Heavy metal concentrations in rice that meet safety standards can still pose a risk to human health

The study addresses the public health risks from heavy metal(loid)s in rice, a staple for over half of the world’s population that accumulates more heavy metals than other cereals. Although maximum acceptable concentrations (MACs) for metals such as arsenic and copper exist, evidence shows that long-term exposure to concentrations below MACs can still cause adverse health effects. Existing assessments often use uniform exposure parameters and overlook variability in age, body weight, region, and diet, potentially underestimating risks for susceptible groups. Prior nationwide assessments were limited and simplified key exposure parameters. Moreover, uncertainty in parameters (aleatory and epistemic) can bias risk estimates. The study aims to integrate probabilistic (Monte Carlo) and fuzzy methods within a human health risk assessment (HHRA) framework to: (1) identify critical receptors by province and quantify exceedance probabilities; (2) determine provincial contributions of Cd, As, Hg, Pb, and Cr to risks; and (3) clarify mismatches between national food safety (NFS) standards and HHRA, ultimately informing locally tailored standards.

Previous studies have evaluated heavy metal(loid) contamination in rice, often at local scales and with simplified exposure assumptions (e.g., fixed body weight and intake), leaving receptor- and region-specific impacts unresolved. Limited nationwide surveys (e.g., China 2014; Spain 2012; Kuwait 2013; United States 2024) exist, generally without refined exposure characterization. Long-term exposure to low-level arsenic has been linked to non-carcinogenic outcomes and cancer. Monte Carlo methods are widely used to manage aleatory uncertainty when data support probabilistic parameterization, while fuzzy analysis can capture epistemic uncertainty and assessor judgment. Integrated probability–fuzzy frameworks have been applied in contaminated site remediation, environmental risk analysis, and water resource management, offering methodological precedents for food safety assessment.

Data collection: Peer-reviewed articles on heavy metal(loid) concentrations in rice in China (1997–2021) were retrieved from Web of Science and China National Knowledge Infrastructure using keywords such as “heavy metals,” “rice,” “risk assessment,” and “China.” After removing duplicates and excluding studies from highly contaminated settings (e.g., mining areas, sewage irrigation), data on five heavy metals (Cd, As, Hg, Pb, Cr) and two nutrient elements (Cu, Zn) were compiled from 408 articles, yielding 3376 concentration data points across 32 provinces. National Food Safety (NFS) standards for rice were referenced for MACs (e.g., As 0.2 mg kg⁻1, Cd 0.2 mg kg⁻1, Hg 0.02 mg kg⁻1, Pb 0.2 mg kg⁻1, Cr 0.1 mg kg⁻1). Single Factor Pollution Index (SFPI): P = C/MAC, where P < 1 indicates compliance. Human Health Risk Assessment (HHRA): Following US EPA methodology, exposure was evaluated for four age groups using demographic and intake parameters from the Handbook of Exposure Parameters for the Chinese Population. Average daily dose (ADD) = (C × IR × ED)/(BW × AT). Non-carcinogenic risk (NCR) was quantified via hazard quotient (HQ = ADD/RfD). Carcinogenic risk (CR) used slope factors, with inherent lifetime cancer risk (ILCR) aggregated over age groups. Probabilistic analysis: Monte Carlo simulation characterized parameter variability and produced exceedance probabilities for non-carcinogenic and carcinogenic risks (e.g., PnCR, PlCR). Fuzzy analysis: Fuzzy sets and membership functions mapped risk and nutritional indicators to linguistic categories. Fuzzy AND/OR operators combined health risk and nutritional value to derive a rice quality–heavy metal (RQHM) score, defuzzified using centroid calculation to obtain a 0–1 score (higher indicates better safety/quality). The integrated framework produced provincial risk exceedance probabilities, element-wise risk contributions, and RQHM scores.

- Rice that meets NFS standards can still pose non-negligible health risks, particularly for children (5–12 years) and toddlers (2–5 years) under chronic exposure. Young people (<18) were the critical receptors in all provinces; children were critical in about two-thirds of provinces and toddlers in the rest, with toddlers more common in rice-producing provinces. - Average hazard quotient (HQ) for critical receptors ranked: As (0.67) > Cd (0.52) > Cr (0.38) > Pb (0.16) > Hg (0.15), highlighting As and Cd as dominant contributors. - Probability that non-carcinogenic risk exceeds the threshold (PnCR) varied widely by province (0.005–0.997), generally higher in central China and increasing from west to east and north to south. - Carcinogenic risk: Mean CR for critical receptors was below 1 × 10⁻4 (acceptable range). In 24 provinces, the probability of unacceptable CR (PlCR) was zero. Central and western provinces showed slightly higher PlCR (mean ~0.413). Taiwan’s unacceptable CR was driven by elevated As. - Elemental contributions to overall health risk showed strong spatial patterns: As dominated in northern China (provincial contributions 52.55–100%). Cd dominated in parts of southern China (e.g., Hunan 51.60%, Jiangxi 97.48%, Guangdong 43.13%, Guangxi 29.88%). Across China, As contributed on average ~64.57% and Cd ~21–22% to total risk, while Hg contributed minimally (~1.5%). - Compliance vs risk mismatch: Examples showed As concentrations below MACs yielding HQs 1.8–3.2 times the non-carcinogenic threshold, whereas Pb and Hg exceeded MACs in some provinces but had HQs < 1 (e.g., Pb in Tianjin, Anhui, Jiangsu with SFPI > 1.0 yet HQs 0.52–0.64). - Exceedances of MACs were identified for specific metals in certain provinces: Hg in Shaanxi, Guizhou, Jilin, Guangdong, and Hunan; Pb in Jiangsu, Anhui, Tianjin, Jilin, and Liaoning; As in Taiwan; Cr in Sichuan. - Nutritional quality (Cu, Zn) was generally acceptable; most provinces showed low nutritional risk indicators. - Fuzzy RQHM scores indicated higher safety/quality in northwest and northeast China, and lower scores in central and southern regions. Northern China’s score was approximately eight-fold that of southern China, reflecting lower risk and better nutritional status in the north. - Geographic and exposure drivers: Differences in rice concentrations, intake rates (IR), and body weight (BW) explained provincial risk variability even at similar contaminant levels.

The findings demonstrate that relying solely on MAC compliance can underestimate health risks because receptor-specific exposure (age, intake, body weight) significantly modifies risk. Children and toddlers face higher risks due to higher intake per body weight and greater vulnerability, consistent with other studies. Although dietary shifts could theoretically reduce exposure, rice will remain the staple in China, making contaminant reduction in rice critical. Spatial heterogeneity shows As- and Cd-driven risks with clear regional patterns. Differences between risks from commercial versus locally grown rice, and inter-provincial trade—including the growth of e-commerce—contribute to spatial transfer of risk, so non-producing regions can still face elevated intake risks. The mismatch observed between SFPI/NFS-based assessments and HHRA—where elements below MAC (e.g., As) can still cause non-carcinogenic hazards, and elements exceeding MAC (e.g., Pb, Hg) may not—highlights the need to integrate localized exposure parameters into standards and decision-making. Tailoring limits to local dietary habits and receptor profiles can better protect sensitive populations while efficiently targeting mitigation.

Heavy metal(loid) concentrations in commercial rice in China generally meet NFS standards, yet probabilistic HHRA reveals non-negligible risks for sensitive groups, especially children and toddlers, even when concentrations are below MACs. Non-carcinogenic risks are relatively higher in central and southern China. Arsenic is the predominant contributor to overall health risk (approximately 2.8–100% across provinces), followed by cadmium (0–96.81%), with body weight and rice intake shaping final risks. Fuzzy evaluation shows pronounced regional differences in rice safety and quality, with higher safety in northern regions. Policymakers should prioritize reducing As and Cd in rice, refine exposure parameters (age- and region-specific BW and intake), and align food safety standards with local conditions to better protect public health. Future work should expand and refine exposure characterization, consider multiple dietary sources, and integrate nutritional considerations into comprehensive risk management.

- Exposure characterization used average intake levels for age groups by province, which may not capture within-group variability; integrating national nutrition and health survey data would improve estimates. - The assessment focused solely on rice; excluding other foods likely underestimates total dietary heavy metal(loid) risks. - Nutritional evaluation was limited (e.g., focusing on select elements); many factors (climate, agronomic practices, rice varieties) influence nutritional quality and were not fully considered.