Biomarkers of occupational exposure to pesticides: Systematic review of insecticides

Journal Pre-proof Biomarkers of occupational exposure to pesticides: Systematic review of insecticides Suelen Pizzolatto Dalmolin, Danielly Bassani Dreon, Flavia ˜ Thiesen, Eliane Dallegrave Valladao

PII:

S1382-6689(19)30179-6

DOI:

https://doi.org/10.1016/j.etap.2019.103304

Reference:

ENVTOX 103304

To appear in:

Environmental Toxicology and Pharmacology

Received Date:

9 August 2019

Revised Date:

26 October 2019

Accepted Date:

21 November 2019

Please cite this article as: Dalmolin SP, Dreon DB, Thiesen FV, Dallegrave E, Biomarkers of occupational exposure to pesticides: Systematic review of insecticides, Environmental Toxicology and Pharmacology (2019), doi: https://doi.org/10.1016/j.etap.2019.103304

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Biomarkers of occupational exposure to pesticides: Systematic review of insecticides Suelen Pizzolatto Dalmolin1*, Danielly Bassani Dreon2* Flavia Valladão Thiesen3, Eliane Dallegrave2,4 1

Experimental Research Center, Clinical Hospital of Porto Alegre: Graduate Program in Medical Sciences – Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil 2

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Laboratory of Toxicological Research. Graduate Program in Health Sciences - Federal University of Health Sciences of Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil 3

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Health Sciences School, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil 4

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Department of Pharmacosciences - Federal University of Health Sciences of Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil

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*Corresponding authors Highlights

Biomarkers for insecticides are very important to monitoring occupational exposure

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Most of the existing biomarkers for pesticides are non-specific

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Higher prevalence of analyses involving OP insecticides classes

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The protective equipment used is still limited which can increase poisoning risk

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Introduction: Pesticides are widely used around the world, and rural workers have greater risk of poisoning. The use of biomarkers for insecticides can contribute to the diagnosis and

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prevention of poisoning.

Objective: To identify, in the scientific literature, the biomarkers of occupational exposure to insecticides of different insecticide classes. Methods: The PubMed, Lilacs and Embase databases were analyzed using a systematic search strategy and in accordance with the criteria established by the PRISMA methodology. Articles

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with information related to the use of biomarkers to identify active ingredients, or insecticide metabolites, or effects on the human biological matrices were analyzed. Results: A total of 840 studies was found, and 30 met the selection criteria. The search identified 118 results for insecticide biomarkers, of which 45% were of exposure, 42% of effect, and 14% of susceptibility. Additionally, 78 were possible biomarkers, and only 67 confirmed to be different biomarkers for insecticides. Acetylcholinesterase (AChE), butyrylcholinesterase (BuChE) and 3,5,6-trichloro-2-pyridinol (TCP-y), specific for Chlorpyrifos, were among the

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most common biomarkers identified; however, most metabolites found were non-specific. Conclusion: Various insecticide biomarkers were mentioned; nonetheless, only a few are

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specific and used to identify the wide range of insecticides to which farm workers are exposed.

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Key-words: biomarkers, metabolites, insecticides, pesticides, occupational monitoring

1. Introduction

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For centuries, hundreds of types of pesticides have been widely used throughout the world in various contexts, and it is estimated that workers are among the population group most affected

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by insecticides (Abrasco, 2015) due to their proximity to the chemicals and substances during formulation, manufacturing and application (Lionetto et al., 2013). Consequently, the World Health Organization estimates that 70% of pesticide poisoning in the world is a result of

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occupational exposure (Oliveira-Silva et al., 2003; WHO, 2017), causing harm to millions of farm workers every year (Jeyaratnam, 1990). The primary drivers for the increased use of insecticides are related to population growth and the availability of land used for farming (Report Buyer, 2017). Considering that the world population will reach about nine billion people by 2050 (United Nations, 2017), there will be an

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increase in demand for food, directly driving the continuous expansion of food consumption, what in turn may trigger a number of consequences for producers, consumers and the environment by reason of the use of pesticides. In order to control occupational exposure and undue consumption of these compounds, biomarkers have been researched because of their application in the identification of exposure to these agents and their potential for interacting with the biological system and chemical, physical 2

or biological substances (IPCS, 1993). There are biomarkers of exposure, effect and susceptibility (NRC, 1987; IPCS, 1993), all of which are useful in several areas, such as medicine, environmental health, toxicology, developmental biology and scientific research (Lionetto et al., 2013). The identification of biomarkers can be done through the analysis of several biological matrices, in which toxic substances, their metabolites (Anwar, 1997) or an effect – such as enzymatic activity – are detected, thus enabling, in addition to the identification of the substance of interest,

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the assessment of adverse conditions resulting from exposure, even before damages to human health (Amorim, 2003) can be observed. Hence, biomarkers provide evidence that allows the monitoring of physiological and biochemical impacts on the organism (Hook et al., 2014) by

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means of a biological parameter of exposure to these substances (Amorim, 2003).

Knowing the appropriate biomarkers for the identification of insecticides in human biological

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matrices can contribute to a quick and accurate diagnosis. Therefore, this study aimed to conduct a systematic review of the literature on the use of biomarkers to identify the active ingredient,

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metabolites or enzymatic activity related to the mechanism of action of insecticides in humans in different biological matrices. It focused on the evaluation of the following classes of insecticides:

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organophosphorus (OP), carbamates (CRB), pyrethroids (PYR), neonicotinoids and phenylpyrazoles. These insecticides are widely used in diverse fields – representing around 64%

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of the market – and well-known causes of human poisoning (Report Buyer, 2017).

2. Methods

2.1 Description of research

This is a systematic review study, conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology (Galvão et al., 2015). In order

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to identify the articles related to the topic, the reviewers carried out standardized searches in different databases from January 9, 2018 to February 9, 2018, through specific descriptors, with the purpose of compiling information regarding the use of biomarkers used to identify human exposure to the following insecticide classes: OP, CRB, PYR, neonicotinoids and phenylpyrazoles.

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2.2 Identification The descriptors were chosen according to the MeSH term, associated with Boolean operators for better cross-referencing of terms and result obtention, adopting the following search strategy: Humans “AND” insecticides “AND” organophosphorus compounds “OR” pyrethroids “OR” carbamates “OR” imidacloprid “OR” fipronil “AND” biomarkers. The searched databases were PubMed, Lilacs and Embase, which are considered relevant for health research worldwide. Three reviewers were selected to carry out the systematic search for articles.

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2.3 Eligibility At first, the title and abstract of the articles resulting from the search that addressed the

identification of biomarkers of insecticide exposure in humans were considered possibly eligible

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for the reading. For this purpose, eligibility criteria were created by the reviewers in Microsoft Excel. Among these are: use of observational methodology, rural population as subjects,

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published in English or Portuguese, full available texts, exposure to at least one insecticide under study (classes of OP, CRB, PYR, neonicotinoids and/or phenylpyrazoles), and evaluation of

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biomarkers.

Through the analysis of the databases, the application of the search strategies, and the initial

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reading of titles and abstracts, the articles were categorized so they could be read in full at a later time. If the full text of an article was not found in the database being searched, either the article was searched in other databases or the authors were contacted. If none of these strategies yielded

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a result, the article was discarded.

2.4 Selection

In order to extract the data from the articles in their respective databases, another Excel file was created containing the following information: title, authors, language, year of publication, focus

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population, insecticides active ingredient, insecticide class, type of study, type of bioindicator, biomarker and biomarker specificity. Before articles were fully read to confirm eligibility and inclusion in the study, duplicate articles were excluded.

2.5 Methodological quality evaluation

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The articles were divided conforming to their methodological design, then evaluated according to protocol of methodological quality tool from Newcastle-Ottawa Quality Assessment Scale and PEDro tool. The methodological evaluation tools was adapted from quantitative results to qualitative (low, regular and high) in order to facilitate comprehension of the findings.

3. Results The systematic search had a total of 840 results, of which 57 were duplicates, thus providing a total of 783 unique papers for potential inclusion in the current review. After the exclusion

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process, 30 articles were identified for inclusion in the final review, as shown in the flow chart (Figure 1). The main characteristics of studies is presented in Table 1, evidencing the used of

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chlorpyrifos (Table 2) and the lack of use of protective personal equipment (PPE). Besides that, mostly of the studies were transversal (47%) and cohort (43%) studies, the remain was case

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control (7%) and clinical trial (1%). Over all the articles demonstrated good quality, a small percentage (7%) have low quality. The authors choose to keep the articles with low quality

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evaluation in this systematic review because there are ethics factors involved on the experimental design in toxicology studies.

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Regarding the analyses found in this systematic review, 118 insecticide biomarker results were recognized, being 45% biomarkers of exposure, 42% of effect, and 14% of susceptibility. With those analyses, it was noted that there were 78 possible different biomarkers, but the results

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showed that only 67 biomarkers were confirmed (evidenced statistical difference when compared to the control group).

It was observed that the majority of the analyses was performed through blood samples (53%) or urine (43%), and the remaining 4% used other biological matrices, such as saliva, semen and air expired by the worker. The biomarkers identified were usually non-specific: acetylcholinesterase

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(AChE), butyrylcholinesterase (BuChE) and 3,5,6-trichloro-2-pyridinol (TCP-y) (Table 3). Specific biomarkers were observed for carbamate, neonicotinoid, organophosphorus and pyrethroid insecticides, all in urine, with high-level concentrations (Table 4). Furthermore, the results showed that the most used insecticide classes were organophosphorus (54%) and pyrethroids (14%) (Figure 2). The main insecticide active ingredients used in the studies included in this systematic review are shown in Table 3, in which it can be observed that 5

the most common was Chlorpyrifos (75%), and 34% used a mixture of active ingredients; however, 67% of the studies did not specify the insecticide active ingredient. . It is interesting to compare the most researched pesticides with the most widely used pesticides in the study, by country (Table 5). In this context, we realize that despite the increasing use of new generation insecticides the most widely used and researched pesticides worldwide remain the OP. 4. Discussion It is known that around 50% of the world’s labor force is employed in the agriculture chain

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(Maroni et al., 2006). The changes that have occurred in agriculture over the past 50 years, through the increased use of pesticides to enhance crop protection, as well as production, quality and preservation of food (Aktar et al., 2009; Singleton et al., 2015), added to the application in

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the most diverse scopes, expanded the risk of occupational exposure.

Human occupational exposure to insecticides often involves multiple agents (Singleton et al.,

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2015) making it difficult to identify and evaluate the exposure associated with other classes of insecticides, since most evaluations only identify exposure to an active principle or formulated

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product (Abrasco, 2015), corroborating the results of this review, in which 76.7% of the articles assessed one active principle and only 7 studies (23.33%) involved multiple exposure. Therefore,

workers (Galea et al., 2015).

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it is possible that the studies’ participating rural workers are not representative of all rural

Another problem evidenced in occupational exposure is the use of PPE. Filho and Pereira (2011),

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in an interview with rural workers, indicated that, besides 89.9% of the interviewees agreed that pesticides are harmful to health and had knowledge about PPE and its functions, however, these aspects were not enough to motivate the rural workers to use PPE. It's important to point out that, in the same research, only 14.8% of the rural workers learned about PPE with their employer and 43.8% of them reported not having received any information.

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A higher prevalence of analyses involving insecticides of the OP classes (54%) was observed, mainly with a trend of analysis of the active ingredient Chlorpyrifos (CPS) in 30% of the cases, followed by pyrethroid-class analyses (14%), in which several active principles were evaluated, and none highlighted. For the identification of the biomarkers of exposure, it was verified that the majority was analyzed in urine (96%), being these biomarkers, in general, specific for the insecticide class, 6

which is understandable, since the exposure markers are usually the substance or their metabolites. In the case of biomarkers of effect, a prevalence of analyses in blood matrices (96%) was observed, which showed a high frequency of cholinesterase evaluation: 18% of them aimed to determine AChE activity, and 16% BuChE activity. Among biomarkers of susceptibility, 81% of the biomarkers were identified in blood, and 19% in oral fluid. Therefore, despite biomarkers identified in oral fluid being well described in the

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literature as an appropriate tool to evaluate occupational exposure to insecticides in biomonitoring studies (Ballestreri, 2017), this conclusion was not repeated among the authors of

4.1 Biomarkers for organophosphorus (OP) exposure

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the articles selected in this review.

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In the attempt to identify biomarkers of occupational exposure, hepatic enzyme activity has been used since the 1970s to evaluate occupational exposure of workers to the OP class, isolated or in

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association (Albers et al., 2004; Farahat et al., 2011). However, although the study by Jamal et al., (2016) addresses the evaluation of aspartate aminotransferase (AST) and alanine

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aminotransferase (ALT), these enzymes were not found in other studies that related their alteration with exposure to OP and therefore corroborated this information. Considering this context, one of the biomarkers characteristic of human exposure is the

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inhibition of AChE, widely used and recognized as a biomarker of exposure to OP and CRB, as well as the inhibition of BuChE, which is sometimes more strongly inhibited than AChE (Mason, 2000; Lionetto et al., 2013), despite the fact that it is less effective as an indicator of chronic exposure (Kamel and Hoppin, 2004).

Thus, blood evaluation of BuChE as an indicator of OP exposure was described in several

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studies (Albers et al., 2004; Kamel and Hoppin, 2004; Farahat et al., 2011; Crane et al., 2013; Bernal-Hernández et al., 2014; Singleton et al., 2015; Jamal et al., 2016; Ismail et al., 2017), similarly to the assessment of AChE (Mason, 2000; Albers et al., 2004; Farahat et al., 2011; Ogut et al., 2011; Crane et al., 2013; Bernal-Hernández et al., 2014; Singleton et al., 2014; 2015; Jamal et al., 2016; Ismail et al., 2017), which is applicable for monitoring in areas with use of insecticides association (Lionetto et al., 2013). Even though it did present a low correlation in 7

occupational exposure (Amorim, 2003), AChE is considered the biological indicator of choice by the WHO since 1987 (NRC, 1987). Plasma cholinesterase (pChE) was identified as in decrease in one study with dichlorvos (Ndlovu et al., 2014) and cholinesterase (ChE) (Crane et al., 2013; Costa et al., 2014) was considered in Farahat’s et al., (2011) study as an indicator of toxicity by CPS as well, in the same way as other OPs. Their determination was also employed in a study that involved pesticide association (Ndlovu et al., 2014).

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In addition to ChE, the methyl chlorpyrifos metabolite (CP-me), 8-oxo-2'-deoxyguanosine (8OHdG) (Wang et al., 2016) and non-specific dialkyl phosphate (DAP) metabolites, such as

diethyldithiophosphate (DEDTP), diethyl phthalate (DEP), diethylthiophosphoric acid (DETP),

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dimethyldithiophosphate (DMDTP), dimethylthiophosphate (DMTP) and dimethyl phthalate (DMP) (Buchanan et al., 2001; Runkle et al., 2013; Taneepanichskul et al., 2014), have been

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identified.

It is seen that the metabolic route of these agents produces metabolites that are excreted in the

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urine, and, despite their variable specificity, they increase in concentration after occupational exposure (Santos et al., 2013). Among the specific urinary biomarkers of OP, the malathion

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monocarboxylic acid (MMA) metabolite (Tuomainen et al., 2002), 3,5,6-trichloro-2-pyridinol (TPC-y) (Hines and Deddens, 2001; Albers et al., 2004; Kamel and Hoppin, 2004; Aktar et al., 2009; Farahat et al., 2011; Santos et al., 2013; Callahan et al., 2014; Singleton et al., 2015;

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Ndlovu et al., 2014; Singleton et al., 2014; Costa et al., 2015) and 4-bromo-2-chlorophenol (BCP) (Scher et al., 2008; Dadson et al., 2013), when at high levels, were identified in association with the inhibition of BuChE and AChE (Albers et al., 2004; Singleton et al., 2015), corroborating the evidence of the dose-effect relationship between levels of TPCy, BuChE and AChE in occupationally exposed humans found in other study (Farahat et al., 2011).

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Biological indicators of susceptibility for long-term OP exposure, such as the potential use of paroxonase genotyping (PON-1) and the identification of polymorphisms in PON-1 (codon 192 and codon 55) (Bernal-Hernández et al., 2014), are also cited in the literature, and are sometimes associated with AChE activity reduction (Araoud, 2011). PON-1 activities, such as arylesterase (AREase) and cytidine monophosphatase (CMPAse), seem to be biomarkers of susceptibility sensitive to OP-related toxicity (Jamal et al., 2016; Ismail et 8

al., 2017), since CMPAse activity demonstrates association with polymorphisms in PON-1 (Bernal-Hernández et al., 2014). This type of biomarker was identified in 7% of the cases in this review. Some parameters – advanced glycation end products (AGE) and advanced oxidation protein products (AOPP), for instance – demonstrated that this serum’s levels were correlated at the presence of an association between the PON-1 gene polymorphisms, indicating that AOPP levels may mainly provide a novel biomarker for oxidative damage in subjects exposed to OP. Studies support the hypothesis that pesticides induce oxidative stress in populations exposed to

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pesticides (Costa et al., 2015). In addition, the identification of alterations in cytochrome CYP2B6/CYPP2C19 variants, which have the potential to metabolize some chemical agents

(Ellison et al., 2012), are also currently described as good indicators of susceptibility to OP-class

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poisoning.

Hence, in the present review, it was observed that 53% of the studies (Maroni et al., 2006)

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involved exposure to organophosphates, and their exposure was mostly evaluated through the measurement of ChE activity. These results corroborate a study on insecticides carried out in

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China, which indicated that the main agrochemicals used in agriculture in this country are of the organophosphorus and pyrethroid classes (Hu et al., 2015).

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4.2 Biomarkers for carbamate exposure

Although this insecticides class represents one of the main categories of insecticides, for this

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class, only two inespecific metabolites were identified: 1-naphthol and 2-naphthol. The only study found evidenced a clear increase in the rates of 1-naphthol excretion in persons occupationally exposed to this class of insecticide (Bouchard et al., 2008), and, thus, it is considered a biomarker of carbamate poisoning. 4.3 Biomarkers for pyrethroid exposure

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Currently, PYR is one of the most used insecticide classes worldwide (Housset and Dickmann, 2009). The assessment of human exposure to insecticides of the PYR class is often based on the quantification of metabolites in urine (Singleton et al., 2014). For the evaluation of this insecticide class, there are, in the literature, the non-specific urinary biomarkers cis-2,2-(dibromovinyl)-2,2-dimethylcyclopropane carboxylic acid (DBCA), dicarboxylic acid (CDCA), 4-fluoro-3-phenoxybenzoic acid (FPBA) (Couture et al., 2009) and 9

3-phenoxybenzoic acid (3-PBA). 3-PBA is the most generally used for different active principles of PYR (Schettgen et al., 2002; Wang et al., 2007; Couture et al., 2009; Taneepanichskul et al., 2014; Ferland et al., 2015; INCA, 2015; Ratelle et al., 2016), while 2,2-dichlorovinyl-3,3dimethylcyclopropane-1-carboxylic acid (DCVA) (Galea et al., 2015), and cis- and trans-2,2(dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (cDCCA and tDCCA) were described as specific urinary metabolites for certain active principles (Heudorf and Angerer, 2001; Schettgen et al.,, 2002; Elfman et al., 2009; Taneepanichskul et al., 2014; Ferland et al., 2015;

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INCA, 2015). In the last two centuries, there has been a rise in the use of pyrethroids, both in agriculture and in domestic environments (INCA, 2015), probably because of their broad spectrum and relatively

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low toxicity and environmental impact when compared to other classes of insecticides (Ferland et al., 2015). In this review, it was found that, in 17% (Couture et al., 2009; Ferland et al., 2015;

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Costa et al., 2014; Singleton et al., 2014; Ratelle et al., 2016) of the studies, there was PYR

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exposure. 4.4 Biomarkers for neonicotinoid exposure

The class of neonicotinoid is considered the most important synthetic insecticide in the last

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decades. Although the literature indicates that there are no validated biomarkers in the urine for the assessment of exposure to imidacloprid (Elfman et al., 2009), its presence was identified in

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our review through one study that evaluated specific urinary biomarkers, such as 6chloronicotinic acid (6-CNA) and bifenthrin metabolite (MPA) (Harris et al., 2010). When in combination with pyrethroid, one study identified 3-PBA and albumin in urine, as well as in blood (Elfman et al., 2009). However, we did not find indicators of new biomarkers for the evaluation of this insecticide class in this systematic review.

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4.5 Biomarkers for phenylpyrazole exposure As an alternative to pesticide resistance, due to the continuous use of the same classes, mainly OP, CRB and PYR, a new generation of insecticides has a growing use – the phenylpyrazole class (Tingle et al., 2003; Tang et al., 2004), especially fipronil, which is widely used across the world as a broad-spectrum insecticide. However, the studies found in the literature do not match the current reality about occupational exposure, since the new-generation insecticides had low 10

representability in the current systematic review. We did not identify bioindicators for this insecticide class since they should be used to replace some insecticide classes and improve insecticide action, in order to reduce collateral effects. 4.6 Biomarkers for the identification of insecticides association Regarding the association of insecticide classes, we found an evaluation of non-specific biomarkers, such as immunoglobulin E, for asthma, and ChE, which is connected with asthmatic scores (some PYR are allergens), and high levels of fractional exhaled nitric oxide (FeNO)

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(Ndlovu et al., 2014). AChE, BuChE and hemogram were measured in several studies for the evaluation of insecticide association (Bernal-Hernández et al., 2014; Costa et al., 2014; Jamal et

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al., 2016). Parameters of changes in BuChE were related to low levels of leukocytes and high levels of lymphocytes in rural workers when compared to the control group (Bernal-Hernández

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et al., 2014).

Other biochemical parameters – catalase (CAT), AChE activity, glutathione peroxidase,

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superoxide dismutase (SOD) and lipid peroxidation (Ogut et al., 2011), free thyroxin, glucose, luteinising hormone, prolactin, triglycerides, thyroid stimulating hormone, uric acid, AST, ALT, follicle stimulating hormone, cholesterol, creatinine (Jamal et al., 2016) and CMPAase (Bernal-

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Hernández et al., 2014), for instance – were evaluated through blood samples as well. Some results indicate that chronic exposure to the association of OP, CRB and PYR insecticides are

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related with increased CAT, SOD and lipid peroxidation activity in erythrocytes, and may be employed in poisoning assessment (Ogut et al., 2011). To identify urinary metabolites in insecticides association, a kit was also used to detect OP, CRB and PYR (Costa et al., 2014), as well as semen evaluations of occupationally exposed rural workers through the analysis of chromatid sperm, as its harmful effect on fertility has been

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previously described (Jamal et al., 2016). In addition, chromosomal aberrations, chromatid-type aberrations, micronuclei assay (MN), micronuclei in reticulocytes (MN-RET), comet assay (Costa et al., 2014), molecular cytogenetics and sister chromatid exchange (Aiassa et al., 2012; Singleton et al., 2014) were mentioned in the selected studies as biomarkers of susceptibility. There are indications that exposed workers present a significant increase in the number of micronuclei in lymphocytes and reticulocytes, 11

chromosomal aberrations, DNA damage and a significant reduction in the proportion of Blymphocytes when compared to the control group of the studies (Costa et al., 2014). Furthermore, the evaluation of different genetic polymorphisms related to metabolism, such as EPHX-1 (codon 113, codon 139), GSTM1, GSTP1 (codon 105), GSTT, mutation test of T-cell receptor (TCR), XRCC1 (codon 194, codon 399, codon 188), and the evaluation of lymphocytic subpopulations were found in the literature (Costa et al., 2014). 5. Conclusion

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Biomarker research to evaluate insecticide exposure contributes to the knowledge of the effects of the compounds on the organism and to the selection of the most suitable biomarker for

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evaluation – for efficient monitoring of human exposure –, given the hundreds of thousands of tons of pesticides used worldwide (Abass, 2014).

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Despite of the increased use of insecticides in all settings, it is noted that there is still limited evidence regarding new biomarkers for the evaluation of exposure, its impact, and diagnosis and treatment of poisoning caused by these agents.

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It can be noticed that, in spite of the identification of 68 biomarkers – of susceptibility (12), exposure (24) and effect (32) –, only 6 specific biomarkers were found, all in urine. The majority

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were biomarkers of exposure, and only 1 of effect. The insecticide classes included in these specific biomarkers were carbamate (carbaryl), neonicotinoid (imidacloprid), organophosphorus

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(chlorpyrifos, profenophos and malathion) and pyrethroid (α-cypermethrin). Considering the large size of the global workforce, the estimates for the growth in human population and the use of insecticides increasing (including new products) associated at fact that their use frequently involves the association of different pesticides, there is a growing need for studies to broaden their risk evaluation. In this way, it would be possible to expand specificities

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and provide valuable information so that health professionals can deal with patients involved in exposure and poisoning, especially in the occupational field. Given this scenario, public health authorities are interested in identifying the best methods available to evaluate insecticide exposure. Therefore, it is important to define biomarkers, as well as the biological matrices in which they are measured, before establishing standardized protocols for occupational exposure monitoring. The use of protocols should be facilitate a faster and accurate diagnosis, improving care of occupationally exposed workers. 12

Study limitations This systematic review about biomarkers of exposure to insecticides in humans occupationally exposed included only articles in Portuguese and English and the gray literature articles were not researched. The analysis of the methodological quality was low because articles in the area of toxicology present methodological limitations due to ethical factors, as for the number, sample and control of exposure

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Support/funding This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) for fellowships. Conflicts of interest None.

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Contributions Suelen Pizzolatto Dalmolin and Danielly Bassani Dreon contribute equally for the paper. All authors approve the final version of the manuscript.

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Acknowledgements We would like to thank to Federal University of Health Sciences of Porto Alegre and Pontifical Catholic University of Rio Grande do Sul for technical support.

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References

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Abass, K.S., 2014. Experimental measurements for the effect of dilution procedure in blood esterases as animals biomarker for exposure to OP compounds. BioMed research international. 2014, 451982. http://dx.doi.org/10.1155/2014/451982. Aiassa D., Mañas, F., Bosch, B., Gentile, N., Bernardi, N., Gorla, N., 2012. Biomarcadores de daño genético en poblaciones humanas expuestas a plaguicidas. Acta Biológica Colombiana, 17(3), 485–510. http://dx.doi.org/10.15446/abc. Aktar, M.W., Sengupta, D. and Chowdhury, A., 2009. Impact of pesticides use in agriculture: their benefits and hazards. Interdisciplinary Toxicology. 2(1), 10.2478/v10102-009-0001-7. https://dx.doi.org/10.2478/v10102-009-0001-7. Albers, J.W., Berent S., Garabrant D.H., Giordani B., Schweitzer S.J., Garrison R.P., Richardson R.J., 2004. The effects of occupational exposure to chlorpyrifos on the neurologic examination of central nervous system function: a prospective cohort study. Journal of Occupational and Environmental Medicine. 46(4), 367– 378. http://dx.doi.org/10.1097/01.jom.0000121127.29733.5c. Amorim, L.C.A, 2003. O Uso dos Biomarcadores na Avaliação da Exposição Ocupacional a Substâncias Químicas. Revista Brasileira de Medicina do Trabalho. 1(2), 124–32. http://dx.doi.org/10.1590/S1415790X2003000200009.

lP

re

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Anwar, W.A., 1997. Biomarkers of human exposure to pesticides. Environmental Health Perspectives. 105, 801–806. https://doi.org/10.2307/3433286. Aprea, C., Strambi, M., Novelli, M. T., Lunghini, L., & Bozzi, N., 2000. Biologic monitoring of exposure to organophosphorus pesticides in 195 Italian children. Environmental health perspectives, 108(6), 521–525. doi:10.1289/ehp.00108521. Araoud, M, 2011. Biological Markers of Human Exposure to Pesticides. Environmental Health Perspectives. 05(Suppl 4): 801–806. https://doi.org/10.1289/ehp.97105s4801. Ballestreri, E., 2017. Teste de micronúcleos como ferramenta para avaliação da exposição ocupacional a pesticidas: revisão. Revista Intertox de Toxicologia, Risco Ambiental e Sociedade, 10(1). https://doi.org/10.22280/revintervol10ed1.260.

Jo

ur na

Bernal-Hernández, Y., Medina-Díaz, I., Barrón-Vivanco, B., Robledo-Marenc, M., Girón-Pérez, M., PérezHerrera, N., Quintanilla-Veja, B., Cerda-Flores, R., Rojas-García, A., 2014. Paraoxonase 1 and its relationship with pesticide biomarkers in indigenous Mexican farmworkers. Journal of Occupational and Environmental Medicine. 56(3). 281–290. https://doi.org/10.1097/01.jom.0000438381.25597.88. Bouchard, M., Carrier, G. and Brunet, R.C., 2008. Assessment of absorbed doses of carbaryl and associated health risks in a group of horticultural greenhouse workers. International Archives of Occupational and Environmental Health [online], 81(3), 355–70. https://doi.org/10.1007/s00420-007-0220-1. ABRASCO - Brazilian Association of Post-Graduation in Collective Health, 2015. Dossiê Abrasco – Os Impactos dos Agrotóxicos na Saúde. http://abrasco.org.br/dossieagrotoxicos/ (accessed 15 November 2017). Buchanan, D., Pilkington A., Sewell C., Tannahill S.N., Kidd M.W. , Cherrie B., Hurley J.F., 2001. Estimation of cumulative exposure to organophosphate sheep dips in a study of chronic neurological health effects among United Kingdom sheep dippers. Occupational and Environmental Medicine. 58(11), 694-701. https://doi.org/10.1136/oem.58.11.694. Callahan, C.L., Al-Batanony, M., Ismail A.A., Abdel-Rasoul, G., Hendy, O., Olson, J.R., Rohlman, D.S., Bonner, M.R., 2014. Chlorpyrifos Exposure and Respiratory Health among Adolescent Agricultural Workers. International Journal of Environmental Research and Public Health. 11(12), 13117-13129. https://doi.org/10.3390/ijerph111213117 Costa, C., Gangemi, S., Giambò, F., Rapisarda, V., Caccamo D., Fenga, C., 2015. Oxidative stress biomarkers and paraoxonase 1 polymorphism frequency in farmers occupationally exposed to pesticides. Molecular Medicine Reports. 12(4), 6353-6357. https://doi.org/10.3892/mmr.2015.4196. 14

re

-p

ro

of

Costa, C., García-Lestón, J., Costa, S., Coelho, P., Silva, S., Pingarilho, M., Valdiglesias, V., Mattei, F., Dall'Armi, V., Bonassi, S., Laffon, B., Snawder, J., Teixeira, J. P., 2014. Is organic farming safer to farmers’ health? A comparison between organic and traditional farming. Toxicology Letters. 230(2). 166– 76. https://doi.org/10.1016/j.toxlet.2014.02.011. Couture, C., Fortin, M. C., Carrier, G., Dumas, P., Tremblay, C., Bouchard, M., 2009. Assessment of Exposure to Pyrethroids and Pyrethrins in a Rural Population of the Montérégie Area, Quebec, Canada. Journal of Occupational and Environmental Hygiene. 6(6), 341-352. https://doi.org/10.1080/15459620902850907. Crane, A.L.., Abdel Rasoul, G., Ismail, A.A., Hendy, O., Bonner, M.R., Lasarev, M.R., Al-Batanony, M., Singleton, S.T., Khan, K., Olson, J.R., Rohlman, D.S., 2013. Longitudinal assessment of chlorpyrifos exposure and effect biomarkers in adolescent Egyptian agricultural workers. Journal of Exposure Science & Environmental Epidemiology. 23(4), 356–362. https://doi.org/10.1038/jes.2012.113. Elfman, L., Hogstedt, C., Engvall, K., Lampa, K., Lindh, C.H., 2009. Acute Health Effects on Planters of Conifer Seedlings Treated with Insecticides. The Annals of Occupational Hygiene. 53(4), pp. 383–90. https://doi.org/10.1093/annhyg/mep016. Ellison, C.A., El-Ella, S.S.A., Tawfik, M., Lein, P.J., Olson, J.R., 2012. Allele and Genotype Frequencies of CYP2B6 and CYP2C19 Polymorphisms in Egyptian Agricultural Workers. Journal of Toxicology and Environmental Health, Part A. 75(4), 232–241. https://doi.org/10.1080/15287394.2012.641201. Farahat, F.M., Ellison, C.A., Bonner, M.R., McGarrigle, B.P., Crane, A.L., Fenske, R.A., Lasarev, M.R., Rohlman, D.S., Anger, W.K., Lein, P.J., Olson, J.R., 2011. Biomarkers of Chlorpyrifos Exposure and Effect in Egyptian Cotton Field Workers. Environmental Health Perspectives. 119(6), 801–806. https://doi.org/10.1289/ehp.1002873. Ferland, S., Côté, J., Ratelle, M., Thuot, R., Bouchard, M., 2015. Detailed Urinary Excretion Time Courses of Biomarkers of Exposure to Permethrin and Estimated Exposure in Workers of a Corn Production Farm in Quebec, Canada. Annals of Occupational Hygiene. 59(9),1152–67. https://doi.org/10.1093/annhyg/mev059

Jo

ur na

lP

Galea, K.S., MacCalman, L., Jones, K., Cocker, J., Teedon, P., Cherrie, J.W., van Tongeren, M., 2015. Urinary biomarker concentrations of captan, chlormequat, chlorpyrifos and cypermethrin in UK adults and children living near agricultural land. Journal of Exposure Science & Environmental Epidemiology. 25(6), 623–631. https://doi.org/10.1038/jes.2015.54. Galvão, T.F., Pansani, T.S.A., Harrad, D., 2015. Principais itens para relatar Revisões sistemáticas e Meta-análises: A recomendação PRISMA. Epidemiologia e Serviços de Saúde. Ministério da Saúde do Brasil. 24(2), 335–42. http://dx.doi.org/10.5123/S1679-49742015000200017. Garcıá de Llasera, M.P., Bernal-González M., 2001. Presence of carbamate pesticides in environmental waters from the northwest of Mexico: determination by liquid chromatography. Water Research. 35 (8), 1933-1940. https://doi.org/10.1016/S0043-1354(00)00478-4. Greenpeace Research Laboratories, School of Biosciences, Innovation Centre Phase 2, University of Exeter, Exeter, 2019. https://www.exeter.ac.uk/research/partnership/greenpeace/ (accessed 19 october 2019). Harris, S.A., Villeneuve, P.J., Crawley, C.D., Mays, J.E., Yeary, R.A., Hurto, K.A., Meeker, J.D., 2010. National Study of Exposure to Pesticides among Professional Applicators: An Investigation Based on Urinary Biomarkers. Journal of Agricultural and Food Chemistry .58(18), 10253– 10261. http://dx.doi.org/ 10.1021/jf101209g. Heudorf, U., Angerer, J., 2001. Metabolites of pyrethroid insecticides in urine specimens: current exposure in an urban population in Germany. Environmental Health Perspectives. 109(3), 213–217. http://dx.doi.org/10.1289/ehp.01109213. Hines, C.J., Deddens, J.A., 2001. Determinants of chlorpyrifos exposures and urinary 3,5,6-trichloro-2-pyridinol levels among termiticide applicators. The Annals of Occupational Hygiene. 45(4), 309–321. 15

re

-p

ro

of

Hook, S.E., Gallagher, E.P., Batley, G.E., 2014. The role of biomarkers in the assessment of aquatic ecosystem health. Integrated Environmental Assessment and Management. 10(3), 327–341. https://doi.org/10.1002/ieam.1530. Housset, P., Dickmann, R., 2009. A promise fulfilled - pyrethroid development and the benefits for agriculture and human health. Bayer CropScience Journal 62(2), 135-144. Hu, R., Huang, X., Huang, J., Li, Y., Zhang, C., Yin, Y., Chen, Z., Jin, Y., Cai, J., Cui, F., 2015. Long- and ShortTerm Health Effects of Pesticide Exposure: A Cohort Study from China. PLOS ONE. 10(6), 1-13. https://doi.org/10.1371/journal.pone.0128766 IPCS - International Programme on Chemical Safety, 1993. World health organization. Environmental Health Criteria 155. Biomarkers and Risk Assessment: Concepts and Principles. 154(106). http://apps.who.int/iris/bitstream/10665/39037/1/9241571551-eng.pdf (accessed 19 March 2018). Ismail, A.A, Wang, K., Olson, J.R., Bonner, M.R., Hendy, O., Abdel Rasoul, G., Rohlman, D.S., 2017. The impact of repeated organophosphorus pesticide exposure on biomarkers and neurobehavioral outcomes among adolescent pesticide applicators. Journal of Toxicology and Environmental Health. Part A, 80(10– 12), 542–555. https://doi.org/10.1080/15287394.2017.1362612. Jamal, F., Haque, Q.S, Singh, S,, Rastogi, S.K., 2016. The influence of organophosphate and carbamate on sperm chromatin and reproductive hormones among pesticide sprayers; Toxicology and Industrial Health. 32(8), 1527–1536. https://doi.org/10.1177/0748233714568175. Jeyaratnam, J., 1990. Acute pesticide poisoning: a major global health problem. World Health Statistics Quarterly. 43(3), 139–44. Kamel, F., Hoppin, J.A.,2004. Association of pesticide exposure with neurologic dysfunction and disease. Environmental Health Perspectives. 112(9), 950–958. https://doi.org/10.1289/ehp.7135. Lionetto, M.G., Caricato, R., Calisi, A., Giordano, M.E., Schettino, T., 2013. Acetylcholinesterase as a biomarker in environmental and occupational medicine: new insights and future perspectives. BioMed Research International. 1-9. http://dx.doi.org/10.1155/2013/321213.

lP

Maroni, M., Fanetti, A.C., Metruccio, F., 2006. Risk assessment and management of occupational exposure to pesticides in agriculture. La Medicina del Lavoro. 97(2), 430–437. Mason, H. J., 2000. The recovery of plasma cholinesterase and erythrocyte acetylcholinesterase activity in workers after over-exposure to dichlorvos. Occupational Medicine. 50(5), 343–347. https://doi.org/10.1093/occmed/50.5.343

Jo

ur na

Mansour, S.A., 2008. Environmental Impact of Pesticides in Egypt. In: Whitacre D. (eds) Reviews of Environmental Contamination and Toxicology Vol 196. Reviews of Environmental Contamination and Toxicology (Continuation of Residue Reviews), vol 196, 1-5. https://doi.org/10.1007/978-0-387-78444-1_1. Narayan, S., Liew Z., Paul K., Lee PC, Sinsheimer JS, Bronstein JM, Ritz., 2013. Household organophosphorus pesticide use and Parkinson's disease. International journal of epidemiology, 42(5), 1476–1485. doi:10.1093/ije/dyt170. National Cancer Institute - (INCA) - Comunicação e Informação - Brasil lidera o ranking de consumo de agrotóxicos. http://www2.inca.gov.br/wps/wcm/connect/comunicacaoinformacao/site/home/namidia/brasil_li dera_ranking_consumo_agrotoxicos (accessed 15 November 2017). Norén, E., Larsson, E., Littorin, M., Maxe, M., Jönsson, B. A. G., Lindh, C. H., 2017. Biomonitoring of organophosphorus flame retardants in a Swedish population – Results from four investigations between years 2000 – 2013. Rapport till Naturvårdsverket.. Ndlovu, V., Dalvie, M.A., Jeebhay, M.F., 2014. Asthma associated with pesticide exposure among women in rural Western Cape of South Africa. American Journal of Industrial Medicine. 57(12), 1331–1343. https://doi.org/10.1002/ajim.22384. 16

NRC - Information Notices – 1987, 2016. Unite States Nuclear Regulatory Commission. https://www.nrc.gov/reading-rm/doc-collections/gen-comm/info-notices/1987/ 22384 (accessed 09 Feb 2019).

ro

of

Ogut, S., Gultekin, F., Kisioglu, A.N., Kucukoner, E., 2011. Oxidative stress in the blood of farm workers following intensive pesticide exposure. Toxicology and Industrial Health. 27(9), 820– 882. https://doi.org/10.1177/0748233711399311 Panuwet, P., Siriwong, W., Prapamontol, T., Ryan, P. B., Fiedler, N., Robson, M. G., and Barr, D. B., 2012. Agricultural Pesticide Management in Thailand: Situation and Population Health Risk. Environmental science & policy. 17:72–81. doi:10.1016/j.envsci.2011.12.005. Pérez, J.J., Ortiz, R., Ramírez, M.L., Olivares, J., Ruíz, Daniel., Montiel, D., 2016. Presence of organochlorine pesticides in xoconostle (Opuntia joconostle) in the central region of Mexico. Food Contamination. 3 (21). https://doi.org/10.1186/s40550-016-0044-4 Ratelle, M., Côté, J., Bouchard, M., 2016. Time courses and variability of pyrethroid biomarkers of exposure in a group of agricultural workers in Quebec, Canada. International Archives of Occupational and Environmental Health. 89(5), 767–783. https://doi.org/10.1007/s00420-0161114-x.

re

-p

Report Buyer, 2017. Global Insecticides Market 2021: Emerging Trends, Market Dynamics and Strategic Assessments of Leading Suppliers. https://www.reportbuyer.com/product/5208512/global-insecticidesmarket-2021-emerging-trends-market-dynamics-and-strategic-assessments-of-leading-suppliers.html (Accessed 09 Feb 2019). Runkle, J.D., Tovar-Aguilar, J.A., Economos, E., Flocks, J., Williams, B., Muniz, J.F., Semple, M., McCauley, L., 2013. Pesticide Risk Perception and Biomarkers of Exposure in Florida Female Farmworkers. Journal of Occupational and Environmental Medicine. 55(11), 1286–92. https://doi.org/ 10.1097/JOM.0b013e3182973396.

ur na

lP

Quinn, L.P., de Vos B, J., Fernanders-Whaley, M., Roos,C., Bowman H., Kylin, H., Pieters and R. van der Berg J., 2011. Pesticide Use in South Africa. One of the largest importers of pesticide in Africa. In book: Pesticides in the Modern World - Pesticides Use and Management. Margarita Stoytcheva (Ed.), ISBN: 978-953-307-459-, inTech. DOI: 10.5772/16995. Santos, M.G., Vitor, R.V., Nakamura, M.G., Morelini, L.D.S., Ferreira, R.S., Paiva, A.G., Azevedo, L., Marques, V.B.B., Martins, I., Figueiredo, E.C., 2013. Study of the correlation between blood cholinesterases activity, urinary dialkyl phosphates, and the frequency of micronucleated polychromatic erythrocytes in rats exposed to disulfoton. Brazilian Journal of Pharmaceutical Sciences. 49(1), 149–54. http://dx.doi.org/10.1590/S1984-82502013000100016.

Jo

Scher, D.P., Sawchuk, R.J., Alexander, B.H., Adgate, J.L., 2008, Estimating Absorbed Dose of Pesticides in a Field Setting Using Biomonitoring Data and Pharmacokinetic Models. Journal of Toxicology and Environmental Health. Part A. 71(6), 373–383. http://dx.doi.org/10.1080/15287390701801638. Schettgen, T., Heudorf, U., Drexler, H., Angerer J., 2002. Pyrethroid exposure of the general population-is this due to diet. Toxicology Letters. 134(1–3), pp. 141–145. https://doi.org/10.1016/S0378-4274(02)00183-2 Singleton, S.T., Lein, P.J., Dadson, O.A., McGarrigle, B.P., Farahat, F.M., Farahat, T., Bonner, M.R., Fenske, R.A., Galvin, K., Lasarev, M.R., Anger, W.K., Rohlman, D.S., Olson, J.R., 2015. Longitudinal assessment of occupational exposures to the organophosphorous insecticides chlorpyrifos and profenofos in Egyptian cotton field workers. International Journal of Hygiene and Environmental Health. 218(2), 203–211. https://doi.org/10.1016/j.ijheh.2014.10.005.

Singleton, S.T., Lein, P.J., Farahat, F.M., Farahat, T., Bonner, M.R., Knaak, J.B., Olson, J.R., 2014. Characterization of α-cypermethrin exposure in Egyptian agricultural workers. International Journal of Hygiene and Environmental Health. 217(4–5), 538–545. https://doi.org/10.1016/j.ijheh.2013.10.003. 17

Srinivas Rao, Ch., Venkateswarlu, V., Surender, T., Eddleston, M., Buckley, NA., 2005. Pesticide poisoning in south India: opportunities for prevention and improved medical management. Tropical medicine & international health. 10(6):581–588. doi:10.1111/j.13653156.2005.01412.x.

of

Taneepanichskul, N., Norkaew, S., Siriwong, W., Siripattanakul-Ratpukdi, S., Maldonado Pérez, H.L., Robson, M.G., 2014. Organophosphate pesticide exposure and dialkyl phosphate urinary metabolites among chili farmers in northeastern Thailand. Roczniki Panstwowego Zakladu Higieny. 65(4), 291–9. Tang, J., Usmani, K.A., Hodgson, E., Rose, R.L., 2004. In vitro metabolism of fipronil by human and rat cytochrome P450 and its interactions with testosterone and diazepam. Chemico-Biological Interactions. 147(3), 319–329. https://doi.org/10.1016/j.cbi.2004.03.002. Tingle, C.C., Rother, J.A., Dewhurst, C.F., Lauer, S., King, W.J., 2003. Fipronil: environmental fate, ecotoxicology, and human health concerns. Reviews of Environmental Contamination and Toxicology. 176, 1–66.

ro

Tuomainen, A., Kangas, J.A., Meuling, W.J., Glass, R.C., 2002. Monitoring of pesticide applicators for potential dermal exposure to malathion and biomarkers in urine. Toxicology Letters. 134(1– 3),125–32. https://doi.org/10.1016/S0378-4274(02)00181-9. Teixeira, H., Proença, P., Alvarenga, M., Oliveira M., Marques, E. P., Vieiram D. N., 2004. Pesticide intoxications in the Centre of Portugal: three years analysis. Forensic Science International. 143(2-3), 199-204. https://doi.org/10.1016/j.forsciint.2004.02.037.

-p

United Nations, World Population Prospects - Population Division, 2017. https://esa.un.org/unpd/wpp/ (accessed 25 July 2018).

lP

re

Van Balen, E. C., Wolansky, M. J., Kosatsky T., 2012. Increasing use of pyrethroids in Canadian households: should we be concerned? Canadian Journal Public Health. 103(6): e404–e407. Published online 2012 Nov 7. DOI: 10.1007/BF03405626. · Ye, M., Beacha, J., Martin, J. W., Senthilselvana, A., 2015. Associations between dietary factors and urinary concentrations of organophosphate and pyrethroid metabolites in a Canadian general population. International Journal of Hygiene and Environmental Health. 218(7), 616-626. https://doi.org/10.1016/j.ijheh.2015.06.006.

Jo

ur na

Wang, D., Kamijima, M., Imai, R., Suzuki, T., Kameda, Y., Asai, K., Okamura, A., Naito, H., Ueyama, J., Saito, I., Nakajima, T., Goto, M., Shibata, E., Kondo, T., Takagi, K., Takagi, K., Wakusawa, S., 2007. Biological monitoring of pyrethroid exposure of pest control workers in Japan. Journal of Occupational Health. 49(6), 509–514. https://doi.org/10.1539/joh.49.509. Wang, L., Liu, Z., Zhang, J., Wu, Y., Sun, H., 2016. Chlorpyrifos exposure in farmers and urban adults: Metabolic characteristic, exposure estimation, and potential effect of oxidative damage. Environmental Research. 149, 164–70. https://doi.org/10.1016/j.envres.2016.05.011. WHO - World Health Organization, 2017. Insecticide resistance. http://www.who.int/malaria/areas/vector_control/insecticide_resistance/en/ (accessed 19 March 2018).

18

Figure 1: Flowchart PRISMA of identification and selection of systematic review about biomarkers of insecticides in occupationally exposed humans.

lP

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Pre-selected articles 783

Complete articles reviewed 30

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Studies removed for duplicity 57

of

Studies identified from search in databases: Pubmed- 736 Lilacs- 5 Embase- 99 Totality: 840

Excluded records:

Population: 570 Exposition: 166 Absctract/articles not available: 14 Language: 12 Search designing: 16 Other biomarkers: 5

ur na

No. =

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Studies included in the review 30

19

of ro

Jo

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Fig. 2. The most used insecticide classes found in the systematic review.

20

Table 1. Characteristics of studies included in the systematic review. Gender

Age (years)

Inseticide Class

Crop type

Contact with the insecticide

PPEs

Citation

Crosssectional

-

18-70

Pyrethroid

Not specified

Lived nearby

Not reported

Couture et al. (2009)

Crosssectional

Male

14-69

Organophosphorus

Not specified

Not specified

Not reported

Ellison et al. (2012)

Crosssectional

Female

-

Not specified

Not specified

Rural workers or lived nearby

Not specified

Crosssectional

Male and female

28-50

Pyrethroid

Sweet corn

Harvesters, applicator or supervisor

Yes

Crosssectional

Male and female

-

Organophosphorus

Not specified

Farm family members; lived on the farm

Yes

Scher et al. (2008)

Crosssectional

-

-

Organophosphorus

Cotton

Applicator, technician or engineer

Not reported

Dadson et al. (2013)

Crosssectional

Male and female

-

Organophosphorus

Not specified

Greenhouse applicators

Yes

Tuomainen et al. (2002)

Crosssectional

Male

19-65

Mixture of pesticides

Not specified

Not specified

Not specified

Costa et al. (2015)

Mixture of pesticides

Not specified

Farmworker

Not specified

BernalHernández et al. (2014)

-

-

Ndlovu et al. (2014)

ro

-p

re

lP

ur na

Jo

Crosssectional

of

Study type

Ferland et al. (2015)

21

Female

18-40

Organophosphorus

Not specified

Hispanic and Haitian farmworkers

Not specified

Runkle et al. (2013)

Crosssectional

Male

18-52

Mixture of pesticides

Not specified

Sprayers

Not reported

Jamal et al. (2015)

Crosssectional

Male and female

18-83

Mixture of pesticides

Not specified

Residents and workers

Not reported

Galea et al. (2015)

Crosssectional

Male and female

-

Carbamate

Horticultu ral

Greenhouse worker

Yes

Crosssectional

-

-

Organophosphorus

Sheep dippers

Plunger, chucker helper

Control case

Male and female

25-54

Pyrethroid

Not specified

Control case

Male and female

35-39

Mixture of pesticides

Cohort

-

15-55

Cohort

-

14-36

ro

Bouchard, Carrier, Brunet. (2008)

Buchanan et al. (2001)

Not specified

Yes

Costa et al. (2014)

Not specified

formulating workers

Not reported

Ogut et al. (2011)

Organophosphorus

Cotton

Applicator, technician or engineer

Yes

Farahat et al. (2011)

Pyrethroid

Cotton

Applicator, technician or engineer

Not reported

Singleton et al. (2014)

lP

re

-p

Yes

ur na

Jo

of

Crosssectional

Cohort

Male

12-21

Organophosphorus

Cotton

Applicators

Yes

Callahan et al. (2014)

Cohort

Male and female

-

Organophosphorus

Not specified

Spraying

Not reported

Wang et al. (2016)

22

-

-

Organophosphorus

Not specified

Termiticide applicators

Yes

Hines e Deddens (2001)

Cohort

Male

12-21

Organophosphorus

Cotton

Sprayers

Not reported

Crane et al. (2013)

Cohort

Male

19-59

Neonicotinoid

Not specified

Turf applicators

Not specified

Harris et al. (2010)

Cohort

Male and female

33-47

Organophosphorus

Chili

Not specified

Not reported

Cohort

Male and female

18-65

Organophosphorus

Not related

Employees

Cohort

-

12-21

Organophosphorus

Cotton crop

Cohort

-

-

Organophosphorus

Cohort

-

-

Organophosphorus

Cohort

Male and female

Clinical Trial

-

-

ro

Taneepanic hskul et al. (2014)

-p

Not reported

Albers et al. (2004)

Not reported

Ismail et al. (2017)

Cotton crop

Applicators, technicians, engineers

Not reported

Singleton et al. (2015)

Not specified

Not specified

Not reported

Mason (2000)

Pyrethroids

Not reported

Not specified

Yes

Ratelle, Côté, Bouchar. (2016)

Mixture of pesticides

Conifer seedlings

Planters

Not specified

Elfman et al. (2009)

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Pesticide applicators

ur na

Jo

25-63

of

Cohort

Yes - Article demonstrated results of PPE analysis Not specified - Article related to query about PPE use but did not show results or discussion of this matter Not reported - Article did not reported PPE

23

% 30% 23%

Active ingredient association

5

17%

Alpha-cypermethrin

1

3%

Carbaryl

1

3%

Cypermethrin

1

3%

Diazinon

1

3%

Dichlorvos

1

3%

Imidacloprid

1

3%

Malathion

1

3%

Permethrin

1

3%

Prophenophos

1

3%

TOTAL

30

100%

ro

Studies 9 7

Jo

ur na

lP

re

-p

Insecticide Chlorpyrifos Not specified

of

Table 2. Active ingredients found in the review.

24

Table 3. Information about occupational exposure biomarkers of insecticides summarized from the literature. Insecticides Active principle

Class

Biomarker Type of bioindicator

Matri x

Reference

Biomarker

Results

Specifity

Citation

Increase

No

Bouchard, Carrier and Brunet, 2008

Increase

Yes

Harris et al., 2010

Carbaryl

Exposure

Urine

Neonicotinoid

Imidacloprid

Exposure

Urine

Susceptibilit y

Blood

2-Naphthol MPA-6 CNA CYP2B6 CYPP2C19

Present

No

-p

ro

Carbamate

Chlorpyrifos

Jo Profenophos

DETP DEP CP-me

Increase

No

Present

No

8-OHdG

Increase

No

Wang et al., 2016

Decrease

No

Farahat et al., 2011

Urine

ur na

Organophosph orus

Yes

lP

Exposure

Increase

re

TPCy

Effect

DEDTP

ChE

Blood

BChE CYP3A4

Taneepanic hskul et al., 2014

Decrease

No

Farahat et al., 2011; Crane et al., 2013; Ismail et al., 2017; Albers et al., 2004

Present

No

Dadson et

Blood AChE

Susceptibilit

Ellison et al., 2012 Callahan et al., 2014; Wang et al., 2016; Hines and Deddens, 2001; Scher et al., 2008; Crane et al., 2013; Farahat et al., 2011; Ismail et al., 2017; Albers et al., 2004; Singleton et al., 2015; Galea et al., 2015

of

1-Naphthol

25

y

al., 2013

CYP2B6 CYP2C19 BCP

Exposure

Urine

Chlorpyrifos + Profenophos

Effect

Blood

Diazinon

Exposure

Urine

Dichlorvos

Effect

Blood

AChE

Increase

Yes

Decrease

No

Singleton et al., 2015

Increase

No

Buchanan et al., 2001

Decrease

No

Mason, 2000

DEP DETP

AChE Malathion

Effect

Urine

MMA

Increase

DEP Urine

DMP DMTP

Tuomainen et al., 2002

No

Runkle et al., 2013

No

Costa et al., 2015

No

Galea et al., 2015

No

Ratelle, Côté and Bouchard, 2016

Increase

Yes

Singleton et al., 2014

Increase

No

Ferland et al., 2015

Increase

No

Increase

-p

Exposure

Yes

ro

DAP

of

BuChE

ChE

Singleton et al., 2015; Dadson et al., 2013

DETP N/I Effect

re

DMDTP AGE

Blood

lP

Susceptibilit y

AOPP PON1 gene polymorphi sm

ur na

Cis-DCVA

Cypermethri n

αCypermethri n

Jo

Pyrethroid

Permethrin

N/I

Exposure

Exposure

Decrease Present

Increase

TransDCVA

Urine

Cis-DCCA Increase TransDCCA 3-PBA

Urine

Cis-DCCA 3-PBA 3-PBA

Exposure

Exposure

Urine

Urine

Cis-DCCA TransDCCA Urinary PYR Cis-DCCA Trans-

No

Costa et al., 2014 Couture et al., 2009

26

DCCA 3-PBA

Increase

CDCA DBCA FPBA

Effect

Blood

Susceptibilit y

Blood

Exposure

Urine

Effect

Blood

Decrease

IGE asthma specific PON-1 activity (AREase and CMPAase) Urinary OP and CRB BuChE

Decrease

Increase Decrease

No

No

-p

re

No

Costa et al., 2014

BernalHernández et al., 2014

Increase

ALT

N/I

Creatinine

Blood

Jo

ur na

Effect

Carbamate + Organophosph orus + Pyrethroid

BernalHernández et al., 2014

Decrease

lP

Carbamate + Organophosph orus

Leukocytes Lymphocyt es AST

No

Present

AChE BuChE

No

Ndlovu, Dalvie and Jeebhay, 2014

of

N/I

Increase

pChE

ro

Pesticides in general

FeNO

N/I

Susceptibilit y

Uric acid

Cholesterol Triglyceride s Glucose FSH LH

No

Jamal et al., 2016*

Increase

PRL TSH Seme n

Blood

FT4 Sperm chromatin Gene EPHX-1Codon 139 Gene EPHX-1Codon 113 GSTP1Codon 105

Decrease

No

Present

No

Costa et al., 2014

27

GSTM1

of ro

Decrease Present

-p

Blood

Increase

No

Increase

ur na

lP

re

Effect

GSTT 1 XRCC1Codon 194 XRCC1Codon 399 XRCC2Codon 188 ARG/HIS Chromatidtype aberrations Chromosom al aberrations B lymphocyte s DNA damage TCR mutation MN (lymphocyt es and reticulocyte s) BuChE Lymphocyt e subpopulati ons

Organophosph orus + Pyrethroid

N/I

Effect

Blood

Decrease

MN

Increase

Lipid peroxidatio n CAT

Increase

No

Ogut et al., 2011*

SOD

Jo

GPx Imidacloprid 3-PBA No Exposure Urine Increase Neonicotinoid + Elfman et Lisozim Increase Expir + Pyrethroid Cypermethri al., 2009* Effect No ed air Albumin n Notes: * Some parameters such as albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), cholesterol, creatinine, free thyroxin (FT4), glucose, prolactin (PRL), thyroid stimulating hormone (TSH), triglycerides and uric acid were evaluated but the parameters showed no difference such as biomarkers. *The term “Results” means the change presents in the results of the articles 3-PBA, 3-phenoxybenzoic acid; AChE, Acetylcholinesterase; AGE, Advanced glycation end products; ALT, Alanine aminotransferase; AOPP, Advanced oxidation protein products; AREase, Arylesterase; AST, Aspartate

28

Jo

ur na

lP

re

-p

ro

of

aminotransferase; BCP, 4-bromo-2-chlorophenol; BuChE, Butyrylcholinesterase; CAT, Catalase; CDCA, Dicarboxylic acid; Cis-DCCA, Cis-2,2-(dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid; CMPAase, Cytidine monophosphatase; 6-CNA, 6-chloronicotinic acid; CP-me, Methyl chlorpyrifos; CYP, Cytochrome; DAP, Dialkyl phosphate; DBCA, Cis-2,2-(dibromovinyl)-2,2-dimethylcyclopropane carboxylic acid; DCVA, 2,2-dichlorovinyl3,3-dimethylcyclopropane-1-carboxylic acid; DEDTP, Diethyldithiophosphate; DEP, Diethyl phthalate; DETP, Diethylthiophosphoric acid; DMDTP, Dimethyldithiophosphate; DMP, Dimethyl phthalate; DMTP, Dimethylthiophosphate ; FeNO, Exhaled fraction of nitric oxide; FPBA,4-fluoro-3-phenoxybenzoic acid; FSH, Follicle stimulating hormone; FT4, Free thyroxin; Gene EPHX, Epoxide Hydrolase; GPx, Glutathione peroxidase; GSTM1 Gene, Glutathione S-Transferase Mu 1; GSTT 1, Glutathione S-Transferase Pi 1; IGE, Immunoglobulin E; N/I, Not identified; OP + CRB, Organophosphorus + Carbamate; pChE, Plasma cholinesterase; PYR, Pyrethroids; LH, Luteinising hormone; MMA, Malathion monocarboxylic acid; MPA, Bifenthrin metabolite; PON-1, Paraoxonase 1 ; PRL, Prolactin; SOD, Superoxide dismutase ; TCR, T Cell receptor; TPCy, 3,5,6-trichloro-2pyridinol; Trans-DCCA, Trans-2,2-(dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid; TSH, Tyroid stimulating hormone; XRCC, X-ray repair cross complementing protein.

29

Table 4. Characteristics of specific biomarkers found in the review. Class

Imidacloprid

Type of bioindicator Exposure

Chlorpyrifos

Exposure

Urine

Profenophos

Exposure

Urine

Malathion

Effect

Urine

Alfa-Cypermethrin

Exposure

Urine

Active ingredient

Neonicotinoid Organophosphorus

Biomarker

Results

Urine

2-Naphthol Trichloro-2-pyridyl

Increase

4-bromo-2-chlorophenol

Increase

Increase

Malathion monocarboxylic acid Increase cis-2,2-(dichlorovinyl)-2,2dimethylcyclopropane Increase carboxylic acid

Jo

ur na

lP

re

-p

ro

of

Pyrethroid

Matrix

30

Table 5.Comparison among pesticides found in the systematic review with those most used in the countries of origin of the study.

Continent

Nº of studies

Pesticides found*

Most used pesticides**

References

South Africa

1

Not specified

OP

*Ndlovu, Dalvie and Jeebhay, 2014; **Quinn et al., 2011

OP

*Callahan et al., 2014; Crane et al., 2013; Dadson et al., 2013; Ellison et al., 2012; Farahat et al., 2011; Singleton et al., 2014; 2015; Ismail et al., 2017; **Mansour, 2008

Egypt

8

OP, PYR

of

Africa

Country

United States

5

OP, OP+PYR and NEO

NEO, OP

Mexico

1

OP, CRB

OC

China

1

India

1

Thailand

1

Turkey

1

Finland

1

Ireland

1

Europe

Italy

1

re

lP OP

ro

OP, PYR

-p

PYR, CRB,

Jo

Asia

4

OP, NEO

OP, CRB

OP, PYR *Jamal et al., 2015; **Rao et al., 2015 OP, CRB, OC; *Taneepanichskul et al., 2014 **Panuwet, OP PYR et al.,2012 Information not OP, PYR, CRB *Ogut et al., 2011 available Information not OP *Tuomainen et al., 2012 available Information not OP *Buchanan et al., 2001 available OP, PYR, NEO OP *Costa et al., 2015; **Aprea, et al., 2000

ur na

America

Canada

*Bouchard, Carrier and Brunet, 2008; Couture et al., 2009; Ferland et al., 2015; Ratelle, Côté and Bouchard, 2016; ** Van Balen, Wolansky and , 2012; Ye et al., 2015 *Albers et al., 2014; Harris et al., 2010; Hines and Deddens, 2001; Runkle et al. 2013; Scher et al., 2008; **Narayan et al., 2013 *Bernal-Hernández et al., 2014; **de Llasera and Bernal-González, 2001; Pérez et al., 2016 *Wang et al., 2016; **Greenpeace, 2019

Portugal 1 OP, PYR, CRB *Costa et al., 2014; **Teixeira, et al., 2004 OP United Information not 2 OP, OP+PYR *Galea et al., 2015; Mason, 2000 Kingdom available Sweden 1 PYR, NEO OP *Elfman et al., 2009; **Norén et al., 2017 CRB – Carbamates; NEO – Neonicotinoid; PYR – Pyrethroids; OC – Organochlorine; OP – Organophosphorus; * - Reference of the pesticides searched by the articles found in this review; ** Reference of most used pesticides reported by the countries of origin of the studies 31