Physicochemical characterization and determination of chloramphenicol residues and heavy metals in Algerian honeys

Assessment of Toxic Element Contamination in Honey, Milk, and Eggs from Algiers (Algeria) Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS): Exploring Health Implications of Pollution

Consumption of foods such as milk, honey, and eggs contaminated with toxic elements above established norms poses a health risk to the population. This study explores the potential of products from beehives, poultry, and dairy as indicators of environmental pollution caused by toxic substances (Pb, Cd, Hg), seeks contamination sources, evaluates the exposure level, and assesses health risks. Through the analysis of samples from three distinct regions in Algiers, including 30 milk, 30 honey, and 30 poultry egg samples, the study assesses levels of toxic elements (lead, cadmium, and mercury) using ICP-MS and analyzes consumer exposure risk. The analysis of honey reveals levels of Pb (0.282 μg/g) > Cd (0.161 μg/g) > Hg (0.017 μg/g), the analysis of eggs shows levels of Pb (0.399 μg/g) > Cd (0.239 μg/g) > Hg (0.027 μg/g), and the results in milk show levels of Cd (0.250 μg/g) > Pb (0.131 μg/g) > Hg (0.019 μg/g). The risk analysis indicates a risk associated with milk consumption for both adults and children, whereas for honey and eggs, the risk is limited to children only in polluted areas. Future research should expand to other toxic elements in different food matrices in both northern and southern Algeria to evaluate the health risk for African and European consumers.

Lead exposure from honey: meta-analysis and risk assessment for the Arab region

The Codex Alimentarius Commission has adopted a maximum level for lead in honey (0.1 mg/kg). Despite representing a population of more than half a billion, exposure and risk assessments for lead specific to the Arab region are lacking. The aim of this work was to collect analytical data for lead in honey available in Arab countries and to assess the risk caused by exposure to lead from these samples for local consumers. A regional mean lead concentration in honey, obtained through a meta-analysis of 57 studies, was used in deterministic risk assessments for adults (nephrotoxicity and cardiovascular effects) and young children (developmental neurotoxicity). A regional pooled mean concentration of 0.12 mg/kg [95%CI: 0.07-0.21] (0.13 mg/kg, if non-detects are considered at their highest possible value) was obtained. Margins of exposure of 363 [71-17182] and 865 [168-40909] were calculated for adults, and of 48 [9-2273] for children, indicating potential concern for the latter population subset. These values were produced using GEMS consumption data, and considering the same intake for both children and adults, potentially overestimating the risk for children. Nevertheless, food competent authorities should consider measures to reduce lead concentration in honey available for sale in the region to prevent trade constraints and to better protect vulnerable populations.

Evaluation of trace metallic element levels in coffee by icp-ms: a comparative study among different origins, forms, and packaging types and consumer risk assessment

Trace elements (TE) contamination of foods and beverages constitutes a public health issue. In this context, the main objective of this study was to determine metals and metalloids content in coffee and to assess the health risks associated with contaminated coffee consumption. To this end, 44 samples of coffee from different origins, forms, and packaging types were analyzed. TE analysis was performed by ICP-MS after digestion. The data analysis was based on principal components analysis (PCA) and analysis of variance (ANOVA). Health risk assessment was determined by the estimated daily intake (EDI), target hazard quotient (THQ), and hazard index (HI). The findings showed that TE levels in coffee varied widely. The highest levels were related to aluminum (Al) (59.88 ± 54.86 mg/kg), manganese (Mn) (16.26 ± 24.59 mg/kg), copper (Cu) (11.60 ± 11.55 mg/kg), and cadmium (Cd) (9.92 ± 10.32 mg/kg). In terms of coffee form and packaging type, a significant difference (P < 0.0001) was observed in nickel (Ni), chromium (Cr), zinc (Zn), cobalt (Co), Cu, Mn, and Al content. The highest EDI was found in Al (0.0109 mg/kg BW/day) in ground coffee packaged in capsules. In terms of chronic daily intake (CDI), Cd and Al were above the reference dose (RfD). THQ of these elements were greater than 1.0, and HI was above the value of 1.0 in different forms of coffee. More interdisciplinary research on the relationships between the metal concentrations in coffee samples and those in feed, water, and soil would be quite interesting.

Sentinel animals for monitoring the environmental lead exposure: combination of traditional review and visualization analysis

In nature, certain animals share a common living environment with humans, thus these animals have become biomonitors of health effects related to various environmental exposures. As one of the most toxic environmental chemicals, lead (Pb) can cause detriment health effects to animals, plants, and even humans through different exposure pathways such as atmosphere, soil, food, water, and dust, etc. Sentinel animals played an "indicative" role in the researches of environmental pollution monitoring and human health. In order to comprehend the usage of sentinel animals in the indication of environmental Pb pollution and human Pb exposure completely, a combination of traditional review and visualization analysis based on CiteSpace literature was used to review earlier researches in this study. In the first instance, present researches on exposure sources and exposure pathways of Pb were summarized briefly, and then the studies using sentinel animals to monitor environmental heavy metal pollution and human health were combed. Finally, visualization software CiteSpace 5.8.R3 was used to explore and analyze the hotspots and frontiers of lead exposure and sentinel animals researches at home and abroad. The results showed that certain mammals were good indicators for human lead exposure. Sentinel animals had been widely used to monitor the ecological environment and human lead exposure. Among them, the blood lead levels of small mammals, particularly for domestic dogs and cats, had a significant correlation with the blood lead levels of human living in the same environment. It indicated that certain biological indicators in animals can be used as surrogates to monitor human body exposure to heavy metals. This study also explored the challenges and perspectives that may be faced in sentinel animal research, in order to provide a certain theoretical basis and train of thought guidance for future research.

Multi-element Analysis of Honey from Amhara Region-Ethiopia for Quality, Bioindicator of Environmental Pollution, and Geographical Origin Discrimination

Honey is a widely utilized sweetener containing mainly sugars with many other minor ingredients such as metallic elements. The analysis aimed to develop a chemometric model for tracing the geographical origin, evaluating nutritional quality, assessing pollution effect, and searching for marker metals for the region's honey. Forty-seven honey samples were collected directly from the apiarists at seven administrative zones. The contents of 14 metals were analyzed using inductively coupled plasma optical emission spectrometry after standard sample digestion. The findings showed us the major elements ranged from 24.8 to 1996 mg/kg of the honey sample with K > Ca > Na > Mg. The minimum and maximum values for the trace metals were 2.35 mg/kg and 163 mg/kg, respectively, in the order of Fe > Cr > Zn > Ni > Mn > Cu > Co. From this data, the region's honey has its own contribution as a source of major and trace elements. Furthermore, mean values for the toxic heavy metals were 0.57 to 1.85 for Pb, 1.03 to 1.21 for Cd, and 2.85 to 6.21 for As in mg/kg. Thus, the pollution level in the environment seems to be at an alarming rate. Using principal components analysis (PCA), the first four principal components explained 80.16% of the total variation. The region's honey was best classified into five major clusters using linear discriminant analysis (LDA) with an average discrimination power of 89.91%. The LDA sorting model was verified by the cross-validation method. The verification revealed that the model has 92.11% recognition power and 93.33% prediction ability.