Determination of a guidance value for the communication of individual-level biomonitoring data for urinary arsenic

https://doi.org/10.1016/j.ijheh.2022.113927Get rights and content

Highlights

  • Guidance values to interpret individual data on urinary As are lacking.

  • A structural equation model is built using As data in urine and drinking water (DW).

  • The resulting regression is applied considering an overexposure of 10 μg As/L in DW.

  • A range of values for the sum of urinary arsenic species (9–20 μg/L) is derived.

  • Sensitivity/specificity consideration allow to orientate the final value selection.

Abstract

Background

Available guidance values to interpret individual-level biomonitoring data (ILBD) for the sum of urinary inorganic-related arsenic species (SUIAS) are generally based on population statistical descriptors and not on a predetermined exposure level that should not be exceeded. The objective of this study was thus to propose a range of SUIAS concentrations, reflecting an exposure corresponding to WHO's provisional guideline value (PGV) for arsenic in drinking water (10 μg/L), within which an exposure-based biomonitoring guidance value can be identified. METHOD A comprehensive literature review was carried out in order to identify studies that were relevant to the determination of a guidance value. Drinking water arsenic exposure and urinary biomonitoring concentrations obtained from selected studies were used to conduct a structural equation modeling meta-analysis, from which regression coefficients were obtained to derive an interpretative guidance range. RESULTS Individuals exposed to the arsenic background level comparable to North American and European countries and to a water source contaminated at the WHO's PGV, would have, on average, urinary SUIAS between 9 and 20 μg/L, with the most probable value being 15 μg/L. To address the associated uncertainty, the final guidance value selection within this range may be based on a targeted sensitivity and specificity towards detecting overexposed individuals. Indeed, spans of sensitivity of 60–82%, and of specificity of 58–85%, were estimated for the proposed range based on drinking water exposure raw data from the literature. CONCLUSION The range of guidance values obtained appears suitable for interpreting and communicating ILBD in any population biomonitoring studies in which background exposure is comparable to the North American and European context. Before selecting a single value within the proposed range, it will be important for Public Health officials to assess the possible consequences of this selection on the management and communication of the biomonitoring results.

Introduction

Biomonitoring, which involves measuring contaminants concentrations in the human body through biomarkers, has become a commonly tool used in populational survey. The main goal of such biomonitoring surveys is to assess a population's environmental exposure to contaminants and to support subsequent health risk management (Angerer et al., 2007; Haines et al., 2011). Inorganic arsenic (iAs), a recognized human carcinogen, is often included in biomonitoring programs (Angerer et al., 2011; CDC, 2021; Health Canada, 2019; IARC, 2012).

Populations are exposed to iAs mainly from drinking water (DW) and some types of foods (e.g. rice, rice-based products, other grains and grain-based products and certain fruit juices and vegetables) (ATSDR, 2007; European Food Safety Authority (EFSA) et al., 2021; IARC, 2012; Joint F.A.O./WHO Expert Committee on Food Additives, 2011). The biomarker most commonly used to determine exposure to iAs is the sum of urinary inorganic-related arsenic species (SUIAS), which corresponds to the sum of the inorganic forms As (III) and As (V) and their metabolites DMA and MMA (Hsueh et al., 2002). In a health risk assessment perspective, the analysis of the SUIAS is considered more useful than measurements of total urinary arsenic. Indeed, this latter biomarker is strongly influenced by the presence of the much less toxic organic forms of As (eg: arsenobetaine ans arsenosugars) from the consumption of seafood (fish, shellfish and algae) (CDC, 2017; Navas-Acien et al., 2011).

For many biomarkers of toxicant exposure such as SUIAS, the paucity of available guidance values strongly challenges the communication to participants of biomonitoring campaigns of their individual results (Haines et al., 2011). This barrier is even more limitating in the case of iAs, in particular because the SUIAS data show a high interindividual variability and due to the premise of absence of threshold exposure for its carcinogenic effect (Concha et al., 2006; Health Canada, 2006; IARC, 2012; Lindberg et al., 2006). It results in missed opportunities to make potentially overexposed participants aware of their specific situation and to invite them to identify their individual sources of exposure and to control them when possible. This is a concern for the managers in charge of large biomonitoring campaigns since there is a need of follow-up with the study participants whom's individual results may be considered as truly alarming (Haines et al., 2011).

In the absence of appropriate individual overexposure guidance value for SUIAS, it is still possible to use statistical criteria to identify situations of overexposure (e.g. Population's 95th percentile value) (Angerer et al., 2011; Ewers et al., 1999; Garnier et al., 2021; Vogel et al., 2019). However, for a naturally occurring contaminant such as iAs, a double challenge needs to be addressed when applying this approach: on the one hand, not to trivialize biomarker levels that are considered “normal” from a statistical point of view, but which are still associated with an elevated exposure and, likely, corresponding health risk; and on the other hand, not to stigmatize behaviors based on traditional diets such as high rice or seafood consumption, the latter associated to undeniable nutritionnal benefits(Mozaffarian and Rimm, 2006).

Indeed, interpretation of SUIAS values is still complicated by the fact that, for a large proportion of individuals, iAs intakes come mainly from food sources whose iAs levels are more or less controlled depending on the jurisdiction, or even strongly associated with diets that are perceived as being particularly healthy (e.g. gluten free diets) (Bulka et al., 2017). Moreover, certain kinds of seafood such as finfish, algae and a few shellfish can contain DMA as well as arsenosugars that are partially metabolized to DMA (CDC, 2017; Navas-Acien et al., 2011; Taylor et al., 2017). The occasional consumption of these seafoods can therefore cause a punctual increase in urinary concentrations of this metabolite. This increase could in turn result into overestimating the true iAs exposure and trigger an unjustified shift in dietary habits (National Academy of Sciences, 1999).

Under these circumstances, SUIAS results from populations primarily exposed to iAs through consumption of contaminated water have the advantage of being more representative of its toxic potential. In addition, these biomonitoring results can be interpreted in relation to the exposure associated to WHO's provisional guideline value (PGV) for iAs of 10 μg/L (World Health Organization, 2003), which is applied as a standard in several jurisdictions (Canada, USA, European Union, among others) (Council Directive (EU), 1998; Health Canada, 2006; U.S. EPA, 2001). This PGV is set on the basis of the best possible compromise between the cancer risk and the lowest achievable concentration in water, taking current DW treatment techniques into account (World Health Organization, 2017).

The objective of this study was therefore to propose an approach for the determination of a guidance value for biomonitoring data of SUIAS that allows the identification of individual study participants that may likely have experienced an iAs overexposure for which action of reduction can reasonably be envisaged at the individual scale. More specifically, the study aimed to 1) identify a range of SUIAS concentrations which could indicate a possible iAs environmental overexposure for North American and European populations; 2) assess the sensitivity and specificity of the different values within this range in order to orient decision-makers on the a priori selection of a final guidance value that allows an appropriate identification of overexposed individuals.

Section snippets

Framework

On the basis of the underlying premise that the WHO PGV in DW of 10 μg As/L constitutes a guideline that reflects an iAs exposure that is consensually considered as a level of which the exceedance should be avoided, the approach followed consists into predicting the range of SUIAS concentrations which would reflect 1) the consumption DW contaminated to or above the level of the PGV for As; and 2) the background exposure through the environmental, in particular, dietary sources of As in north

Selected studies

A total of 1137 studies were initially identified from the literature search strategy. Excluding duplicates, revising the titles and abstract for relevancy, adding relevant reference by the snowballing approach and applying the inclusion criteria (see Table 1) to the resulting group of references allowed to reduce this number to 14 studies, from which only 11 could be used for the upcoming SEM meta-analysis. Indeed, the remaining 3 had either missing summary statistics or had a high proportion

Originality

The objective of this study was to propose a range of potential SUIAS concentrations guidance values, reflecting a predetermined exposure level that should not be exceeded, that allows the individual identification of -and communication with- concerned biomonitoring study participants in North American and European populations, presumably sharing similar diets and environmental exposure. Rather than single guidance value, a range of values is proposed, more precisely 9–20 μg/L, with 15 μg/L

Conclusion

To the best of the authors’ knowledge, this is the first study to propose a range of guidance values that allows an exposure-based communication of human biomonitoring data on urinary As at the individual level. Concretely, such guidance value could be used during biomonitoring surveys to determine whether participants should be informed of their individual result and receive information and general advice to help determine, and if necessary control, their sources of iAs exposure. The

Credit author statements

Gabriela Ponce: Methodology, Formal analysis, Data curation, Visualization, Writing - original draft, writing – review & editing. Fabien Gagnon: Conceptualization, Methodology, Formal analysis, Writing - original draft, writing – review & editing. Marie-Hélène Bourgault: Methodology, Formal analysis, writing – review & editing. Michelle Gagné: Methodology, Formal analysis, Writing - original draft, writing – review & editing. Elhadji Anassour Laouan-Sidi: Formal analysis, Writing - original

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgements

Funding by Health Canada (MOA #4500370380) for the preliminary steps of this work is acknowledged. The authors would like to thank Dr Stéphane Buteau for his thoughtful comments throughout the course of this work. We thank Dr. David J. Thomas, Dr. Pierre Ayotte and Dr. Michèle Bouchard for providing the raw data of the studies of Calderon et al. (2013), Normandin et al. (2014) and Gagnon et al. (2016).

References (65)

  • Y.-M. Hsueh et al.

    Urinary arsenic speciation in subjects with or without restriction from seafood dietary intake

    Toxicol. Lett.

    (2002)
  • A.-L. Lindberg et al.

    Gender and age differences in the metabolism of inorganic arsenic in a highly exposed population in Bangladesh

    Environ. Res.

    (2008)
  • M. Molin et al.

    Major and minor arsenic compounds accounting for the total urinary excretion of arsenic following intake of blue mussels (Mytilus edulis): a controlled human study

    Food Chem. Toxicol.

    (2012)
  • M. Molin et al.

    Humans seem to produce arsenobetaine and dimethylarsinate after a bolus dose of seafood

    Environ. Res.

    (2012)
  • A. Navas-Acien et al.

    Seafood intake and urine concentrations of total arsenic, dimethylarsinate and arsenobetaine in the US population

    Environ. Res.

    (2011)
  • T. Roychowdhury

    Groundwater arsenic contamination in one of the 107 arsenic-affected blocks in West Bengal, India: status, distribution, health effects and factors responsible for arsenic poisoning

    Int. J. Hyg Environ. Health

    (2010)
  • V. Taylor et al.

    Human exposure to organic arsenic species from seafood

    Sci. Total Environ.

    (2017)
  • C.-H. Tseng

    A review on environmental factors regulating arsenic methylation in humans

    Toxicol. Appl. Pharmacol.

    (2009)
  • N. Vogel et al.

    Human biomonitoring reference values: differences and similarities between approaches for identifying unusually high exposure of pollutants in humans

    Int. J. Hyg Environ. Health

    (2019)
  • M. Wilhelm et al.

    Revised and new reference values for some trace elements in blood and urine for human biomonitoring in environmental medicine

    Int. J. Hyg Environ. Health

    (2004)
  • Arsenic and soluble inorganic compounds: BEI., in: documentation of the threshold limit values and biological exposure indices

  • Arsenic: Public Health Statement. Agency for Toxic Substances & Disease Registery, Atlanta, USA

    (2007)
  • C.M. Bulka et al.

    The unintended consequences of a gluten-free diet

    Epidemiology

    (2017)
  • C. Cascio et al.

    The impact of a rice based diet on urinary arsenic

    J. Environ. Monit.

    (2011)
  • (2021)
  • Biomonitoring Summaries—Arsenic

    (2017)
  • D. Chakraborti et al.

    Arsenic groundwater contamination in Middle Ganga Plain, Bihar, India: a future danger?

    Environ. Health Perspect.

    (2003)
  • C.-L. Chen et al.

    Ingested arsenic, cigarette smoking, and lung cancer RiskA follow-up study in arseniasis-endemic areas in Taiwan

    JAMA

    (2004)
  • M.W.L. Cheung

    Meta-analysis: a Structural Equation Modeling Approach

    (2015)
  • G. Concha et al.

    Spatial and Temporal variations in arsenic exposure via drinking-water in northern Argentina

    J. Health Popul. Nutr.

    (2006)
  • On the quality of water intended for human consumption

    Off. J. Eur. Communities

    (1998)
  • D. Arcella et al.

    Chronic dietary exposure to inorganic arsenic

    EFSA J.

    (2021)
  • Cited by (0)

    View full text