Probabilistic risk assessment of dietary exposure to lead in residents of Guangzhou, China

Abstract

Lead and its compounds can have cumulative harmful effects on the nervous, cardiovascular, and other systems, and especially affect the brain development of children. We collected 4918 samples from 15 food categories in 11 districts of Guangzhou, China, from 2017 to 2022, to investigate the extent of lead contamination in commercial foods and assess the health risk from dietary lead intake of the residents. Lead was measured in the samples using inductively coupled plasma mass spectrometry. Dietary exposure to lead was calculated based on the food consumption survey of Guangzhou residents in 2011, and the health risk of the population was evaluated using the margin of exposure (MOE) method. Lead was detected in 76.5% of the overall samples, with an average lead content of 29.4 µg kg⁻¹. The highest lead level was found in bivalves. The mean daily dietary lead intakes were as follows: 0.44, 0.34, 0.25, and 0.28 µg kg⁻¹ body weight (bw) day⁻¹ for groups aged 3–6, 7–17, 18–59, and ≥ 60 years, respectively. Rice and rice products, leafy vegetables, and wheat flour and wheat products were identified as the primary sources of dietary lead exposure, accounting for 73.1%. The MOE values demonstrated the following tendency: younger age groups had lower MOEs, and 95% confidence ranges for the groups aged 3–6 and 7–17 began at 0.6 and 0.7, respectively, indicating the potential health risk of children, while those for other age groups were all above 1.0. Continued efforts are needed to reduce dietary lead exposure in Guangzhou.

Keywords:

• Lead
• dietary exposure
• margin of exposure
• risk assessment

Acknowledgments

The authors express thanks to Hongwei Zhou for his excellent technical assistance in chemical analysis.

Authors’ contributions

Shaofang Song: Methodology, data curation, writing-original draft; Weiwei Zhang: conceptualization and software; Yanyan Wang: investigation; Yufei Liu: supervision; Yan Li: validation; Xinhong Pan: experimental detection; Jinheng Zeng: investigation; and Yuhua Zhang: data curation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Science and Technology Program of Guangzhou [No. 2023A03J0450], the Science and Technology Program of Guangzhou [No. 202102080205], the Science and Technology Program of Guangzhou [No.2023A03J01368], the Science and Technology Program of Guangzhou [No.2023A03J0940], and the Basic Research Project of Key Laboratory of Guangzhou [No.202102100001]. This work was supported by the Guangzhou Municipal Health Commission and the Guangzhou Municipal Science and Technology Bureau.