Deterministic and Probabilistic Health Risk Assessment of Toxic Metals in the Daily Diets of Residents in Industrial Regions of Northern Ningxia, China

Abstract

This study was designed to investigate the toxic metal (aluminum (Al), arsenic (As), chromium (Cr), cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn)) concentrations in drinking water and different foodstuffs meat (pork, beef, and mutton), cereals (rice, flour, corn, millet), beans (cowpeas, tofu), potatoes (potato, sweet potato), solanaceous fruits (pepper, eggplant, bitter gourd, cucumber), vegetables (cabbage, cauliflower, spinach), and fruits (apples, watermelons, pears, grapes)) and then estimate the potential health risks of toxic metal consumption to local residents in industrial regions of northern Ningxia, China. As in drinking water, Cr in meat, Pb in cereals, Pb in beans, As and Pb in potatoes, Pb in solanaceous fruits, Cr and Ni in vegetables, and Ni and Pb in fruits were the most contaminated heavy metals in the corresponding food with over-standard rates of 16.7%, 12.5%, 5.1%, 60%, 50%, 50%, 38.2%, 44.4%, 44.4%, 31.8%, and 31.8%, respectively.The results of the deterministic assessment of health risks showed that the total noncarcinogenic risk value of dietary intake of toxic metals by the local population was 5.6106, indicating that toxic metals pose a high noncarcinogenic risk. The order of the non-carcinogenic risk is HIcereal (1.2104) > HIsolanaceous fruit (0.9134) > HIVegetables (0.8726) > HIFruit (0.8170) > HIMeat (0.7269) > HIDrinking water (0.6139) > HIBeans (0.2991) > HIPotatoes (0.1573). The total carcinogenic health risk from exposure to toxic metals through dietary intake was 9.98 × 10−4, indicating that the total cancer risk value of residents is beyond the acceptable range (10−4) under the current daily dietary exposure and implies a high risk of cancer. The order of the carcinogenic risk is RDrinking water (2.34 × 10−4) > RMeat (2.11 × 10−4) > Rsolanaceous fruit (1.89 × 10−4) > RFruit (1.88 × 10−4) > Rcereal (1.36 × 10−4) > RPotatoes (2.44 × 10−5) > RVegetables (1.51 × 10−5) > RBeans (0). The probabilistic assessment results showed that 98.83% of the population is exposed to severe noncarcinogenic risk and 87.02% is exposed to unacceptable carcinogenic risk. The sensitivity analysis showed that drinking water, local cereals, vegetables, and fruits were the major contributors to health risks. Our results indicated that the daily dietary exposure of residents in industrial regions of northern Ningxia poses a serious threat to human health, and it is suggested that relevant departments should strengthen monitoring and control of the current situation of toxic metal pollution in the environment and continue to pay attention and take measures to reduce the exposure of toxic metals in the diets of residents in this area. Graphical Abstract

Carcinogenic and non-carcinogenic health risk assessment of organic compounds and heavy metals in electronic cigarettes

“…We performed the probability assessment by pre-processing data to determine the distribution of parameters (e.g., concentration of chemical substances, daily intake, frequency of exposure, and body weight). The parameter distributions were fitted using Crystal Ball software, and the best-fit probability distribution type for each variable was determined by simulating the exposure factors with Anderson–Darling and chi-square tests 48 . Probabilistic estimation of health risks was performed using Monte Carlo techniques, and the number of Monte Carlo simulations in this study was 10,000.…”

Health Risk Assessment of Organic Compounds and Heavy Metals in Electronic Cigarettes

“…We performed the probability assessment by pre-processing data to determine the distribution of parameters (e.g., concentration of chemical substances, daily intake, frequency of exposure, and body weight). The parameter distributions were tted using Crystal Ball software, and the best-t probability distribution type for each variable was determined by simulating the exposure factors with Anderson-Darling and chi-square tests [43]. Probabilistic estimation of health risks was performed using Monte Carlo techniques, and the number of Monte Carlo simulations in this study was 10,000.…”

Health Risk Appraisal of Trace Elements in Groundwater in an Urban Area: A Case Study of Sichuan Basin, Southwest China

“…For the purpose of drinking, the samples with HPI values higher than 100 were considered to be polluted [33]. To carry out differentiated protection measures for groundwater, the HPI score was segmented into three grades: low (<15), medium (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), and high (>30) [30].…”

“…Monte Carlo simulation is a widely used method due to its flexibility and high efficiency. In addition, the sensitivity of health risk parameters was analyzed by the Sobol method [1,23,24]. This approach can deal with nonlinear data and provide a comprehensive analysis of global sensitivity [25].…”