Human exposure to dietary inorganic arsenic and other arsenic species: State of knowledge, gaps and uncertainties

Sci Total Environ. 2017 Feb 1;579:1228-1239. doi: 10.1016/j.scitotenv.2016.11.108. Epub 2016 Nov 30.


Inorganic arsenic (iAs) is ubiquitous in the environment as arsenite (AsIII) and arsenate (AsV) compounds and biotransformation of these toxic chemicals leads to the extraordinary variety of organoarsenic species found in nature. Despite classification as a human carcinogen based on data from populations exposed through contaminated drinking water, only recently has a need for regulatory limits on iAs in food been recognized. The delay was due to the difficulty in risk assessment of dietary iAs, which critically relies on speciation analysis providing occurrence data for iAs in food - and not simply for total arsenic. In the present review the state of knowledge regarding arsenic speciation in food and diet is evaluated with focus on iAs and human exposure assessment through different dietary approaches including duplicate diet studies, market basket surveys, and total diet studies. The analytical requirements for obtaining reliable data for iAs in food are discussed and iAs levels in foods and beverages are summarized, along with information on other (potentially) toxic co-occurring organoarsenic compounds. Quantitative exposure assessment of iAs in food is addressed, focusing on the need of capturing variability and extent of exposure and identifying what dietary items drive very high exposure for certain population groups. Finally, gaps and uncertainties are discussed, including effect of processing and cooking, and iAs bioavailability.

Keywords: Arsenic speciation; Dietary exposure; Food; Human health; Inorganic arsenic; Risk assessment.

MeSH terms

  • Arsenic / analysis
  • Diet / statistics & numerical data*
  • Dietary Exposure / statistics & numerical data*
  • Environmental Pollutants / analysis*
  • Environmental Pollution / statistics & numerical data*
  • Food Contamination / statistics & numerical data
  • Humans
  • Risk Assessment


  • Environmental Pollutants
  • Arsenic