Occupational benzene exposure and the risk of genetic damage: a systematic review and meta-analysis

doi:10.21203/rs.2.10985/v1

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Occupational benzene exposure and the risk of genetic damage: a systematic review and meta-analysis

https://doi.org/10.21203/rs.2.10985/v1

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published 15 Jul, 2020

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Background

To systematically evaluate the influence of benzene exposure on the genetic damage index of workers, and to explore the influence of low concentration benzene exposure on workers’ genetic damage index using 3.25mg/m3 as the boundary value, in order to provide a basis for improved prevention and control of the harm from benzene exposure to the occupational population.

Methods

We conducted a search of five databases, including Pub Med, Web of Science,China National Knowledge Infrastructure(CNKI), Wan Fang Data and Chongqing VIP, to identify relevant articles up to December 25, 2018. Two researchers independently extracted and carefully evaluated the data according to the inclusion and exclusion criteria of the literature. The imported articles were managed by Endnote X7, and the data were extracted and sorted by Excel 2013. We utilized Stata 12.0 software to perform the meta-analysis in the present study.

Results

A total of 68 eligible articles were finally included for the synthetic analyses. The meta-analysis results showed that occupational benzene exposure led to significantly increased Micronucleus (MN) frequency, Sister chromatid exchange (SCE) frequency, Chromosome aberration (CA) frequency, Olive Tail moment (OTM), Tail moment (TM), Tail length (TL), and Tail DNA% (T DNA%) compared to the control group (P < 0.05), and the pooled effect value estimates were 1.36, 0.98, 0.76, 1.06, 0.96, 1.78, and 1.42, respectively. Subsequent analysis of the effect of low concentration benzene exposure on genetic damage found significantly increased MN frequency increased compared with the control group (P < 0.05).

Conclusions

Occupational benzene exposure can affect multiple genetic damage indicators. Even at an exposure concentration lower than 3.25mg/m3, benzene exposure has genotoxicity. These data provide an important scientific basis for the further revision of occupational disease prevention strategies in China. At the same time, increased attention should be focused on the health monitoring of the occupational population exposed to benzene, and health management should be strengthened to improve the health of the occupational population.

Health Economics & Outcomes Research

Health Policy

Benzene

Genetic damage

Meta-analysis

Benzene (C₆H₆) is the simplest aromatic hydrocarbon and organic solvent. It is widely used in the leather, painting, petrochemical, and automobile industries, amongst others. The International Agency of Research on Cancer has classified benzene as a Group I carcinogen. Benzene can affect human health and cause many health problems, such as decreased white blood cell and platelet counts in peripheral blood, aplastic anemia, myelodysplastic syndromes, and leukemia[1, 2]. Genotoxicity may be a possible carcinogenic mechanism underlying the leukemic effect of benzene[3]. Epidemiological studies have shown that benzene exposure is associated with genetic damage, and some studies have shown elevated the frequency of Sister chromatid exchange (SCE), Micronucleus (MN) , and Chromosome aberrations (CA) in benzene-exposed workers[4, 5]. Although the links between benzene and various types of genetic damage have been evaluated in several studies[6-8], the evidence from these independent studies was found to be insufficient to support such associations.

Occupational exposure limits can be used to judge the hygienic status of workers in the workplace and form the basis for hygienic supervision in the workplace as an occupational health management tool[9]. Data on the occupational health or epidemiology of workers’ health is another criteria for establishing occupational exposure limits for workplace chemicals[10]. As the official agency of the U.S. Department of Labor tasked with managing occupational safety and health, the Occupational Safety and Health Administration (OSHA) recommended in 1971 that the allowable exposure limit for benzene should be 32.5 mg/m³ (10 ppm). In 1987, the time-weighted average allowable concentration was recommended to be reduced to 3.25 mg/m³ (1 ppm), which is the limit used currently. According to animals experiments, epidemiological studies and quantitative risk assessment, the occupational exposure limit of benzene recommended by the scientific expert group to European Union countries should be less than 3.25 mg/m³[11]. The maximum allowable concentration of benzene exposure in China was 50 mg/m³ in 1956, 40 mg/m³ in 1979, 10 mg/m³ as Pemissible concentration-Short Term Exposure Limit (PC-STEL) and 6 mg/m³ (1.8 ppm) as Permissible concentration-Time Weighted Average (PC-TWA) in 2002. The method of monitoring breathing zone air was changed to the individual sampling monitoring method[12]. At present, benzene-induced leukemia has been classified as an occupational cancer in China. Benzene exposure concentrations less than 3.25mg/m³ show inconsistent genetic damage results.

Meta-analysis can generate reliable conclusions. In this study, we used meta-analysis to examine the impact of benzene exposure on genetic damage. At the same time, we explored the effect of low concentration benzene exposure (3.25mg/m³) on genetic damage indicators. These data provide a scientific reference for the future revision of benzene occupational exposure limits in China.

Search strategy and study selection

We conducted a search of five databases, including PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Wan Fang Data and Chongqing VIP, to identify relevant articles up to December 25, 2018. The last search was on December 25, 2018. The retrieval strategy used the following keywords: (“Benzene” OR “benzol”) AND (“Genetic damage” OR “DNA damage” OR “chromosomal aberration” OR “CA” OR “sister chromatid exchange” OR “SCE” OR “single-cell gel electrophoresis” OR “SCGE”). When identifying multiple articles of the same study, we selected the most recent or most comprehensive articles. All of the selected articles were required to meet the following inclusion criteria: (1) Published in English or Chinese; (2) independent population epidemiological investigation; (3) article contains an exposure group and control group; (4) the two groups were comparable in terms of length of service, age and health status; and (5) data can be expressed in or converted into . Studies were excluded according to the following criteria: (1) Case reports, reviews and letters; (2) duplicated data and incomplete information studies; (3) data cannot be converted into the outcome indicators; and (4) animal experiments and basic research.

Data extraction

Two researchers independently extracted and carefully checked the data according to the inclusion and exclusion criteria. Disagreements were resolved through discussion. If the two researchers could not reach a consensus, the result was reviewed by a third researcher. The imported articles were managed by Endnote X7, and the data were extracted and sorted by Excel 2013. We extracted the following data: first author's name, year of publication, number of exposed groups and control groups, exposure concentration, etc. We collected and expressed seven types of genetic damage indicators as including Micronucleus (MN) frequency, Sister chromatid exchange (SCE) frequency, Chromosome aberration (CA) frequency, Olive Tail moment (OTM), Tail moment (TM), Tail length (TL) and Tail DNA% (T DNA%). Before the analysis, it was decided that a study number ≤ 3 would not be conducive for the meta-analysis. If the unit of benzene exposure concentration was expressed in ppm, it was converted into mg/m³ according to 1 ppm = 3.25mg/m³. For articles that provided sample size, maximum and minimum values, and median, an online calculator was used with the compiled formulas provided by Wan et al[13] and Luo et al[14]. (http://www.comp.hkbu.edu.hk/~xwan/median2mean.html). Data from 11 articles were converted by this method. For articles with genetic damage index values expressed in the μ ± SE format, we using SD = SE×; 13 articles were subjected to this conversion. The standard mean difference (SMD) method was used for the meta-analysis to quantitatively analyze the effects of benzene exposure on genetic damage.

Statistical methods

We utilized Stata 12.0 software to perform the meta-analysis in the present study. Heterogeneity among the studies was assessed using the I² statistic[15] . P < 0.1 and I² > 50% was considered evidence of heterogeneity among the studies[16]. If I² > 50%, we used a random-effects model to estimate the pooled SMD. Otherwise, a fixed-effects model was used for the estimation. A sensitivity analysis was used to compare the fixed-effects model and random-effects model and to assess the stability of the meta-analysis results. Egger’s linear regression test[17] and Begg’s tests[18] can be used to evaluate publication bias; if P < 0.05, we used the trim and fill method for correction. All P values in the meta-analysis were two-sided, and P < 0.05 was considered significant. Cumulative meta-analysis is used to highlight the dynamic trend of research conclusions and to reflect the impact of each study on comprehensive conclusions[19].

Characteristics of the studies

According to the search strategy, we found a total of 3,714 articles (1,056 from PubMed, 823 from Web of Science, 463 from CNKI, 1150 from Wan Fang Data and 222 from Chongqing VIP). Among these articles, a total of 68 eligible articles[3, 4, 6-8, 20-82] were finally included for the synthetic analyses. All were published between 1981 and 2017. Among the 68 included articles, 33 were published in Chinese, and 35 were published in English. A flow diagram for the article selection is shown in Figure 1. Baseline characteristics of the 68 eligible articles are listed in additional file 1 Table 1. Among the included articles, there were 37 that reported MN frequency, 20 SCE frequency, 16 CA frequency, four OTM, five TM, seven TL, and four articles reporting T DNA%. The concentration of benzene exposure was less than 3.25mg/m³ in seven articles reporting MN frequency, three on CA frequency and two on TM.

Meta-analysis results

Q statistics and I² were used to test the heterogeneity of the genetic damage indicators, and the results are as follows: MN frequency (Q = 1126.55, I²= 95.7%, P < 0.1), SCE frequency (Q = 228.21, I²= 91.2%, P < 0.1), CA frequency(Q = 88.01, I²= 81.8%, P < 0.1), OTM (Q = 20.09, I²= 80.1%, P < 0.1), TM (Q = 114.24, I²= 93.9%, P < 0.1), TL (Q = 254.58, I²= 95.7%, P < 0.1), and T DNA% (Q = 83.13, I²= 95.2%, P < 0.1). The results showed a high degree of heterogeneity among the studies, and we therefore used the random-effects model for analysis. The pooled estimates of effect SMD values on genetic damage indicators are shown in Table 2.

The meta-analysis results showed that occupational benzene exposure significantly increased MN frequency, SCE frequency, CA frequency, OTM, TM, TL, and T DNA% compared with the control group (P < 0.05), and the pooled effect value estimates were 1.36, 0.98, 0.76, 1.06, 0.96, 1.78, and 1.42, respectively. The study also evaluated the effects of an exposure concentration less than 3.25mg/m³. For low exposure, the pooled estimate of effect value for MN frequency was 0.46 (95% confidence interval (CI)(0.09-0.82), P < 0.05), for CA frequency was 0.26 (95% CI (−0.16-0.68), P > 0.05), and for TM was 0.59 (95% CI (−0.08-1.27), P > 0.05), indicating that a low concentration of benzene exposure can also cause genetic damage, mainly by affecting MN frequency. The respective forest plots are shown in Figures 2, 3 and 4.

Sensitivity analysis

To judge the stability of the analysis method, the fixed effect model and random effect model were used to calculate the combined SMD and 95% CI for each genetic damage index. The results of the fixed-effects model of MN frequency, SCE frequency, CA frequency, OTM, TM, TL, and T DNA% are as follows: 0.97 (95% CI, 0.91-1.02), 0.67 (95% CI, 0.56-0.78), 0.74 (95% CI, 0.63-0.85), 0.90 (95% CI, 0.71-1.08), 0.84(95% CI, 0.69-0.99), 1.50 (95% CI, 1.33-1.66), and 1.15 (95% CI, 0.98-1.31), respectively. The detailed results are shown in Table 3. Comparing the results of the two models, no significant difference was found in the combined effect value of each genetic damage index, which indicated that the results were stable and reliable.

Publication bias

Egger’s linear regression test and Begg’s test are used to demonstrate publication bias; if P < 0.05, we used the trim and fill method for corrections. Egger’s linear regression test and Begg’s tests both showed no publication bias for the genetic damage indicators CA frequency, OTM, TM, and TL (P > 0.05), while the Egger’s linear regression test and Begg’s tests both found publication bias (P < 0.05) for MN frequency and SCE frequency, Egger’s linear regression test showed publication bias for T DNA% (P = 0.039, 95% CI, 1.57-33.02). The results are shown in Table 4. Therefore, we corrected for publication bias using the trim and fill method. The results for MN frequency and SCE frequency showed that the number of missing articles was 0, and there was no publication bias. The T DNA% results showed that 1 article was missing; although there was publication bias, the combined effect values did not change significantly, and the original results were robust. The results are shown in Table 5.

Cumulative meta-analysis

The selected articles are regarded as a continuous study. This means that the research results must be added to the meta-analysis over time, as the publication of new original studies requires a repeated analysis. This approach can highlight the dynamic trend of the research conclusions and thus reflect the impact of each study on the overall conclusions. We performed cumulative meta-analysis of MN frequency, SCE frequency, and CA frequency according to publication time. The results showed that the stability of the pooled estimate of effect and 95% CI increased with publication time, becoming more stable and statistically significant (P < 0.05). The results are shown in Figures 5, 6, and 7.

Meta-analysis can sort out and count the results of various article studies. Through comprehensive analysis of multiple research results, the statistical efficiency of the original research results and the estimated effect can be improved. Genetic damage caused by exogenous chemicals is not only a sensitive indicator of early health damage but also an important mechanism underlying the effects of carcinogenic chemicals. Therefore, genetic damage can be used as an early biomarker for health damage caused by carcinogens. In this study, a final total of 68 domestic and foreign eligible articles investigating the effects of benzene exposure on genetic damage in the occupational population were included for synthetic analyses, and a total of 7 genetic damage indicators were evaluated in the meta-analysis including MN frequency, SCE frequency, TM, TL, OTM, T DNA%, and CA frequency. The large number of samples included in the articles can overcome differences in research results caused by different research subjects, methods and designs. This approach can quantitatively and comprehensively evaluate the effects of occupational benzene exposure on workers' genetic damage and use reliable statistical analysis methods to obtain more credible inferences. The meta-analysis results showed that occupational benzene exposure significantly increased MN frequency, SCE frequency, CA frequency, OTM, TM, TL, and T DNA% compared with the control group (P < 0.05).

At present, there is no definite conclusion as to whether a low concentration of benzene can cause genetic damage in the occupational population. Lovreglio P et al[6] revealed that for benzene concentrations of 246.6ug/m³ and 19.9 ug/m³, the exposure group and control group did not show differences in the frequency of CA and MN. However, Fang Y et al.[81] suggested that current levels of low concentration benzene exposure can induce a significant increase in MN frequency. Our study found that even at concentrations below 3.25 mg/m³, the MN frequency in the exposed group was higher than that of the control group. This result is consistent with Fang Y et al.[81], suggesting that exposure to low concentrations of benzene may cause genetic damage. However, the TM and CA frequency indexes in the exposed group were not increased compared with controls. Within this concentration range, only four groups with CA frequency index results and four groups of TM index data were combined for the analysis, and the small number of articles may lead to a large random error. Another potential reason for this result is that among the four groups of TM studies, one subject group was gasoline pump maintenance workers; this type of work is characterized by non-continuous benzene exposure, and the workers may therefore be exposed to high concentrations of benzene for a relatively short period of time, leading to negative results. Thus, attention should be paid to the different mechanisms of exposure. In addition, the Occupational Exposure Limit is 6 mg/m³ (8 h time-weighted average) in the Chinese workplace, whereas the level recommended by OSHA in the United States is 3.25mg/m³[11] . According to the results of this study, exposure to low concentrations of benzene may lead to an increase in MN frequency in the occupational population, suggesting that exposure to low concentrations of benzene can have an impact on genetic damage. Therefore, we should consider whether the current occupational exposure limit in China is reasonable. At the same time, engineering and individual protection mechanisms should be strengthened, and self-protection awareness of the occupational population should be enhanced. Occupational health check-ups are performed regularly to detect abnormalities over time and protect workers' health.

Although a previous meta-analysis article evaluated the relationship between occupational benzene exposure and genetic damage[83] , that study only analyzed the MN frequency indicator; no other genetic damage indicators were evaluated. The present study is the first meta-analysis of studies examining the relationship between occupational benzene exposure, as well as low benzene exposure concentrations, and different genetic damage indicators. This study collected relevant articles published since the 1980s and quantitatively analyzed the influence of benzene exposure on various genetic damage indicators, elaborating on the results of previous articles. The results showed a high degree of heterogeneity among the studies, and we therefore used the random-effects model for analysis. Potential sources of heterogeneity include the large time span of the study, developments in genetic damage detection technology, mixed exposure and exposure duration. The fixed effect model and random effect model were used for sensitivity analysis, and no significant difference was detected in the combined effect value of each genetic damage index, indicating that the results were stable and reliable. This study analyzed the publication bias of each genetic damage index and found that MN frequency, SCE frequency and T DNA% showed publication bias. After correcting these indexes with the trim and fill method, there were no significant changes, indicating that the results of the meta-analysis of these indicators were stable. We also performed a cumulative meta-analysis of MN frequency, SCE frequency, and CA frequency by publication time. The results showed that the accuracy of the pooled estimate of effect and 95% CI increased with publication time to become more stable and statistically significant (P < 0.05).

Despite the strengths of our study, we would like to note that our meta-analysis does have several limitations. First, only Chinese and English articles were included, as we did not search for articles in other languages. Second, the time span of this study is 1983−2017, and the results may be influenced by confounding factors. Finally, due to insufficient data, no further analyses were performed on the dose-response relationship between benzene exposure and genetic damage.

We used a thorough meta-analysis to show that occupational benzene exposure can increase the levels of MN frequency, SCE frequency, TM, TL, OTM, T DNA% and CA frequency compared with control groups, and low concentration benzene exposure was also found to increase MN frequency, suggesting that benzene exposure can cause genetic damage. These data provide an important scientific basis for the revision of occupational disease prevention strategies in China. At the same time, attention should be given to health monitoring of the occupational population exposed to benzene, and health management should be strengthened to improve the health of the occupational population.

CNKI: China National Knowledge Infrastructure; MN: Micronucleus; SCE: Sister chromatid exchange; CA: Chromosome aberration; OTM: Olive Tail moment; TM: Tail moment; TL: Tail length; T DNA%: Tail DNA% ; CI: Confidence interval; OSHA: Occupational Safety and Health Administration; SMD: Standard mean difference; PC-STEL: Pemissible concentration-Short Term Exposure Limit; PC-TWA: Permissible concentration-Time Weighted Average.

Acknowledgements

Not applicable.

Funding

This work was supported by the National Natural Science Foundation of China（Grants no. 81573120 , 81730087 , 81872645）. These funding bodies had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript.

Availability of data and materials

All data generated or analysed during this study are included in this published article (and its additional files).

Authors’ contributions

JZ conceived the idea and revised the manuscript. YHZ and KW screened the articles and extracted the data. YHZ analysed the data and wrote the manuscript. BSW reconciled disagreements and provided statistical support. YPP critically revised the manuscript and guided data analysis. All authors reviewed, read and approved the final version before submission.

Ethics approval and consent to participate

Not applicable. Only published reviews were included in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author details

Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of Public Health，Southeast University, Nanjing 210009, Jiangsu, China

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Table 2 Meta-analysis results of the effects of benzene exposure on various genetic damage indicators

Genetic damage index	The number of groups	SMD(95% CI)	P-Value	heterogeneity
Genetic damage index	The number of groups	SMD(95% CI)	P-Value	I²(%)	P-Value
MN frequency	49	1.36(1.084-1.63）	P<0.05	95.7	P<0.1
SCE frequency	21	0.98(0.6-1.36)	P<0.05	91.2	P<0.1
CA frequency	17	0.76(0.49-1.03)	P<0.05	81.8	P<0.1
OTM	5	1.06(0.63-1.50)	P<0.05	80.1	P<0.1
TM	8	0.96(0.34-1.58)	P<0.05	93.9	P<0.1
TL	12	1.78(1-2.56)	P<0.05	95.7	P<0.1
T DNA%	5	1.42(0.66-2.19)	P<0.05	95.2	P<0.1

Table 3 Sensitivity Analysis of Benzene Exposure for Genetic Damage Indicators

Genetic damage index	Random-effects model			Fixed-effects model
Genetic damage index	SMD(95%CI)	Z-value	P-value	SMD (95%CI)	Z-value	P-value
MN frequency	1.36(1.08-1.63）	9.74	P<0.05	0.97(0.91-1.02)	34.76	P<0.05
SCE frequency	0.98(0.6-1.36)	5.02	P<0.05	0.67(0.56-0.78)	11.94	P<0.05
CA frequency	0.76(0.49-1.03)	5.46	P<0.05	0.74(0.63-0.85)	12.84	P<0.05
OTM	1.06(0.63-1.50)	4.81	P<0.05	0.90(0.71-1.08)	9.68	P<0.05
TM	0.96(0.34-1.58)	3.05	P<0.05	0.84(0.69-0.99)	11.16	P<0.05
TL	1.78(1-2.56)	4.48	P<0.05	1.50(1.33-1.66)	18.27	P<0.05
T DNA%	1.42(0.66-2.19)	3.63	P<0.05	1.15(0.98-1.31)	13.69	P<0.05

Table 4 Tests for publication bias

Genetic damage indicators	Begg’s Test		Egger’s Test
Genetic damage indicators	Z-value	P-value	P-value	95%CI
MN frequency	2.95	0.003	0.003	1.67-7.93
SCE frequency	3.20	0.001	0.004	2.24-10.36
CA frequency	0.33	0.742	0.701	-3.94-5.71
OTM	0.98	0.327	0.086	-1.51-12.92
TM	0.99	0.322	0.481	-9.18-17.31
TL	1.78	0.075	0.051	-0.090-28.27
T DNA%	1.47	0.142	0.039	1.57-33.02

Table 5 Combined effects of benzene exposure on MN frequency, SCE frequency and T DNA% before and after publication bias correction by the trim and fill method

Genetic damage index	The number of groups			Q-value	P-value	Effect model	SMD (95%CI)
Genetic damage index	Before trim, and fill		After trim, and fill	Q-value	P-value	Effect model	SMD (95%CI)
MN frequency	49	49		1126.549	<0.05	Random	1.36(1.08-1.63）
SCE frequency	21	21		228.207	<0.05	Random	0.98(0.6-1.36)
T DNA%	5	6		113.919	<0.05	Random	1.15(0.37-1.91)

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Occupational benzene exposure and the risk of genetic damage: a systematic review and meta-analysis

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