scholarly journals Proposal of New Health Risk Assessment Method for Deficient Essential Elements in Drinking Water—Case Study of the Slovak Republic

Author(s):  
Stanislav Rapant ◽  
Veronika Cvečková ◽  
Edgar Hiller ◽  
Dana Jurkovičová ◽  
František Kožíšek ◽  
...  

The US EPA health risk assessment method is currently widely used to assess human health risks for many environmental constituents. It is used for risk assessment from the exposure to various contaminants exceeding tolerable or safe reference doses, determined e.g., for drinking water, soil, air and food. It accepts widely that excess contents of non-essential elements (e.g., As, Pb or Sb) in environmental compartments represent a general risk to human health. However, contrary to toxic trace elements, deficient contents of essential (biogenic) elements e.g., F, I, Se, Zn, Fe, Ca or Mg may represent even higher health risk. Therefore, we propose to extend the human health risk assessment by calculating the health risk for deficient content and intake of essential elements, and to introduce the terms Average Daily Missing Dose (ADMD), Average Daily Required Dose (ADRD) and Average Daily Accepted Dose (ADAD). We propose the following equation to calculate the Hazard Quotient (HQ) of health risk from deficient elements: HQd = ADRD/ADAD. At present, there are no reference concentrations or doses of essential elements in each environmental compartment in world databases (Integrated Risk Information System IRIS, The Risk Assessment Information System RAIS). ADRD and ADMD can be derived from different regulatory standards or guidelines (if they exist) or calculated from actual regional data on the state of population health and content of essential elements in the environment, e.g., in groundwater or soil. This methodology was elaborated and tested on inhabitants of the Slovak Republic supplied with soft drinking water with an average Mg content of 5.66 mg·L−1. The calculated ADMD of Mg for these inhabitants is 0.314 mg·kg−1·day−1 and HQd is equal to 2.94, indicating medium risk of chronic diseases. This method extending traditional health risk assessment is the first attempt to quantify deficient content of essential elements in drinking water. It still has some limitations but also has potential to be further developed and refined through its testing in other countries.


2020 ◽  
Vol 192 (11) ◽  
Author(s):  
Juan C. Fernández-Macias ◽  
Ángeles C. Ochoa-Martínez ◽  
Sandra T. Orta-García ◽  
José A. Varela-Silva ◽  
Iván N. Pérez-Maldonado




2019 ◽  
Vol 20 (2) ◽  
pp. 499-507 ◽  
Author(s):  
Qiao Zhang ◽  
Sheng Yang ◽  
Bangmi Xie ◽  
Jian Zhang ◽  
Chen Deng ◽  
...  

Abstract The occurrence, distribution, ecological and health risk assessment of five antibiotics (CFM, ERY, LCM, SMD and SMX) in 32 drinking water reservoirs of a megacity (Shenzhen) in Guangdong–Hong Kong–Macao Greater Bay Area (GBA), were investigated. Among the above antibiotics, CFM was not detected, ERY, SMD, LCM and SMX were detected in 65.6%, 46.9%, 43.7% and 40.6% of samples, with concentrations of 1.594–7.605 ng·L−1, 0.335–6.695 ng·L−1, 0.288–7.878 ng·L−1 and 0.770–5.355 ng·L−1, respectively. The maximum concentration of ERY was detected in GT Reservoir, and those of the other 3 antibiotics were detected in SZ Reservoir. The ecological risk quotient (RQ) values for SMX in SZ, XL, YT, EJ, SY, TG, XK, GK, MK and GT reservoirs ranged from 0.1 to 1.0, indicating a median risk to aquatic organisms, the others posed insignificant risk or low risk. Considering the joint effects of detected antibiotics, the highest overall RQ value was 0.38, obtained in SZ Reservoir, in other words, it was exposed to greater risk. Based on health risk assessment, the health RQ values for the detected antibiotics were significantly lower than 0.01, indicating insignificant risk to human health. These findings could provide a scientific basis for the government to ensure the drinking water safety of a megacity in GBA.



2020 ◽  
Vol 12 (3) ◽  
pp. 469-485 ◽  
Author(s):  
Yujie Ji ◽  
Jianhua Wu ◽  
Yuanhang Wang ◽  
Vetrimurugan Elumalai ◽  
Thirumalaisamy Subramani


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