correspond to the lower bound (BERSD L) and the upper bound (BERSD U) of the cancer exposure guidance value range derived by the U.S. EPA. Medians are re- presented by the horizontal lines; boxes extend to the 25th and 75th percentiles, and whiskers extend to the 5th and 95th percentiles. Abbreviations: +: HQ is to be used with caution as coefficient of variation is between 16.6% and 33.3%, BERSD: Biomonitoring equivalent at risk specific dose, BERSD L: BERSD at lower bound, BERSD U: BERSD at upper bound, DMA: Dimethylarsinic acid, iAs: inorganic arsenic, MMA: Monomethylarsonic acid. S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 276 chemicals, namely fluoride, inorganic arsenic, 3-PBA, PFOA, and PFOS in the general population and acrylamide, cadmium, and benzene in smokers. These results indicate that exposure to these substances in the general and/or smoking Canadian population could be exceeding their respective exposure guidance values. In this study, cancer risks for benzene, acrylamide and inorganic arsenic in the general population fell above the range defined as essentially negligible (10−5-10−6) (Health Canada, 2010a). BE values are applied with an assumption of chronic exposure, however for biomarkers with short half-life such as fluoride, large variations in concentrations can be expected within an individual over the course of a day. Consequently, high exposures represented by the P95 are not necessarily indicative of continuous exposure for non-per- sistent chemicals, particularly when measured in spot urine samples. Rather, for non-persistent chemicals, the upper bound of exposure may be more reflective of a transient peak of exposure and the central ten- dency (GM or P50) is more informative of long term exposure (Aylward et al., 2012; Gurusankar et al., 2017). In this study, this is relevant for fluoride, inorganic arsenic, 3-PBA and benzene for which biomarkers are rapidly eliminated and HQs at the GM are under 1. However, as the size of the sample in this analysis is large, it may be interesting to ex- plore whether the P95 may actually be reflective of high level exposures to chemicals with short-elimination half-lives. Indeed, an examination of the CHMS biomonitoring data for short-lived chemicals demonstrates consistency of estimates across cycles at the tail of the population ex- posure, suggesting potential validity of use of the upper percentile es- timates for short-lived chemicals in large population studies. For ex- ample, P95 concentrations of urinary BPA in cycles 1, 2, 3 and 4 are 6.9 μg/L, 6.7 μg/L, 6.6 μg/L and 6.0 μg/L, respectively. For substances with biomarkers having a longer half-life such as acrylamide, cadmium and perfluoroalkyl substances (PFOA and PFOS) both HQs at the GM and P95 are informative of population exposure because their blood or urine levels are more likely to remain constant over the course of days or weeks. Results from the 2014–2015 data are consistent with the previous assessment of the same chemicals using data from 2007 to 2009 and 2009–2011. For example, St-Amand et al. (2014) identified ex- ceedances of cadmium and inorganic arsenic concentrations over their respective biomonitoring screening values. The current results can also be compared with other national biomonitoring data screening studies such as those conducted on data from the U.S. National Health and Nutrition Examination Survey (NHANES). An interpretation of NHANES data from 2013 using BE values resulted in similar findings to those of St-Amand et al. (2014) and the present work. For example, HQs for inorganic arsenic exceeded 1 at the P95 concentration for the U.S. general population. HQs for acrylamide, cadmium and benzene also exceeded 1 at the P95 for smokers based on NHANES. Similar to our findings on cancer risks based on Canadian data, cancer risks in the U.S. population exceeded the 1× 10−5cancer risk level for benzene and acrylamide in both smokers and non-smokers, and inorganic arsenic in the general population (Aylward et al., 2013). For the chemicals trichloroethylene, bromodichloromethane and dibromochloromethane measured in 2014–2015 of the CHMS, GM and P95 calculations were not possible due to low detection (i.e., more than 95% of measurements were below the LOD). Therefore, while BE values are available for these chemicals, it was not possible to calculate HQ values. Nevertheless, BE values for these chemicals are higher than their respective LODs. The low detection of these chemicals combined with the LODs being lower than the respective BE values indicates that exposures in the general population are below the current level of concern. Finally, HQs greater than 1 at the GM or P95 for acrylamide, ben- zene, cadmium, fluoride, inorganic arsenic, 3-PBA, PFOA and PFOS, as well as cancer risks exceeding the range defined as essentially negligible (10−5-10−6) for benzene, acrylamide and inorganic arsenic suggest that these chemicals should remain as priorities for continued biomonitoring. For these chemicals, this screening exercise also pro- vides evidence to support the findings of past risk assessments resulting in a number of risk management and mitigation measures implemented by Health Canada. Risk assessments under the Canadian Environmental Protection Act, 1999 (CEPA, 1999) have resulted in the listing of ac- rylamide, benzene, cadmium (inorganic), fluoride, inorganic arsenic, PFOA and PFOS on Schedule 1, List of Toxic Substances (Canada, 1999; Canada, 2018). The Act allows the federal government to control the importation, manufacture, distribution, and use of these chemicals in Canada. Accordingly, Health Canada has carried out a number of recent activities for these substances to reduce population exposure including proposed updates to the maximum levels of arsenic in apple juice and water in sealed containers, new guidelines for PFOS and PFOA in drinking water, and a health risk assessment of dietary cadmium (ECCC, 2016; Health Canada, 1996, 2017a, 2017b, 2017e, 2017d, 2018a, 2018b, 2018c). In addition, acrylamide, cadmium and inorganic arsenic have also recently been identified for further scoping to find new potential sources of exposure to assess and manage on the basis of previous screening activities with CHMS data including those by St- Amand et al. (2014) (ECCC and HC, 2019). Under the Pest Control Products Act (PCPA) (Canada, 2006b), various pyrethroid pesticides, for which 3-PBA is a metabolite, have been evaluated including re- evaluations of lambda-cyhalothrin and cypermethrin (Health Canada, 2017f, 2018d). A number of these mitigation measures have been im- plemented since the release of latest cycle of CHMS data (2014–2015) that have been used in the current analyses. These measures along with future studies and assessments and the ongoing collection of human biomonitoring data as part of the CHMS will help contribute to a better understanding of the potential health risks posed by these chemicals in the Canadian population. 4.2. Limitations of BE values and alternate screening approaches Some limitations of this study are inherent to the use of BE values and other biomonitoring screening values. A number of these limita- tions, including the interim approach behind the derivation of these values, their population rather than individual purpose, as well as the lack of tools for the assessment of multi-pollutant exposures, are de- scribed elsewhere (Aylward et al., 2013; Kirman et al., 2012; St-Amand et al., 2014). An important limitation to this study is the absence of biomonitoring screening values for a number of chemicals measured in the CHMS including chlorophenols and neonicotinoid pesticides. This underpins the fact that our ability to monitor chemicals in humans exceeds our ability to interpret these data in a health risk context and that other ways to interpret risks posed by chemicals are required. Screening values can be challenging to derive due to limited experi- mental data or pharmacological models and the lack of a clear under- standing of the mode of action for many environmental chemicals. Nevertheless, a number of BE values are currently being developed by Health Canada including for parabens and malathion. Another limitation which has to be considered when interpreting the results is the fact that confidence in BE values can vary from one chemical to another. This confidence is based on biomarker specificity or relation of this biomarker to dose metrics associated with the end- points of interest and the robustness of pharmacokinetics models. For example, confidence based on biomarker specificity is high for the AAVal and GAVal BE values (Hays and Aylward, 2008). In contrast, the confidence is only low to medium for the cyfluthrin BE as the biomarker is not directly related to the mode of action of this substance (Hays et al., 2009). Low biomarker specificity can lead to overestimation of the risks. For example, caution is required when interpreting data for biomarkers of inorganic arsenic and pyrethroid pesticides. In the case of inorganic arsenic, the concentration of DMA, the most detected urinary arsenic metabolite, drives the sum of the concentrations of inorganic- derived arsenic species calculated for this analysis. However, levels of urinary DMA has also been associated with direct consumption of DMA S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 277 contained in foods such as rice and seafood, and DMA derived from the metabolism of arsenolipids and arsenosugars contained in seafood (Hays et al., 2010). Consequently, the exposure to inorganic-derived arsenic as calculated in this study might be overestimated. In the case of 3-PBA, exceedances of the BE value are only observed when using the tier 1 BE value, which is based on a conservative assumption that all urinary 3-PBA arises from exposure to the most potent pyrethroid compound. A tier 2 BE value for 3-PBA is available which takes into account the estimated proportional contributions of several pyrethroids to an exposure (Aylward et al., 2018). When the tier 2 value is used, the HQ values fall below 0.1 (Fig. 1). Confidence in the pharmacokinetic models used in the development of a BE can be robust as for mo- lybdenum, given that a method based on data from a study using sev- eral different daily doses of molybdenum and conducted in a controlled metabolic research station is used to convert a daily dose of mo- lybdenum to urinary excretion rate, or less robust as for deltamethrin for which a urinary BE is derived based on a dataset from a study using only a single oral dose (Aylward et al., 2011; Hays et al., 2016). Not only are the biomarkers and pharmacokinetic models important for confidence in a BE, but also are the exposure guidance value that were used to derive the BE. These values and associated confidence can also differ greatly between regulatory agencies due to differences in studies used, points of departure and uncertainty factors. Consequently, each BE will be only as strong as the exposure guidance value on which it is based. For example, several BE values exist for benzene including the value of 0.15 μg/L used in this study based on a US EPA assessment and a less conservative value of 0.29 μg/L based on a California Reference Exposure Level. The major difference was the use of two different human studies with different endpoints of interest (Hays et al., 2012). Although BE values are used here only to identify chemicals that may require further evaluation, recent risk assessments have used biomonitoring screening values alongside biomonitoring data from the CHMS to evaluate risks to human health (Health Canada, 2018e; Zidek et al., 2017). Such uses exist for several chemicals including four as- sessed in this study namely selenium, thallium, molybdenum and silver (Health Canada, 2016). Therefore, the increasingly broad use of BE values demonstrates a need to continue to improve the accuracy and relevance of these values based on available exposure guidance values and pharmacokinetic data. More recently, Phillips et al. (2014) pro- posed a stochastically based Monte Carlo approach for calculating a distribution of BE values for a chemical taking into account the varia- bility in physiology and pharmacokinetics at different exposure levels. A distribution of BE values rather than a single BE may be a more useful tool to more appropriately evaluate both the central tendency and the tail (e.g. 95th percentile) of a population distribution of biomonitoring data, especially for short-lived chemicals where higher biomonitoring concentrations may reflect elevated acute or chronic exposures or simply the timing of exposure with respect to sample collection. Chemicals assessed here for cancer risk are classified by the International Agency for Research on Cancer (IARC) as group 1 (car- cinogenic to humans, arsenic and benzene) or group 2A (probably carcinogenic to humans, acrylamide). Nevertheless, it is important to consider some uncertainties associated with cancer risk estimation using screening values derived based on cancer slope factors. Firstly, the slope factors or unit risks associated with lifetime exposure to a chemical may themselves vary between different agencies (e.g. US EPA, Health Canada). Further, the cancer slope factors or unit risks have been arrived at using linear models in conjunction with a low-dose extrapolation approach. Whereas this is an accepted approach for the estimation of cancer risks, it is plausible that the uncertainties asso- ciated with the shape of dose response or mode of action at low-doses may potentially affect results including possible overestimation or un- derestimation of the risks. Considering the uncertainty associated with low-dose cancer risk extrapolation, a margin of exposure approach that uses a point of departure such as the benchmark dose (BMD) associated with a low, measurable (e.g. 10% increase over background cancer incidence) response in an experimental or epidemiological study is gaining significance in the assessment of cancer risks for genotoxic, non-threshold carcinogens. 4.3. Future work This type of analysis provides useful evidence for risk assessors and risk managers for further assessment and/or follow-up related to the assessment and management of chemical exposures. In this sense, continued screening of CHMS data when new biomonitoring screening values and/or new biomonitoring data are available is required. Ongoing revisions to environmental and dietary questionnaires in CHMS to better capture exposure sources will augment follow-up ac- tivities including re-evaluation and mitigation of exposures. It would also be interesting to analyse the risk posed by combined exposure of chemicals with chemical-specific biomonitoring screening values. For example, the Hazard Index is an approach assuming dose addition in tissues and used in an assessment of VOC data from NHANES by Aylward et al. (2013) and Kirman et al. (2012). A similar exercise can be done with CHMS chemicals that have known interac- tions and shared end-points; and this could provide further information to support regulatory evaluation. Benzene is an example of a chemical for which this exercise may be of use as it has HQs above 1 and is known to interact with other organic volatile compounds such as to- luene, xylene and ethylbenzene (Haddad et al., 1999). 5. Conclusion This study provides a unique assessment of chemical exposures in a health risk based context at the population level in Canada using the most recent CHMS biomonitoring data. It is a rapid screening approach to identify environmental chemicals to which the general population may be exposed at levels near or exceeding existing risk assessment- based exposure guidance values. This presents an additional layer of exposure-based prioritization building upon the original prioritization process carried out when the chemicals were initially selected for in- clusion in the CHMS. Consequently the identified chemicals can be seen as priorities for advanced examination including investigation of sources and pathways of exposure. This may subsequently lead to targeted ac- tions to eliminate and mitigate exposure sources and reduce associated health risks. As many regulatory actions are underway or have already been implemented for these chemicals, this study also provides evidence to support these actions. The ongoing collection and screening of human biomonitoring data from the CHMS will help track exposures to these priority chemicals in the Canadian population and support the ongoing work to mitigate exposures and reduce health risks. Conflicts of interest None to declare. Acknowledgement The authors would like to acknowledge Claude Viau, Cheryl Khoury, Jeff Willey, Andy Nong, Michelle Gagné, Kristin Macey and Scott Blechinger for their review or/and valuable insights during pre- paration of this work. The Canadian Health Measures Survey biomo- nitoring component is funded by the Chemicals Managment Plan, a Government of Canada initiative. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ijheh.2019.07.009. S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 278 https://doi.org/10.1016/j.ijheh.2019.07.009 https://doi.org/10.1016/j.ijheh.2019.07.009 References Angerer, J., Aylward, L.L., Hays, S.M., Heinzow, B., Wilhelm, M., 2011. Human biomo- nitoring assessment values: approaches and data requirements. Int. J. Hyg Environ. Health 214 (5), 348–360. Apel, P., Angerer, J., Wilhelm, M., Kolossa-Gehring, M., 2017. New HBM values for emerging substances, inventory of reference and HBM values in force, and working principles of the German Human Biomonitoring Commission. Int. J. Hyg Environ. Health 220 (2), 152–166. Arnold, S.M., Morriss, A., Velovitch, J., Juberg, D., Burns, C.J., Bartels, M., Aggarwal, M., Poet, T., Hays, S., Price, P., 2015. Derivation of human Biomonitoring Guidance Values for chlorpyrifos using a physiologically based pharmacokinetic and pharma- codynamic model of cholinesterase inhibition. Regul. Toxicol. Pharmacol. 71 (2), 235–243. Aylward, L.L., Bachler, G., Von Goetz, N., Poddalgoda, D., Hays, S.M., Nong, A., 2016. Biomonitoring Equivalents for interpretation of silver biomonitoring data in a risk assessment context. Int. J. Hyg Environ. Health 219 (6), 521–526. Aylward, L.L., Hays, S.M., 2015. Interpreting biomonitoring data for 2, 4-di- chlorophenoxyacetic acid: update to Biomonitoring Equivalents and population biomonitoring data. Regul. Toxicol. Pharmacol. 73 (3), 765–769. Aylward, L.L., Hays, S.M., Vezina, A., Deveau, M., St-Amand, A., Nong, A., 2015. Biomonitoring Equivalents for interpretation of urinary fluoride. Regul. Toxicol. Pharmacol. 72 (1), 158–167. Aylward, L.L., Irwin, K., St-Amand, A., Nong, A., Hays, S.M., 2018. Screening-level Biomonitoring Equivalents for tiered interpretation of urinary 3-phenoxybenzoic acid (3-PBA) in a risk assessment context. Regul. Toxicol. Pharmacol. 92, 29–38. Aylward, L.L., Kirman, C.R., Adgate, J.L., McKenzie, L.M., Hays, S.M., 2012. Interpreting variability in population biomonitoring data: role of elimination kinetics. J. Expo. Sci. Environ. Epidemiol. 22 (4), 398. Aylward, L.L., Kirman, C.R., Blount, B.C., Hays, S.M., 2010. Chemical-specific screening criteria for interpretation of biomonitoring data for volatile organic compounds (VOCs)–Application of steady-state PBPK model solutions. Regul. Toxicol. Pharmacol. 58 (1), 33–44. Aylward, L.L., Kirman, C.R., Schoeny, R., Portier, C.J., Hays, S.M., 2013. Evaluation of biomonitoring data from the CDC National Exposure Report in a risk assessment context: perspectives across chemicals. Environ. Health Perspect. 121 (3), 287–294. Aylward, L.L., Krishnan, K., Kirman, C.R., Nong, A., Hays, S.M., 2011. Biomonitoring equivalents for deltamethrin. Regul. Toxicol. Pharmacol. 60 (2), 189–199. Aylward, L.L., LaKind, J.S., Hays, S.M., 2008. Biomonitoring Equivalents (BE) dossier for trihalomethanes. Regul. Toxicol. Pharmacol. 51 (3), S68–S77. Canada, 1999. Canadian Environmental Protection Act, 1999 (CEPA 1999). SC 1999, c. 33. (accessed 18.02.19). https://laws-lois.justice.gc.ca/eng/acts/C-15.31/index. html. Canada, 2006a. Chemicals Management Plan. Minister of health, Ottawa, ON, Canada (accessed 19.09.18). https://www.canada.ca/en/health-canada/services/chemical- substances/chemicals-management-plan.html. Canada, 2006b. Pest Control Products Act. SC 2002, c. 28. (accessed 20.02.19). https:// laws-lois.justice.gc.ca/eng/AnnualStatutes/2002_28/. Canada, 2018. Toxic Substances List: Schedule 1. Minister of health, Ottawa, ON, Canada (accessed 18.02.19). https://www.canada.ca/en/environment-climate-change/ services/canadian-environmental-protection-act-registry/substances-list/toxic/ schedule-1.html. Clewell, H.J., Tan, Y.M., Campbell, J.L., Andersen, M.E., 2008. Quantitative interpreta- tion of human biomonitoring data. Toxicol. Appl. Pharmacol. 231 (1), 122–133. ECCC (Environment and Climate Change Canada), 2016. Chemicals Management Plan, Risk Management Actions to Address Risks from Substances Concluded to Be Harmful to the Environment And/or Human Health as Per Section 64 of the Canadian Environmental Protection Act, 1999. Minister of health, Ottawa, ON, Canada (ac- cessed 19.02.19). http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n= B68C1BAF-1. ECCC and HC (Environment and Climate Change Canada and Health Canada), 2016. Assessment Report Triclosan Chemical Abstracts Service Registry Number 3380-34-5. Ottawa, ON, Canada. (accessed 19.09.18). http://www.ec.gc.ca/ese-ees/default. asp?lang=En&n=65584A12-1. ECCC and HC (Environment and Climate Change Canada and Health Canada), 2019. Identification of Risk Assessment Priorities (IRAP): Result of the 2017-18 Review. Ottawa, ON, Canada. (accessed 19.02.19). https://www.canada.ca/en/ environment-climate-change/services/evaluating-existing-substances/identification- risk-assessment-priorities-irap-2017-18.html#toc7. Eykelbosh, A., Werry, K., Kosatsky, T., 2018. Leveraging the Canadian health measures survey for environmental health research. Environ. Int. 119, 536–543. Garner, R., Levallois, P., 2016. Cadmium levels and sources of exposure among Canadian adults. Health Rep. 27 (2), 10–18. Gurusankar, R., Yenugadhati, N., Krishnan, K., Hays, S., Haines, D., Zidek, A., Kuchta, S., Kinniburgh, D., Gabos, S., Mattison, D., Krewski, D., 2017. The role of human bio- logical monitoring in health risk assessment. Int. J. Risk Assess. Manag. 20 (1–3), 136–197. Haddad, S., Tardif, R., Charest-Tardif, G., Krishnan, K., 1999. Physiological modeling of the toxicokinetic interactions in a quaternary mixture of aromatic hydrocarbons. Toxicol. Appl. Pharmacol. 161 (3), 249–257. Haines, D.A., Saravanabhavan, G., Werry, K., Khoury, C., 2017. An overview of human biomonitoring of environmental chemicals in the Canadian Health Measures Survey: 2007–2019. Int. J. Hyg Environ. Health 220 (2), 13–28. Hays, S.M., Aylward, L.L., 2008. Biomonitoring Equivalents (BE) dossier for acrylamide (AA) (CAS No. 79-06-1). Regul. Toxicol. Pharmacol. 51 (3), S57–S67. Hays, S.M., Aylward, L.L., 2009. Using biomonitoring equivalents to interpret human biomonitoring data in a public health risk context. J. Appl. Toxicol. 29 (4), 275–288. Hays, S.M., Aylward, L.L., Gagné, M., Krishnan, K., 2009. Derivation of biomonitoring equivalents for cyfluthrin. Regul. Toxicol. Pharmacol. 55 (3), 268–275. Hays, S.M., Aylward, L.L., Gagné, M., Nong, A., Krishnan, K., 2010. Biomonitoring equivalents for inorganic arsenic. Regul. Toxicol. Pharmacol. 58 (1), 1–9. Hays, S.M., Aylward, L.L., LaKind, J.S., Bartels, M.J., Barton, H.A., Boogaard, P.J., Brunk, C., DiZio, S., Dourson, M., Goldstein, D.A., Lipscomb, J., 2008a. Guidelines for the derivation of biomonitoring equivalents: report from the biomonitoring equivalents expert workshop. Regul. Toxicol. Pharmacol. 51 (3), S4–S15. Hays, S.M., Becker, R.A., Leung, H.W., Aylward, L.L., Pyatt, D.W., 2007. Biomonitoring equivalents: a screening approach for interpreting biomonitoring results from a public health risk perspective. Regul. Toxicol. Pharmacol. 47 (1), 96–109. Hays, S.M., Macey, K., Poddalgoda, D., Lu, M., Nong, A., Aylward, L.L., 2016. Biomonitoring equivalents for molybdenum. Regul. Toxicol. Pharmacol. 77, 223–229. Hays, S.M., Macey, K., Nong, A., Aylward, L.L., 2014. Biomonitoring equivalents for se- lenium. Regul. Toxicol. Pharmacol. 70 (1), 333–339. Hays, S.M., Nordberg, M., Yager, J.W., Aylward, L.L., 2008b. Biomonitoring equivalents (BE) dossier for cadmium (Cd)(CAS No. 7440-43-9). Regul. Toxicol. Pharmacol. 51 (3), S49–S56. Hays, S.M., Pyatt, D.W., Kirman, C.R., Aylward, L.L., 2012. Biomonitoring equivalents for benzene. Regul. Toxicol. Pharmacol. 62 (1), 62–73. Health Canada, 1996. CEPA Supporting Documentation: Health-Based Tolerable Daily Intakes/Concentrations and Tumorigenic Doses/Concentrations for Priority Substances. Minister of Health, Ottawa, ON, Canada. Health Canada, 2006. Guidelines for Canadian Drinking Water Quality: Guideline Technical Document – Arsenic. Minister of Health, Ottawa, ON, Canada. https:// www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines- canadian-drinking-water-quality-guideline-technical-document-arsenic.html, Accessed date: 27 January 2019. Health Canada, 2008. Health Risk Assessment of Bisphenol A from Food Packaging Applications. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/ health-canada/services/food-nutrition/food-safety/packaging-materials/bisphenol/ health-risk-assessment-bisphenol-food-packaging-applications.html, Accessed date: 27 January 2019. Health Canada, 2010a. Federal Contaminated Site Risk Assessment in Canada, Part I: 456 Guidance on Human Health Preliminary Quantitative Risk Assessment (PQRA), 457 Version 2.0. Minister of Health, Ottawa, ON, Canada. Health Canada, 2010b. Guidelines for Canadian Drinking Water Quality: Guideline Technical Document—Fluoride. Minister of Health, Ottawa, ON, Canada. https:// www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines- canadian-drinking-water-quality-guideline-technical-document-fluoride.html, Accessed date: 27 January 2019. Health Canada, 2010c. Report on Human Biomonitoring of Environmental Chemicals in Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/ health-canada/services/environmental-workplace-health/reports-publications/ environmental-contaminants/report-human-biomonitoring-environmental- chemicals-canada-health-canada-2010.html, Accessed date: 28 January 2019. Health Canada, 2011. Residential Indoor Air Quality Guideline: Toluene. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/ publications/healthy-living/residential-indoor-air-quality-guideline-toluene.html, Accessed date: 18 January 2019. Health Canada, 2012. Health Canada Revised Exposure Assessment of Acrylamide in Food. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/content/ dam/hc-sc/migration/hc-sc/fn-an/alt_formats/pdf/securit/chem-chim/food- aliment/acrylamide/rev-eval-exposure-exposition-eng.pdf, Accessed date: 6 March 2019. Health Canada, 2013. Second Report on Human Biomonitoring of Environmental Chemicals in Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada. ca/en/health-canada/services/environmental-workplace-health/reports- publications/environmental-contaminants/second-report-human-biomonitoring- environmental-chemicals-canada-health-canada-2013.html, Accessed date: 28 January 2019. Health Canada, 2014. Guidelines for Canadian Drinking Water Quality: Guideline Technical Document – Toluene, Ethylbenzene and the Xylenes. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/ publications/healthy-living/guidelines-canadian-drinking-water-quality-toluene- ethylbenzene-xylenes.html, Accessed date: 26 January 2019. Health Canada, 2015a. Proposed Re-evaluation Decision PRVD2015-07, Deltamethrin. Pest Management Regulatory Agency (PMRA) Health Canada. Minister of Health, Ottawa, ON, Canada. http://publications.gc.ca/collections/collection_2016/sc-hc/ H113-27-2015-7-eng.pdf, Accessed date: 18 January 2019. Health Canada, 2015b. Third Report on Human Biomonitoring of Environmental Chemicals in Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada. ca/en/health-canada/services/environmental-workplace-health/reports- publications/environmental-contaminants/third-report-human-biomonitoring- environmental-chemicals-canada.html, Accessed date: 28 January 2019. Health Canada, 2016. Science Approach Document Biomonitoring-Based Approach 2 for Barium-Containing Substances, Molybdenum-Containing Substances, Silver- Containing Substances, Thallium-Containing Substances, Inorganic Tin-Containing Substances. Minister of Health, Ottawa, ON, Canada. http://www.ec.gc.ca/ese-ees/ default.asp?lang=En&n=D335D89F-1#toc044 (14.02.2019). Health Canada, 2017a. Acrylamide and Food. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/ chemical-contaminants/food-processing-induced-chemicals/acrylamide/acrylamide- S. Faure, et al. International Journal of Hygiene and Environmental Health 223 (2020) 267–280 279 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref1 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref1 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref1 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref2 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref2 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref2 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref2 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref3 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref3 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref3 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref3 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref3 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref4 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref4 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref4 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref5 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref5 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref5 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref6 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref6 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref6 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref7 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref7 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref7 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref8 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref8 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref8 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref9 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref9 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref9 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref9 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref10 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref10 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref10 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref11 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref11 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref12 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref12 https://laws-lois.justice.gc.ca/eng/acts/C-15.31/index.html https://laws-lois.justice.gc.ca/eng/acts/C-15.31/index.html https://www.canada.ca/en/health-canada/services/chemical-substances/chemicals-management-plan.html https://www.canada.ca/en/health-canada/services/chemical-substances/chemicals-management-plan.html https://laws-lois.justice.gc.ca/eng/AnnualStatutes/2002_28/ https://laws-lois.justice.gc.ca/eng/AnnualStatutes/2002_28/ https://www.canada.ca/en/environment-climate-change/services/canadian-environmental-protection-act-registry/substances-list/toxic/schedule-1.html https://www.canada.ca/en/environment-climate-change/services/canadian-environmental-protection-act-registry/substances-list/toxic/schedule-1.html https://www.canada.ca/en/environment-climate-change/services/canadian-environmental-protection-act-registry/substances-list/toxic/schedule-1.html http://refhub.elsevier.com/S1438-4639(19)30462-6/sref17 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref17 http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=B68C1BAF-1 http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=B68C1BAF-1 http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=65584A12-1 http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=65584A12-1 https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/identification-risk-assessment-priorities-irap-2017-18.html#toc7 https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/identification-risk-assessment-priorities-irap-2017-18.html#toc7 https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/identification-risk-assessment-priorities-irap-2017-18.html#toc7 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref21 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref21 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref22 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref22 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref23 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref23 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref23 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref23 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref24 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref24 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref24 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref25 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref25 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref25 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref26 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref26 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref27 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref27 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref28 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref28 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref29 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref29 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref30 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref30 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref30 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref30 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref31 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref31 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref31 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref32 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref32 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref32 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref33 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref33 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref34 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref34 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref34 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref35 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref35 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref36 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref36 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref36 https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-arsenic.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-arsenic.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-arsenic.html https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/packaging-materials/bisphenol/health-risk-assessment-bisphenol-food-packaging-applications.html https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/packaging-materials/bisphenol/health-risk-assessment-bisphenol-food-packaging-applications.html https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/packaging-materials/bisphenol/health-risk-assessment-bisphenol-food-packaging-applications.html http://refhub.elsevier.com/S1438-4639(19)30462-6/sref39 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref39 http://refhub.elsevier.com/S1438-4639(19)30462-6/sref39 https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-fluoride.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-fluoride.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical-document-fluoride.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/report-human-biomonitoring-environmental-chemicals-canada-health-canada-2010.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/report-human-biomonitoring-environmental-chemicals-canada-health-canada-2010.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/report-human-biomonitoring-environmental-chemicals-canada-health-canada-2010.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/report-human-biomonitoring-environmental-chemicals-canada-health-canada-2010.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/residential-indoor-air-quality-guideline-toluene.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/residential-indoor-air-quality-guideline-toluene.html https://www.canada.ca/content/dam/hc-sc/migration/hc-sc/fn-an/alt_formats/pdf/securit/chem-chim/food-aliment/acrylamide/rev-eval-exposure-exposition-eng.pdf https://www.canada.ca/content/dam/hc-sc/migration/hc-sc/fn-an/alt_formats/pdf/securit/chem-chim/food-aliment/acrylamide/rev-eval-exposure-exposition-eng.pdf https://www.canada.ca/content/dam/hc-sc/migration/hc-sc/fn-an/alt_formats/pdf/securit/chem-chim/food-aliment/acrylamide/rev-eval-exposure-exposition-eng.pdf https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/second-report-human-biomonitoring-environmental-chemicals-canada-health-canada-2013.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/second-report-human-biomonitoring-environmental-chemicals-canada-health-canada-2013.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/second-report-human-biomonitoring-environmental-chemicals-canada-health-canada-2013.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/second-report-human-biomonitoring-environmental-chemicals-canada-health-canada-2013.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-toluene-ethylbenzene-xylenes.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-toluene-ethylbenzene-xylenes.html https://www.canada.ca/en/health-canada/services/publications/healthy-living/guidelines-canadian-drinking-water-quality-toluene-ethylbenzene-xylenes.html http://publications.gc.ca/collections/collection_2016/sc-hc/H113-27-2015-7-eng.pdf http://publications.gc.ca/collections/collection_2016/sc-hc/H113-27-2015-7-eng.pdf https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/third-report-human-biomonitoring-environmental-chemicals-canada.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/third-report-human-biomonitoring-environmental-chemicals-canada.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/third-report-human-biomonitoring-environmental-chemicals-canada.html https://www.canada.ca/en/health-canada/services/environmental-workplace-health/reports-publications/environmental-contaminants/third-report-human-biomonitoring-environmental-chemicals-canada.html http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=D335D89F-1#toc044 http://www.ec.gc.ca/ese-ees/default.asp?lang=En&n=D335D89F-1#toc044 https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/chemical-contaminants/food-processing-induced-chemicals/acrylamide/acrylamide-food-food-safety.html https://www.canada.ca/en/health-canada/services/food-nutrition/food-safety/chemical-contaminants/food-processing-induced-chemicals/acrylamide/acrylamide-food-food-safety.html food-food-safety.html, Accessed date: 22 February 2019. Health Canada, 2017b. Arsenic. Minister of Health, Ottawa, ON, Canada. https://www. canada.ca/en/health-canada/services/food-nutrition/food-safety/chemical- contaminants/environmental-contaminants/arsenic.html, Accessed date: 19 February 2019. Health Canada, 2017c. Fourth Report on Human Biomonitoring of Environmental Chemicals in Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada. ca/en/health-canada/services/environmental-workplace-health/reports- publications/environmental-contaminants/fourth-report-human-biomonitoring- environmental-chemicals-canada.html, Accessed date: 28 January 2019. Health Canada, 2017d. Guidelines for Canadian Drinking Water Quality - Summary Table. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/ services/environmental-workplace-health/reports-publications/water-quality/ guidelines-canadian-drinking-water-quality-summary-table.html, Accessed date: 20 February 2019. Health Canada, 2017e. Proposal to Update the Maximum Levels for Arsenic in Apple Juice and Water in Sealed Containers in the List of Contaminants and Other Adulterating Substances in Foods. Minister of Health, Ottawa, ON, Canada. https://www.canada. ca/en/health-canada/services/food-nutrition/public-involvement-partnerships/ proposal-update-maximum-levels-arsenic-apple-juice-water-sealed-containers/ document.html, Accessed date: 19 February 2019. Health Canada, 2017f. Proposed Re-evaluation Decision PRVD2017-03, Lambda- Cyhalothrin. Pest Management Regulatory Agency (PMRA) Health Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/ consumer-product-safety/pesticides-pest-management/public/consultations/ proposed-re-evaluation-decisions/2017/lambda-cyhalothrin/document.html, Accessed date: 21 February 2019. Health Canada, 2017g. Registration Decision RD2017-01, Beta-Cyfluthrin. Pest Management Regulatory Agency (PMRA) Health Canada. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/consumer- product-safety/reports-publications/pesticides-pest-management/decisions-updates/ registration-decision/2017/beta-cyfluthrin-rd2017-01.html, Accessed date: 18 January 2019. Health Canada, 2018a. Guideline for Canadian Drinking Water Quality : Guideline Technical Document- Perfluorooctane Sulfonate (PFOS). Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/publications/ healthy-living/guidelines-canadian-drinking-water-quality-guideline-technical- document-perfluorooctane-sulfonate/document.html, Accessed date: 19 February 2019. Health Canada, 2018b. Guideline for Canadian Drinking Water Quality: Guideline Technical Document- Perfluorooctanoic Acid (PFOA). Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/publications/ healthy-living/guidelines-canadian-drinking-water-quality-technical-document- perfluorooctanoic-acid.html, Accessed date: 19 February 2019. Health Canada, 2018c. Health Risk Assessment of Dietary Exposure to Cadmium. Minister of Health, Ottawa, ON, Canada (Available upon request). Health Canada, 2018d. Re-evaluation Decision RVD2018-22, Cypermethrin and its Associated End-Use Products. Pest Management Regulatory Agency Health Canada, Ottawa, ON, Canada Minister of Health. https://www.canada.ca/en/health-canada/ services/consumer-product-safety/reports-publications/pesticides-pest- management/decisions-updates/reevaluation-decision/2018/cypermethrin.html, Accessed date: 20 February 2019. Health Canada, 2018e. Uses of Human Biomonitoring Data in Risk Assessment. Minister of Health, Ottawa, ON, Canada. https://www.canada.ca/en/health-canada/services/ chemical-substances/fact-sheets/human-biomonitoring-data-risk-assessment.html, Accessed date: 26 January 2019. Institute of Medicine (IOM), 2000. Dietary Reference Intakes for Vitamin C, Vitamin E, Selenium, and Carotenoids. A Report of the Panel on Dietary Antioxidants and Related Compounds, Subcommittees on Upper Reference Levels of Nutrients and Interpretation and Uses of Dietary Reference Intakes, and the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. National Academy of Sciences, National Academy Press, Washington, DC. JECFA (Joint, F. A. O., WHO Expert Committee on Food Additives, & World Health Organization), 2011. Safety Evaluation of Certain Contaminants in Food: Prepared by the Seventy-Second Meeting of the Joint FAO/WHO Expert Committee on Food Additives (JECFA). https://apps.who.int/iris/bitstream/handle/10665/44520/ 9789241660631_eng.pdf;jsessionid=E27458D4A5C8BA9929E7FCFF9C172D64? sequence=1, Accessed date: 14 March 2019. Kirman, C.R., Aylward, L.L., Blount, B.C., Pyatt, D.W., Hays, S.M., 2012. Evaluation of NHANES biomonitoring data for volatile organic chemicals in blood: application of chemical-specific screening criteria. J. Expo. Sci. Environ. Epidemiol. 22 (1), 24. Krishnan, K., Gagné, M., Nong, A., Aylward, L.L., Hays, S.M., 2010a. Biomonitoring equivalents for bisphenol A (BPA). Regul. Toxicol. Pharmacol. 58 (1), 18–24. Krishnan, K., Gagné, M., Nong, A., Aylward, L.L., Hays, S.M., 2010b. Biomonitoring equivalents for triclosan. Regul. Toxicol. Pharmacol. 58 (1), 10–17. LaKind, J.S., Aylward, L.L., Brunk, C., DiZio, S., Dourson, M., Goldstein, D.A., Kilpatrick, M.E., Krewski, D., Bartels, M.J., Barton, H.A., Boogaard, P.J., 2008. Guidelines for the communication of biomonitoring equivalents: report from the biomonitoring equivalents expert workshop. Regul. Toxicol. Pharmacol. 51 (3), S16–S26. Phillips, M.B., Sobus, J.R., George, B.J., Isaacs, K., Conolly, R., Tan, Y.M., 2014. A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization. Regul. Toxicol. Pharmacol. 69 (3), 434–442. Sexton, K., Needham, L., L, L., Pirkle, J., 2004. Human Biomonitoring of Environmental Chemicals: measuring chemicals in human tissues is the "gold standard" for assessing people's exposure to pollution. Am. Sci. 92 (1), 38–45. Schulz, C., Wilhelm, M., Heudorf, U., Kolossa-Gehring, M., 2011. Update of the reference and HBM values derived by the German human biomonitoring commission. Int. J. Hyg Environ. Health 215 (1), 26–35. St-Amand, A., Werry, K., Aylward, L.L., Hays, S.M., Nong, A., 2014. Screening of popu- lation level biomonitoring data from the Canadian Health Measures Survey in a risk- based context. Toxicol. Lett. 231 (2), 126–134. SRNT (Subcommittee on Biochemical Verification), 2002. Biochemical verification of tobacco use and cessation. Nicotine Tob. Res. 4, 149–159. Steckling, N., Gotti, A., Bose-O’Reilly, S., Chapizanis, D., Costopoulou, D., De Vocht, F., Garí, M., Grimalt, J.O., Heath, E., Hiscock, R., Jagodic, M., Karakitsios, S.P., Kedikoglou, K., Kosjek, T., Leondiadis, L., Maggos, T., Mazej, D., Polańska, K., Povey, A., Rovira, J., Schoierer, J., Schuhmacher, M., Špirić, Z., Stajnko, A., Stierum, R., Tratnik, J.S., Vassiliadou, I., Annesi-Maesano, I., Horvat, M., Sarigiannis, D.A., 2018. Biomarkers of exposure in environment-wide association studies–Opportunities to decode the exposome using human biomonitoring data. Environ. Res. 164, 597–624. US EPA (United States Environmental Protection Agency), 1989. Cadmium (CASRN 7440- 43-9). Integrated Risk Information System (IRIS). https://cfpub.epa.gov/ncea/iris2/ chemicalLanding.cfm?substance_nmbr=141, Accessed date: 18 January 2019. US EPA (United States Environmental Protection Agency), 1991a. Arsenic, Inorganic (CASRN 7440-38-2). Integrated Risk Information System. https://cfpub.epa.gov/ ncea/iris2/chemicalLanding.cfm?substance_nmbr=278, Accessed date: 26 January 2019. US EPA (United States Environmental Protection Agency), 1991b. Silver (CASRN 7440- 22-4). Integrated Risk Information System. https://cfpub.epa.gov/ncea/iris2/ chemicalLanding.cfm?substance_nmbr=99, Accessed date: 18 January 2019. US EPA (United States Environmental Protection Agency), 1992. Styrene (CASRN 100-42- 5). https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=104, Accessed date: 26 January 2019. US EPA (United States Environmental Protection Agency), 2000. Benzene (CASRN 71-43- 2). Integrated Risk Information System. https://cfpub.epa.gov/ncea/iris2/ chemicalLanding.cfm?substance_nmbr=276, Accessed date: 26 January 2019. US EPA (United States Environmental Protection Agency), 2001. Chloroform (CASRN 67- 66-3). Integrated Risk Information System. https://cfpub.epa.gov/ncea/iris2/ chemicalLanding.cfm?substance_nmbr=25, Accessed date: 26 January 2019. US EPA (United States Environmental Protection Agency), 2003. Benzene (CASRN 71-43- 2). Integrated Risk Information System. https://cfpub.epa.gov/ncea/iris2/ chemicalLanding.cfm?substance_nmbr=276, Accessed date: 18 January 2019. US EPA (United States Environmental Protection Agency), 2005. Provisional Peer- Reviewed Toxicity Values for Bromoform. https://cfpub.epa.gov/ncea/pprtv/ recordisplay.cfm?deid=338856, Accessed date: 18 January 2019. US EPA (United States Environmental Protection Agency), 2010. Toxicological review of acrylamide (CASRN 79-06-1). In: Support of Summary Information on the Integrated Risk Information System. IRIS). https://cfpub.epa.gov/ncea/iris/iris_documents/ documents/toxreviews/0286tr.pdf, Accessed date: 18 January 2019. US EPA (United States Environmental Protection Agency), 2016. Memorandum: 2,4-D Human Health Risk Assessment for Registration Review. https://www.24d.org/ Studies/PDF/24D_EPA_Human_Health_Risk_Assmnt_2017.pdf, Accessed date: 28 January 2019. Zidek, A., Macey, K., MacKinnon, L., Patel, M., Poddalgoda, D., Zhang, Y., 2017. A review of human biomonitoring data used in regulatory risk assessment under Canada's Chemicals Management Program. Int.