The Evaluation of ICP OES for the Determination of Potentially Toxic Elements in Lipsticks: Health Risk Assessment

This study aimed to optimize and validate the inductively coupled plasma optical emission spectrometric method (ICP OES) for the simultaneous determination of eleven potentially toxic elements (Al, Cd, Cr, Co, Cu, Ni, Pb, Fe, Sb, Mn, and Zn) in lipstick samples. The method was evaluated by applying...

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Bibliographic Details
Main Authors: Jelena Mrmošanin, Aleksandra Pavlović, Snežana Mitić, Snežana Tošić, Emilija Pecev-Marinković, Jovana Krstić, Milena Nikolić
Format: Article
Language:English
Published: Slovenian Chemical Society 2019-12-01
Series:Acta Chimica Slovenica
Subjects:
Online Access:https://journals.matheo.si/index.php/ACSi/article/view/4800
Description
Summary:This study aimed to optimize and validate the inductively coupled plasma optical emission spectrometric method (ICP OES) for the simultaneous determination of eleven potentially toxic elements (Al, Cd, Cr, Co, Cu, Ni, Pb, Fe, Sb, Mn, and Zn) in lipstick samples. The method was evaluated by applying the standard addition method. The recoveries for all elements in lipsticks were between 90% and 110%, except for Cd and Pb they were <90% and >110%, respectively. The health risk assessment was determined by calculating the average daily intake (ADD), hazard quotient (HQ), and hazard index (HI). The highest mean value for ADD was for Fe (4.8×10-1 mg kg-1 day-1), and the lowest was for Co (9.3×10-6 mg kg-1 day-1). There was no significant toxic health risk for any of the elements (HQ < 1), except for Fe (HQ < 3) which indicates a potential health risk. Based on PCA, all potentially toxic elements have been classified in the three groups. The first group includes Fe, the second includes Al, and all other elements belong to the third group. The cluster analysis of the elements provided the identical grouping that was obtained on the basis of PCA. Two separate clusters were obtained when cluster analysis was applied to the analyzed samples. The first cluster contained the only sample that was brown. The second cluster was divided into two sub-clusters. The first sub-cluster included the samples belonging to category I regarding the price, while the second sub-cluster included the samples belonging to category II and III regarding the price.
ISSN:1318-0207
1580-3155