Do arsenic levels in rice pose a health risk to the UK population?
Bibliographic record
Abstract
Consumption of rice and rice products can be a significant exposure pathway to inorganic arsenic (iAs), which is a group 1 carcinogen to humans. The UK follows the current European Commission regulations so that iAs concentrations must be < 0.20 mg kg−1 in white (polished) rice and <0.25 mg kg−1 in brown (unpolished) rice. However, iAs concentration in rice used for infant food production or direct consumption has been set at a maximum of 0.1 mg kg−1. In this context, this study aimed to evaluate iAs concentrations in different types of rice sold in the UK and to quantify the health risks to the UK population. Here, we evaluated 55 different types of rice purchased from a range of retail outlets. First, we analysed all rice types for total As (tAs) concentration from which 42 rice samples with tAs > 0.1 mg kg−1 were selected for As speciation using HPLC-ICP-MS. Based on the average concentration of iAs of our samples, we calculated values for the Lifetime Cancer Risk (LCR), Target Hazard Quotient (THQ) and Margin of Exposure (MoE). We found a statistically significant difference between organically and non-organically grown rice. We also found that brown rice contained a significantly higher concentration of iAs compared to white or wild rice. Notably, 28 rice samples exceeded the iAs maximum limit stipulated by the EU (0.1 mg kg−1) with an average iAs concentration of 0.13 mg kg−1; therefore consumption of these rice types could be riskier for infants than adults. Based on the MoE, it was found that infants up to 1 year must be restricted to a maximum of 20 g per day for the 28 rice types to avoid carcinogenic risks. We believe that consumers could be better informed whether the marketed product is fit for infants and young children, via appropriate product labelling containing information about iAs concentration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".