Friday, June 2, 2023

Non-carcinogenic and cumulative risk assessment of exposure of kitchen workers in restaurants and local residents in the vicinity of polycyclic aromatic hydrocarbons – Scientific Reports

Characteristics of the participants

Table 1 presents the demographics of the participants (control group (n = 30), kitchen workers (n = 57), and individuals who live close to restaurants (n = 57)). There were 49 (87.5%) males and 8 (12.5%) females among the participants (kitchen workers and people living near restaurants). Among the control group, 25 (83.33%) were male, while 5 (16.67%) were female. The average age of kitchen workers, people living near the restaurant, and the control group was 33.6, 33.9, and 33.41 years, respectively. The participant’s body weight index (BMI) ranged from 24.7 to 25.46 kg/m2. According to the findings, 37 participants were exposed to passive smoking for 48 h before sampling. The most common transportation by volunteers was by private car and taxi. More than 70% of each group used a kitchen hood. Over half of the participants lived close to sources of PAHs emissions, including bus terminals, parking lots, and traffic areas.

Table 1 Specifications of the studied groups in terms of socio-demographics.

Distribution of PAH metabolites levels in urine

Exposure to PAHs is a significant concern because of its effects on human health. The mean levels of PAH metabolites in the urine samples of the study groups are displayed in Fig. 1 and other details are given in Table S1 (Supplementary data). The highest and lowest mean levels were related to 1-OHP and 9-OHPhe, respectively, in the three study groups. Similar findings were also achieved in research on kitchen workers in India13. Another research found that 1-OHP was more prominent than other PAH metabolites26. Further, the highest mean level of PAH metabolites measured in a study of PAHs biomonitoring adults in a Middle Eastern region was 1-OHP5, which is consistent with our results. 1-OHP is rapidly excreted through the urine, which could explain its high urinary level5.

Figure 1

Mean levels of OH-PAH metabolites in the studied group’s urine samples (ng/g cr) ((a) kitchen workers, (b) people living near restaurants, and (c) the control group).

Kitchen workers, people who live near restaurants, and the control group had a total average concentration of PAH metabolites (ΣOH-PAHs) of 2126.7, 1973.7, and 1687.61 ng/g cr, respectively (Fig. 1). Kitchen workers and those living near restaurants had higher ΣOH-PAHs than the control group, but this difference was only significant between the workers and control groups (p value < 0.05). A study in India confirmed this finding, revealing that kitchen workers had higher ΣOH-PAHs than the control group27. The ΣOH-PAHs in the urine of Shiraz citizens were 1988.1 ng/g cr5, which was lower than that found among the people who worked in restaurant kitchens. This seems logical because these workers are more exposed to PAHs due to being involved in the frying processes. It was also found in another study on school children in Shiraz that the ΣOH-PAHs (1460 ng/g cr) were lower than those in our study16. Differences in age and time spent at work and home might explain the discrepancy between the results.

Based on our findings, a significant difference in 9-OHPhe level was seen between people residing near restaurants and the control group (p = 0.017). According to a study conducted by Siddique, a significant concentration of phenanthrene was formed in all samples after cooking (frying)28, so it could be a logical reason for a higher 9-OHPhe level in samples of people living near restaurants (20.08 ng/g cr) than in the control group (7.86 ng/g cr). This result is similar to that reported by Wang et al.29. Nevertheless, there was no significant difference in other urinary PAH metabolites concentration among the three groups of our study (p > 0.05).

Clinical parameters levels in the studied subjects

Descriptive statistics for the clinical parameters of the participants are presented in Table 2. In this study, no significant difference was found between the parameters measured in the different groups (p > 0.05). However, the results of the study by Singh et al.13 in India report that continuous exposure to heat in kitchens can impair the kidney function of kitchen workers. Furthermore, in a study of residents of Shiraz, a significant difference in red blood cell (RBC) count and TG level was found between male and female participants5. This result was not observed in our study; it is probably due to the fact that in the current study, most of the participants were male.

Table 2 A comparison of the levels of the clinical parameters in the blood samples from the different study groups.

Measure of the concentrations of MDA (µm/mM cr) and TAC (mM/mM cr) in urine samples, and CRP (mg/L) in blood samples

Figure 2 shows a measurement of mean concentrations of MDA (µm/mM cr) and TAC (mM/mM cr) in urine samples and CRP (mg/L) in blood samples from study groups.

Figure 2
figure 2

A measure of the average concentrations of (a) MDA (µm/mM cr) and (b) TAC (mM/mM cr) in urine samples, and (c) CRP (mg/L) in blood samples (A: kitchen workers, B: individuals living near restaurants, and C: control group).

According to the test results, no significant difference was observed between the three groups in the concentrations of MDA, TAC, and CRP (p value > 0.05). The mean mass concentration of MDA was (0.00082, 0.00075, and 0.00082), TAC (1.21, 1.4, and 1.01), and CRP levels (3.67, 3.65, and 3.65) in A, B, and C, respectively (Fig. 2). Pan et al.8 found in their study that kitchen staff (369 µmol/mol cr) had significantly higher urinary MDA levels than service staff (267.2 µmol/mol cr), which contradicts the current study.

Spearman’s rank correlation coefficient was used to examine the association between measured concentrations in the study groups. A significant and positive linear relationship between the concentration of red blood cells in blood samples and TAC (CC = 0.33, p = 0.00), CRP (CC = 0.19, p = 0.02), and MDA (CC = 0.17, p = 0.04) was observed. In other words, with increasing RBC concentration, the concentration of TAC, CRP and, MDA increases linearly and this correlation is higher in TAC due to the higher correlation coefficient. Furthermore, RBCs in one study had a direct linear proportional relationship with MDA30, which is consistent with our findings.

Moreover, there was a significant negative linear correlation between TAC concentrations and MDA (CC = − 0.22, p = 0.01). This means that as TAC concentration rises, MDA concentration falls linearly and vice versa. In a biomonitoring study, MDA and TAC levels were significantly higher and lower, respectively, in men with idiopathic infertility than in fertile men31 which, like the present study, showed a relationship inverse between the TAC and MDA parameters.

The correlations between PAH metabolites (ng/g cr) and MDA, TAC, and CRP levels

Table 3 shows the correlations between PAH metabolites (ng/g cr) and MDA (mM/mM cr), TAC (mM/mM cr), and CRP (mg/L) in the groups studied.

Table 3 Correlations between PAHs metabolites concentration (ng/g cr) and concentrations of MDA (mM/mM cr), TAC (mM/mM cr) and CRP (mg/L) in the study groups.

The results indicated that there was a significant correlation between TAC levels and all measured metabolites of PAH, except for 9-OHPhe in the A and C groups, as well as 1-OHP in the B and C groups. The TAC assay was been applied to determine the antioxidant capacity of some heterogeneous compounds with antioxidant activity in body fluids and thus can also help in assessing the overall antioxidant status. Other research has found that increased exposure to PAH compounds increases oxidative stress and decreases TAC, increasing lung cancer susceptibility32.

Furthermore, according to the results shown in Table 3, it can be seen that as the amount of PAH metabolites measured in the urine samples increased, the TAC concentration decreased. Previous research has also indicated that accelerating oxidative stress and reducing TAC affect the prevalence of lung cancer33,34.

Exposure to PAHs has been identified as one of many causes of adverse health effects. It has been suggested that this phenomenon could be due to oxidative damage. For example, some studies on PAHs have been conducted in vitro and in vivo. Therefore, MDA is a commonly used biomarker to assess oxidative stress. Based on our results, there was a significant correlation between MDA levels and all measured PAH metabolites except the control group. The results showed that MDA concentrations increased significantly with increasing concentrations of urinary PAH metabolites. Researchers found that urinary MDA levels were positively associated with hydroxy-PAH levels in a rural population from the North China Plain (p < 0.05)35. Epidemiological studies have also reported an association between exposure to PAHs and urinary concentrations of MDA35. For example, Bae et al.36 reported that urinary MDA concentrations increased significantly with increasing urinary 1-hydroxy pyrene concentrations. A similar result was discovered in this study. Cooking oil smoke is one of the main sources of PAHs. Kitchen workers are highly exposed because they do not wear respiratory protection8. Therefore, it can cause oxidative DNA damage and lipid peroxidation12,37. Urinary levels of 1-OHP and MDA often represent occupational exposure to PAHs and oxidative stress among kitchen workers and their neighbors38,39.

CRP is an inflammation marker that rises when the body is inflamed. In the present study, there was no significant relationship between PAH metabolites and CRP in any of the three study groups (Table 3). However, the results of one study demonstrated that levels of biomarkers for urinary PAHs are positively correlated with serum CRP levels40. Therefore, in the present study, it is possible that the effects of confounders did not show any association between serum CRP and PAH metabolites in the urine of the participants.

Linear regression analysis

The results of the regression analysis were used to examine the relationship between urine PAH metabolites levels and exposure variables such as subjects’ activities, the cooking frequency at home and at work, age of the building, the use of the hood, the weekly consumption of food (meat, fish, grilled fruit and vegetables), passive smoking, body mass index, residence conditions in traffic, and etc. Only secondhand smoke had a significant relationship with the concentration of PAH metabolites in the urine of the studied participants (p < 0.05). 1-OHNap (β = 0.26 and p value = 0.013) and 1-OHP (β = 0.43 and p value = 0.01) were significant according to secondhand smoke in participants (Fig. 3). Therefore, this study considers secondhand tobacco smoke as a possible source of naphthalene and pyrene emissions. Additionally, several other studies have shown that cigarette smokers release significant concentrations of naphthalene into living spaces41,42.

Figure 3
figure 3

A comparison of mean PAH metabolites concentration (ng/g cr) in urine samples of (a) non-passive and (b) passive smokers.

Non-carcinogenic and cumulative risk assessment

Most people believe that cooking and food processing techniques like smoking and drying are the main sources of PAH contamination. Cooking causes a variety of compounds, including PAHs, to be produced in food, depending on a number of factors, such as time, fuel used, distance from the heat source, drainage of fat, and type (grilling, frying, roasting). While the exact mechanisms of how PAHs are created are unknown, it is likely that there are several different ones, including the pyrolysis of meat at high temperatures and the pyrolysis of melted fat when it drips onto a heat source. As a result of eating more grilled and fast food, restaurant employees and people living nearby are exposed to PAH compounds through ingestion. In recent decades, health risk evaluation has been considered a valuable method for evaluating potential environmental risks43. We evaluated the risk of exposure to PAHs in the target subjects by only taking the dietary ingestion route into account because the diet is the primary source of PAHs exposure in non-smokers25.

In the current research, EDIi, HQi, and HIi for 1-OHNap, 2-OHNap, 2-OHFlu, 9-OHPhe, and 1-OHP were estimated to investigate the potential health hazards of PAH metabolites. Table 4 shows the findings associated with EDIi. The results obtained in Table 4 were used to calculate HQi, and HIi based on Eqs. (2) and (3). The results related to HQi and HIi are shown in Fig. 4. Based on the findings, HQi for PAH metabolites (1-OHNap, 2-OHNap, 2-OHFlu, 9-OHPhe, and 1-OHP) was less than one (HQi < 1). Furthermore, HIi was less than one (HIi < 1) in the studied groups, indicating low-risk negative health impacts on the target groups. Similarly, research conducted on Mexican children exposed to high levels of PAHs found that the HQi was less than 1 in those children44. PAHs exposure was not associated with any significant non-cancer health risks in another study conducted in Spain25. As a result of PAHs exposure, Fernandez et al.21 found that Spanish women were not at significant risk of health. According to a study conducted in Mexico, women living in the studied communities had HQi greater than 1, which is associated with increased health risks44.

Table 4 EDIi for PAHs metabolites measured in the studied groups.
Figure 4
figure 4

HQi for PAH metabolites ((a) 1-OHNap, (b) 2-OHNap, (c) 2-OHFlu, (d) 9-OHPhe, and (e) 1-OHP) and (f) HIi in the studied groups (A: kitchen workers, B: people living near restaurants, and C: control group).

Strength and limitations

Biomonitoring of restaurant workers and people living near restaurants was conducted for the first time in Shiraz, Iran. We examined the correlation between PAH metabolites and other measured clinical parameters to increase the reliability of the results of this study. Environmental PAHs can enter the body in several ways and cause a variety of side effects. The limitations of our study are mainly related to the small number of subjects in each of the three groups. Therefore, these results should be interpreted with caution so that other studies can support them. In future studies, larger sample sizes should be used for more detailed statistical analysis, especially for CRP, MDA, TAC, and RBC. It is suggested that future research examine how differences in diet and lifestyle affect emission sources.

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