Dietary exposure and risk assessment to lead of the population of Jiangsu province, China

Abstract

The paper’s main purpose is to estimate the dietary exposure to lead for the inhabitants of Jiangsu province, China. Lead concentration data were obtained from the national food contamination monitoring programme during 2007–10. Food samples (n = 2077) were collected from 23 food categories in Jiangsu province. Consumption data were derived from Chinese national nutrition and health survey in 2002, which included 3938 inhabitants from 1451 households in Jiangsu province. Concentration data were combined with consumption data to estimate the dietary intake for the inhabitants of 2–6, 7–17 and 18–80 years, respectively. The β-binomial–normal (BBN) model was used to estimate the long-term intake for the population in Jiangsu province. The distribution of individual margin of exposure (IMoE) was introduced to assess the health effect. Uncertainty of IMoE was quantified by Monte Carlo and bootstrap methods. The mean levels of dietary exposure to lead were estimated at 3.019 µg kg⁻¹ bw day⁻¹ for children aged 2–6 years, 2.104 µg kg⁻¹ bw day⁻¹ for teenagers aged 7–17 years, and 1.601 µg kg⁻¹ bw day⁻¹ for adults aged 18–80 years. The mean intakes for the urban and rural populations were 1.494 and 1.822 µg kg⁻¹ bw day⁻¹, respectively. From the 25th to 99.9th percentiles, IMoE was 0.125–2.057 for 2–6 years and 0.473–7.998 for 18–80 years, respectively. The distribution of IMoE could indicate a public health concern on lead for the Chinese population in Jiangsu. Control measures should be taken to reduce lead exposure in Jiangsu province.

Keywords:

• dietary exposure
• lead
• individual margin of exposure
• uncertainty analysis

Acknowledgements

The authors thank the Centre for Disease Control and Prevention of Jiangsu province for providing contamination and consumption data for food lead. They are very grateful to Dr van der Voet Hilko, Wageningen University and Research Centre, for his valuable comments on relevant questions of IMoE.

Funding

This work was supported by the National Natural Science Foundation of China [grant number 81172769] and Jiangsu Natural Science Foundation for young scholars [grant number BK2012348].