Risk Assessment of Dibutyl Phthalate (DBP) and Bis(2-Ethylhexyl) Phthalate (DEHP) in Hot Pot Bases with a Hybrid Modeling Approach

(1) Background: Hot pot bases are susceptible to phthalate (PAE) contamination due to their high lipid content. Standard risk models often fail to capture extreme values, leading to biased exposure estimates. This study characterized dibutyl phthalate (DBP) and bis(2-ethylhexyl) phthalate (DEHP) contamination using a hybrid modeling framework to ensure precise risk profiling. (2) Methods: A total of 91 samples were analyzed via GC-MS. Concentration data were fitted using traditional parametric, extreme value mixture (EVMM), and finite mixture models. Probabilistic dietary risks were assessed for Chinese demographic groups using 10,000-iteration Monte Carlo simulations. (3) Results: DEHP (detection rate: 55%) and DBP (32%) were best modeled by a two-component Gamma mixture and a Lognormal-Generalized Pareto distribution, respectively. These advanced models significantly outperformed conventional distributions in capturing upper-tail extremes. Crucially, all hazard quotients (HQs) remained below the safety threshold of 1, indicating acceptable risk, although children aged 7-13 exhibited the highest calculated risk (Max DEHP HQ = 0.68). (4) Conclusions: Although current exposure levels are within safe limits, the heavy-tailed distributions identify potential sporadic high-exposure events that traditional models overlook, specifically highlighting the relative vulnerability of children aged 7-13. This study validates that hybrid statistical approaches offer superior precision for analyzing skewed contamination data. Consequently, these findings provide a critical scientific basis for refining regulatory monitoring and implementing targeted source-tracking measures to mitigate long-tail food safety risks.

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Publication Details

Journal
Toxics
Published
2026-02-02
DOI
https://doi.org/10.3390/toxics14020150
Primary Topic
Effects and risks of endocrine disrupting chemicals
Type
article
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article

Risk Assessment of Dibutyl Phthalate (DBP) and Bis(2-Ethylhexyl) Phthalate (DEHP) in Hot Pot Bases with a Hybrid Modeling Approach

Jing Jing, Haixia Sui, Xiangyu Bian, S. Chen et al.
Toxics
Effects and risks of endocrine disrupting chemicals
article

Risk Assessment of Dibutyl Phthalate (DBP) and Bis(2-Ethylhexyl) Phthalate (DEHP) in Hot Pot Bases with a Hybrid Modeling Approach

Jing Jing, Haixia Sui, Xiangyu Bian, S. Chen, Jihan Sun, Daoyuan Yang, Yuanzhang Zhao, Dongya Chen, Zhujun Liu, Yan Song, Siyu Huang
article en

Abstract

(1) Background: Hot pot bases are susceptible to phthalate (PAE) contamination due to their high lipid content. Standard risk models often fail to capture extreme values, leading to biased exposure estimates. This study characterized dibutyl phthalate (DBP) and bis(2-ethylhexyl) phthalate (DEHP) contamination using a hybrid modeling framework to ensure precise risk profiling. (2) Methods: A total of 91 samples were analyzed via GC-MS. Concentration data were fitted using traditional parametric, extreme value mixture (EVMM), and finite mixture models. Probabilistic dietary risks were assessed for Chinese demographic groups using 10,000-iteration Monte Carlo simulations. (3) Results: DEHP (detection rate: 55%) and DBP (32%) were best modeled by a two-component Gamma mixture and a Lognormal-Generalized Pareto distribution, respectively. These advanced models significantly outperformed conventional distributions in capturing upper-tail extremes. Crucially, all hazard quotients (HQs) remained below the safety threshold of 1, indicating acceptable risk, although children aged 7-13 exhibited the highest calculated risk (Max DEHP HQ = 0.68). (4) Conclusions: Although current exposure levels are within safe limits, the heavy-tailed distributions identify potential sporadic high-exposure events that traditional models overlook, specifically highlighting the relative vulnerability of children aged 7-13. This study validates that hybrid statistical approaches offer superior precision for analyzing skewed contamination data. Consequently, these findings provide a critical scientific basis for refining regulatory monitoring and implementing targeted source-tracking measures to mitigate long-tail food safety risks.

ToxicsVol. 14(2)
Jiangsu Provincial Center for Disease Control and Prevention (CN), China National Center for Food Safety Risk Assessment (CN), University of Manitoba (CA), Chongqing University of Technology (CN), Southeast University (CN)
Zero hunger
Openalex Percentile: Top 70%
Effects and risks of endocrine disrupting chemicals
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