Consumer health risk assessment of Arsenic and Mercury in hen eggs through Monte Carlo simulations

被引:5
|
作者
Abedi, Abdol-samad [1 ]
Hoseini, Hedayat [2 ]
Mohammadi-Nasrabadi, Fatemeh [1 ]
Rostami, Negar [1 ]
Esfarjani, Fatemeh [1 ]
机构
[1] Shahid Beheshti Univ Med Sci, Natl Nutr & Food Technol Res Inst NNFTRI, Fac Nutr Sci & Food Technol, Food & Nutr Policy & Planning Res Dept, Tehran, Iran
[2] Shahid Beheshti Univ Med Sci, Natl Nutr & Food Technol Res Inst, Fac Nutr Sci & Food Technol, Dept Food Sci & Technol, Tehran, Iran
关键词
Hen eggs; Arsenic; Mercury; Risk assessment; ICP-MS; THQ; Monte Carlo simulations; HOME-PRODUCED EGGS; HEAVY-METALS; TRACE-ELEMENTS; DIETARY-INTAKE; EXPOSURE; LEAD; CONTAMINATION; FOODSTUFFS; CHEMICALS; CHROMIUM;
D O I
10.1186/s12889-023-16223-4
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
BackgroundThis study was conducted to assess the concentration of heavy metals (arsenic and mercury) and estimate the probability that consumption of hen egg products collected in Iran has carcinogenic or non-carcinogenic consequences.MethodsA total of eighty-four hen eggs from 21 major brands were randomly selected from among thirty local supermarkets in two seasons (winter (January) and summer (August) 2022). Arsenic (As) and Mercury (Hg) was determined by using ICP-MS. The human health risk assessment refers to the formulation of the USEPA standard focused on Estimated Daily Intake (EDI), International Lifetime Cancer Risk (ILCR), Target Hazard Quotient (THQ), and Monte Carlo simulation (MCS) as a probabilistic method. Data analysis was carried out using the statistical software SPSS. Differences in mean concentrations of As and Hg in two seasons were tested by paired t-test.ResultsOver two seasons, the average As and Hg concentrations in hen eggs were 0.79 and 0.18 & mu;g.kg(-1), respectively. Seasonal difference in As concentration (p = 0.451) was not significant, whereas that of Hg concentration (p < 0.001) was significant. The calculated value of EDI was 0.29 & mu;g As/day and 0.06 & mu;g Hg/day. The EWI in the maximum scenario of as level in hen eggs was estimated to be 8.71 & mu;g As and 1.89 & mu;g Hg/month for Iranian adults. THQ's mean for As and Hg in adults was determined to be 0.00385 and 0.00066, respectively. In addition, ILCRs by MCS for As were 4.35E-4.ConclusionIn total, the result indicates that there was not a significant risk of developing cancer; the calculation of THQ was still below the accepted level of 1, indicating that there was no risk while, according to most regulatory programs (ILCR > 10(- 4)) shows a threshold carcinogenic risk of arsenic through consuming in hen eggs. Therefore, policymakers need to be aware that it is prohibited to establish chicken farms in heavily polluted urban areas. It is essential to regularly conduct examinations to measure the presence of heavy metals in both ground waters used for agriculture and the feed provided to chickens. Additionally, it is advisable to focus on raising public awareness about the importance of maintaining a healthy diet.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] Chapter twelve. Monte Carlo simulations in risk assessment: Cancer risk in the Polish coke industry
    Biesiada, M
    Smolik, E
    Hubicki, L
    ENVIRONMENTAL HEALTH FOR ALL: RISK ASSESSMENT AND RISK COMMUNICATION FOR NATIONAL ENVIRONMENTAL HEALTH ACTION PLANS, 1999, 49 : 147 - 153
  • [22] Transfer and risk assessment of fipronil in laying hen tissues and eggs
    Wang, Zhiwei
    Du, Ziyan
    Shi, Yanke
    Qi, Peipei
    Di, Shanshan
    Zhao, Huiyu
    Ji, Xiaofeng
    Lu, Chunbo
    Wang, Xinquan
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 932
  • [23] Arsenic and arsenic species in shellfish and finfish from the western Arabian Gulf and consumer health risk assessment
    Krishnakumar, Periyadan K.
    Qurban, Mohammad A.
    Stiboller, Michael
    Nachman, Keeve E.
    Joydas, Thadickal V.
    Manikandan, Karuppasamy P.
    Mushir, Shemsi Ahsan
    Francesconi, Kevin A.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 566 : 1235 - 1244
  • [24] External dose assessment of NORM added consumer products using Geant4 Monte Carlo simulations
    Hassan, Halmat J.
    Hashim, S.
    Abu Hanifah, N. Z. H.
    Sanusi, M. S. M.
    Fahmi, M. R.
    Tahar, R. M.
    Bradley, D. A.
    RADIATION PHYSICS AND CHEMISTRY, 2022, 200
  • [25] Respiratory functions and health risk assessment in inhalational exposure to vinyl acetate in the process of carpet manufacturing using Monte Carlo simulations
    Khoshakhlagh, Amir Hossein
    Saberi, Hamid Reza
    Gruszecka-Kosowska, Agnieszka
    Kumar, Vikas
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (12) : 32560 - 32572
  • [26] Summer and winter variations of BTEX concentrations in an oil refinery complex and health risk assessment based on Monte-Carlo simulations
    Khoshakhlagh, Amir Hossein
    Yazdanirad, Saeid
    Mousavi, Mahdi
    Gruszecka-Kosowska, Agnieszka
    Shahriyari, Mehran
    Rajabi-Vardanjani, Hassan
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [27] Respiratory functions and health risk assessment in inhalational exposure to vinyl acetate in the process of carpet manufacturing using Monte Carlo simulations
    Amir Hossein Khoshakhlagh
    Hamid Reza Saberi
    Agnieszka Gruszecka-Kosowska
    Vikas Kumar
    Environmental Science and Pollution Research, 2023, 30 : 32560 - 32572
  • [28] Health risk assessment of exposure to benzene, toluene, ethylbenzene, and xylene (BTEX) in a composite manufacturing plant: Monte-Carlo simulations
    Khoshakhlagh, Amir Hossein
    Askari Majdabadi, Masoud
    Yazdanirad, Saeid
    Carlsen, Lars
    HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2023, 29 (3-4): : 728 - 742
  • [29] Summer and winter variations of BTEX concentrations in an oil refinery complex and health risk assessment based on Monte-Carlo simulations
    Amir Hossein Khoshakhlagh
    Saeid Yazdanirad
    Mahdi Mousavi
    Agnieszka Gruszecka-Kosowska
    Mehran Shahriyari
    Hassan Rajabi-Vardanjani
    Scientific Reports, 13
  • [30] Use of Monte Carlo simulations in the assessment of calibration strategies - Part I: an introduction to Monte Carlo mathematics
    Burrows, John
    BIOANALYSIS, 2013, 5 (08) : 935 - 943