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Urinary Metabolites of Organophosphate and Pyrethroid Pesticides and Neurobehavioral effects in Chinese Children Na Wang, Mengying Huang, Xinyan Guo, and Ping Lin Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01219 • Publication Date (Web): 15 Aug 2016 Downloaded from http://pubs.acs.org on August 15, 2016

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Urinary Metabolites of Organophosphate and Pyrethroid

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Pesticides and Neurobehavioral effects in Chinese Children

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Na Wang †,‡#, Mengying Huang †,‡#, Xinyan Guo †,‡, Ping Lin§*

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Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, PR China

7 ‡

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Key Laboratory of Pesticide Environmental Assessment and Pollution Control, Ministry of Environmental Protection of China, Nanjing 210042, China

9 §

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Jiangsu Provincial Center for Diseases Control and Prevention, Nanjing 210009, PR China

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Author Contributions

13

#

These authors contributed equally to this work.

14 15

Corresponding Author

16

* Ping Lin, Ph.D, Professor

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Email: [email protected]; [email protected]. Tel: 86-25- 83759414; Fax: 86-25- 83759411

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Abstract:

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Organophosphate (OP) and pyrethroid (PYR) pesticides are widely used in China. However,

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few studies have investigated the neurobehavioral outcomes of Chinese children exposed to

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low levels of OP and PYR. We investigated urinary metabolite levels and their association

30

with exposure characteristics and the neurobehavior of children. For all children, biomarker

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measurements were made in the same interval relative to neurobehavioral testing. We

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analyzed the morning urine samples of 406 children aged 3–6 years from Nanjing, China.

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The Kruskal-Wallis and Wilcoxon rank sum tests were used to identify the associations

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between urinary metabolite levels and exposure characteristics. Multiple linear regression

35

models were used to test the associations between urinary metabolite levels and

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neurobehavioral test scores after adjusting for covariates (e.g., sex, age, and education

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expense). The detection of 3,5,6-trichloropyridinol (TCP) and 3-phenoxybenzoic acid

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(3-PBA) in the urine was positively associated with living areas adjacent to agricultural fields

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and using indoor mosquito repellent incense. These two metabolites were negatively

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associated with the soaking time of fruits and vegetables. When treated as dichotomous

41

variables, TCP was significantly associated with arithmetic test scores in adjusted models,

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and 3-PBA was significantly associated with the scores on the Chinese Binet and arithmetic

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tests. When treated as a continuous variable, higher urinary 3-PBA levels were significantly

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associated with lower cancellation test scores. Our findings suggest that exposure to

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organophosphate and pyrethroid pesticides may have a significant impact on children's

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working memory and verbal comprehension.

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Keywords: neurobehavior, organophosphate, pyrethroid, urine, children

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Introduction

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Organophosphate (OP) and pyrethroid (PYR) pesticides are widely used in global

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agricultural production, particularly in China. OPs represent the major class of pesticides

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used in China; in fact, OPs comprised 70.38% of all pesticides used in China in 20131. PYRs,

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developed from natural pyrethroids, are a class of new, efficient and safe insecticides. PYRs

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are not highly used in agricultural production and represent only 3.57% of the national

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pesticide used; however, PYRs are widely used as insecticides in homes and public green

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spaces2. The development of quite a few pesticides with high efficiency and low toxicity has

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caused a gradual decrease in the use of OPs; in contrast, pyrethroid pesticide use has steadily

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increased.

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There are many ways that the human body can be exposed to OPs and PYRs. OP and PYR

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residue in crops can be directly ingested by humans through their daily diet. In recent years,

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OPs and PYRs were detected at concentrations above the health guidelines in fruits and

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vegetables3,4. OPs and PYRs can also be absorbed by the body through inhalation and skin

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contact.

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Numerous animal studies demonstrated that in utero or early exposure to OP and PYR

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pesticides affect neurodevelopment. OP and PYR pesticides can cause the necrosis of neurons

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in the brain and decrease the number of cells because of their cytotoxic effects5,6,7,8,9.

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Ultramicrostructure examinations showed prominent chromatin agglutination, swollen

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mitochondria and loose mitochondrial cristae in the hippocampus of rats exposed to

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chlorpyrifos (8.15 mg/kg/d)10. The study of an in vitro model found that most PYRs can

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inhibit the growth of nerve cells at low concentrations11. OP and PYR pesticides can change

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the activity of a variety of neurotransmitters and their receptors and related enzymes, which

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leads to nervous system damage. Repeated postnatal exposure to chlorpyrifos resulted in a

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transient reduction in the total number of muscarinic acetylcholine receptors and a more

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persistent alteration of presynaptic cholinergic neurons. In addition, a long-term reduction of

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brain cholinesterase activity was observed following a repeated postnatal exposure to

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chlorpyrifos due to the permanent inactivation or "aging" of the enzyme12. PYRs increased

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glutamate content, an excitatory amino acid neurotransmitter, and altered the arrangement of

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glutamate receptors on the postsynaptic membrane, which resulted in a series of biochemical

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cascades that led to apoptosis13. Pesticide exposure is a significant risk for children because

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the developing brain is more susceptible to neurotoxins14. According to weight ratio

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calculations, the relative amounts of inhaled air, water intake and food intake for children are

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several times greater than adults, suggesting that children have more contact with

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environmental contaminants15. Thus, the impact of pesticides on the health of children may

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be greater than that of adults.

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There is a growing concern over the health effects of pesticides on children; however, most

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studies focused on a single type of pesticide exposure16,17,18,19, i.e., OPs and prenatal exposure.

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Rauh et al. reported deficits in the Working Memory Index and Full-Scale intelligence

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quotient (IQ) in children 7 years of age due to prenatal chlorpyrifos exposure17. Eskenazi et al.

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reported that nonspecific dialkylphosphate (DAP) metabolite levels during pregnancy were

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negatively associated with the Mental Development Index (MDI) and pervasive

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developmental disorders18. The findings of Bouchard’s team supports the hypothesis

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that OP exposure

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attention-deficit/hyperactivity disorder (ADHD) prevalence19. Furthermore, studies showed

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that prenatal organophosphate exposure was not significantly associated with impaired

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reciprocal social behavior in childhood; however, there were differences in race20. A recent

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study reported that postnatal exposure to PYRs was associated with ADHD in children21. The

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study of two-pesticide exposures is extremely limited. A study in Canadian children showed

at

levels

common

among

US

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contributes

to

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that organophosphate metabolites were not significantly associated with high Strengths and

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Difficulties Questionnaire (SDQ) scores; however, one pyrethroid metabolite was

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significantly associated with high SDQ scores22. A study of Thai children found that after

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controlling for differences in age and the home environment, exposure to OPs and PYRs

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were not significant predictors of adverse neurobehavioral performance; however, the sample

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size for this study was small23.

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Numerous studies have focused on populations in developed countries, but few of these

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studies were conducted with Chinese children. The association between pesticide exposure

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and neurobehavioral outcomes may differ across ethnic groups. The purpose of the current

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study was to evaluate the neurobehavioral effects of OP and PYR exposure in 3-6 year-old

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Chinese children living in Nanjing (including urban and rural areas). We used multiple tests

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with a wide range of indicators to assess children’s neurobehavior. The data obtained from

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our study may reflect the general level of OP and PYR exposure in Chinese children. The

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results of our study highlight the need for pesticide management in China.

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Material and Methods

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Participants and recruitment

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Investigations were conducted at three kindergartens in Nanjing (including urban and rural

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areas). Eligible children were between 3 to 6 years of age with no reported diseases. We

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randomly selected a total of 406 children from different age groups and collected their

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relevant information. Participating children were in good health and able to complete the

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neurobehavioral tests. All of the participants’ parents were well-informed about our study and

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signed a consent form. The Ethics Committee of Jiangsu Provincial Center for Disease

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Prevention and Control (JS CDC) reviewed and approved the study.

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Maternal interviews and assessments

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A trained interviewer administered a questionnaire to the mothers. The questionnaire

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included the following 3 sections: (1) family information, such as address, environment

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nearby the house, family income, methods of household mosquito prevention, and methods

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for washing fruits and vegetables; (2) parental information, such as education level of parents,

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smoking and drinking habits, parental occupation, occupational exposure to hazardous

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substances, and the mother's reproductive history; and (3) information on the prior pregnancy,

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such as parental smoking and drinking during pregnancy and the parents' occupational

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exposure during pregnancy.

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Neurobehavioral measurements

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We developed a practical combination of intelligence testing tools to meet the testing

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requirements for the intellectual and behavioral expectations of preschool children between

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3-6 years of age. The tools included the Chinese Binet test, arithmetic test, picture completion

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test, maze test and cancellation test. The arithmetic test, picture completion test and maze test

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were obtained from the Wechsler preschool and primary scale of intelligence (Chinese

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revised edition). The description and function of the neurobehavioral tests are provided in

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Table 124,25.

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Procedures

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On the day prior to the neurobehavioral tests, technicians from JS CDC visited each class in

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three kindergartens to explain the project to the parents and obtain informed consent. Trained

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technicians instructed parents on the procedures for collection of morning urine samples. The

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next day, parents provided the urine sample labeled with the subject ID to the kindergarten

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teacher. The teacher then gave the samples to the technicians. The technicians performed a

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physical exam to determine the health data of each child, such as height and weight. Parents

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completed a questionnaire about their family and the potential for pesticide exposure.

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Children completed neurobehavioral tests under the guidance of trained technicians from JS

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CDC. The interval between the collection of urine samples and neurobehavioral testing was

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less than one week.

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Pesticide exposure measurements

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Parents collected 50 mL of morning urine from their child in a pre-washed and labeled

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screw-top polyethylene bottle provided by the JS CDC technician. The urine samples were

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stored at -80°C until analysis.

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For the OP assessment, 3,5,6-trichloropyridinol (TCP), a specific metabolite of

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chlorpyrifos, was measured. We selected only TCP as a marker because nonspecific

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metabolites (DAPs) may reflect exposure not only to pesticide parent compounds but also

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potentially nontoxic preformed metabolites in the environment16. Each urine sample (10.0

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mL) was saturated with salt, acidified with 100 µL of 6 M hydrochloric acid, and then

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extracted with 20 mL of acetonitrile. After adjusting the pH to approximately 7.0, urine

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samples were extracted using 20 mL of ethyl acetate:acetonitrile (70:30, v/v). After vortexing

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and centrifugation, the extract was mixed and passed through a funnel containing an

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appropriate amount of anhydrous sodium sulfate. The extract was dried and redissolved in

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toluene, and then derivatized with N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide

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(MTBSTFA). TCP was analyzed using gas chromatography-tandem mass spectrometry

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(GC-MS-MS).

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For

the

PYR

assessment, acid

three

urinary

(4F3PBA),

a

metabolites

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4-fluoro-3-phenoxybenzoic

metabolite

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cis-3-(2,2-dibromovinyl)-2,2-dimethylcyclopropane-1-carboxylic

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were

measured:

of

cyfluthrin;

(cis-DBCA),

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metabolite of deltamethrin; and 3-phenoxybenzoic acid (3-PBA), a general metabolite of

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pyrethroids. Each urine sample (10.0 mL) was acidified with 100 µL of 6 M hydrochloric

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acid, and then extracted with 20 mL of hexane:isopropanol (95:5, v/v). After vortexing and

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centrifugation, the organic phase was passed through a funnel containing an appropriate

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amount of anhydrous sodium sulfate. The exact was dried and redissolved in toluene, and

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then derivatized with N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide (MTBSTFA).

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The analysis was performed using GC-MS-MS.

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The method we used simultaneously detected PYR and OP metabolites. The limit of

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detection (LOD) for each metabolites was 0.200 µg/L for TCP, 0.833 µg/L for cis-DBCA,

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0.017 µg/L for 4F3PBA and 0.008 µg/L for 3-PBA.

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Metabolite concentrations were adjusted using creatinine concentrations to correct for

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variable urine dilutions in the spot urine samples. Creatinine concentrations were measured

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by JS CDC.

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Data Analysis

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SPSS version 19.0 (SPSS Inc., Chicago, Illinois, USA) was used for all analyses. We set

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the threshold for statistical significance at p < 0.05. Kruskal-Wallis and Wilcoxon rank sum

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tests were used to differences in the rank orders of metabolite concentrations between groups.

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Logistic regression models were used to find predictors of specific metabolites. A multiple

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imputation procedure was used to fill values lower than LOD for analytes with low detection

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frequencies. This procedure is suitable when 30% or more of the data are below detection

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limits26. To assess the relationship between urinary metabolite levels of children and

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neurobehavioral outcomes, we constructed multiple linear regression models for each test.

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We did not determine associations for cis-DBCA and 4F3PBA because of low detection rates.

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Metabolite concentrations were treated as continuous variables (log-transformed) and

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dichotomous

variables (depending on

detection).

Metabolite concentrations

were

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log-transformed in continuous variable models. In dichotomous variable models, the variable

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was assigned a value of 1 if the concentration was greater than the LOD. Using dichotomous

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variables may improve the R-squared value for the multiple linear regression models. Each

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model was adjusted for potential covariates.

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Potential covariates for the models were selected by bivariate analyses and multiple linear

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regression. Variables that were suggested to be related to neurobehavioral outcomes in the

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literature and significantly associated with two or more test scores were selected as potential

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covariates. Age, sex and outside school education expenses were selected as potential

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covariates. Age and sex were related to the neurobehavioral outcomes. We did not test

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parental IQ in our study. Alternatively, we used outside school education expenses as a

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replacement for family effects on the child's intelligence.

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Results

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Participants and urinary pesticide metabolite levels

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The demographic and exposure characteristics of participants are shown in Table 2. The

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data from 406 healthy young children were analyzed in the present study. Overall, 51.2% of

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the sample population was female. One participant’s sex information was missing. The mean

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age of the participants was 4.126 years (SD=0.845). Approximately 59.1% of participating

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families had a duration of dwelling of less than ten years. Approximately 37.2% of

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participating families lived adjacent to agricultural fields. In terms of parental education level,

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48.5% of fathers and 44.6% of mothers completed high school or college. The mean

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household income was 123, 295 RMB per year. Nearly 67.2% of the families spent money on

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extra education. In terms of living habits, approximately 32.5% of the families used mosquito

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repellent incense indoors and 22.7% used insecticide aerosols indoors. Nearly half of the 9

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families did not soak vegetables before washing. Approximately 40.4% of the families did

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not soak fruit before washing. Almost none of the mothers smoked regularly during

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pregnancy; however, a few mothers occasionally consumed alcohol.

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The urinary metabolite levels from the study population are summarized in Table 3. The

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maximum values were 264.05 µg/g for TCP, 23.60 µg/g for cis-DBCA, 1.65 µg/g for

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4F3PBA and 48.98 µg/g for 3-PBA. The GM values were 0.92 for TCP, 0.04 for 4F3PBA and

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0.08 for 3-PBA. The GM value for cis-DBCA was not calculated because of a low detection

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rate.

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Correlation analyses of exposure and environmental factors

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The results of the Kruskal-Wallis and Wilcoxon rank sum tests are summarized in Table 4

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and Table 5, respectively. In the Kruskal-Wallis test, we observed a difference in urinary TCP

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concentrations between groups based on their exposure characteristics, such as vegetable

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soaking time (χ2=20.846, p=0.000), fruit soaking time (χ2=25.583, p=0.000) and the

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frequency of smelling pesticides indoors (χ2=61.992, p=0.000). We also found differences in

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urinary 3-PBA concentrations between groups based on their exposure characteristics, such as

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vegetable soaking time (χ2=26.032, p=0.000), fruit soaking time (χ2=58.153, p=0.000) and

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the frequency of smelling pesticides indoors (χ2=43.213, p=0.000).

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In the Wilcoxon rank sum test, the urinary TCP (Z=-7.062, p=0.000) and 3-PBA (Z=-7.167,

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p=0.000) concentrations differed based on the use of indoor mosquito repellent incense. We

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also observed a difference in urinary TCP (Z=-5.655, p=0.000) and 3-PBA (Z=-7.078,

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p=0.000) concentrations based on whether the family lived adjacent to an agricultural field.

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There were no associations among urinary TCP levels with living adjacent to a green park

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(Z=-0.146, p=0.884) or household insecticide aerosol use (Z=-0.087, p=0.930). The urinary

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3-PBA concentration did not relate to living adjacent to a green park (Z=-1.599, p=0.110) or

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household insecticide aerosol use (Z=-1.235, p=0.217).

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The results of the logistic regression analysis are shown in Table S1 and S2 of Supporting

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Information. Detection of TCP was significantly associated with living adjacent to an

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agricultural field (OR=2.0), living adjacent to a green park (OR=2.0), occasional pesticides

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indoor smell (OR=4.1) and consistent pesticides indoor smell (OR=3.1). Detection of 3-PBA

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was significantly associated with living adjacent to an agricultural field (OR=6.6).

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Associations between urinary pesticide metabolites and neurobehavioral outcomes

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The results of the five neurobehavioral tests are shown in Table S3 of Supporting

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Information. Tables 6 and 7 present the adjusted regression coefficients with 95% confidence

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intervals for all samples. Each of the five tests scores were assessed based on the 3-PBA and

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TCP urinary levels after adjusting for sex, age and outside school expenses. In Table 6,

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urinary levels were treated as continuous variables (log-transformed). In Table 7, urinary

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levels were treated as dichotomous variables (depending on detection).

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We did not observe any significant associations between urinary TCP levels and test scores

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in the adjusted models that used urinary TCP concentration as a continuous variable. When

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the urinary TCP concentration was treated as a dichotomous variable, there was a significant

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negative correlation between the detection of TCP and the arithmetic test scores in the

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adjusted model. The urinary 3-PBA level was negatively associated with cancellation test

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score when 3-PBA concentration was treated as a continuous variable. When urinary

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metabolite concentrations were treated as dichotomous variables, the urinary 3-PBA level

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was negatively related to the scores on the Chinese Binet and arithmetic tests in the adjusted

283

models.

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Discussion

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The use of PYRs is rapidly increasing and has replaced the household use of OPs because of

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concerns about toxic effects. However, in the agricultural production industry, the use of OPs

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remains significant. Due to their extensive use in agriculture, OP residues can be found in

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fruits and vegetables. Household pest control products represent a significant PYR exposure

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source27. In the present study, we selected three metabolites of PYR (cis-DBCA, 4F3PBA,

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3-PBA) and one metabolite of chlorpyrifos (TCP) as biomarkers of pesticide exposure.

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Comparisons with other studies are shown in Table 8. Consistent with the study in Shanghai28,

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we observed a relatively high detection rate for 3-PBA and very low detection rates for

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cis-DBCA and 4F3PBA. The detection frequencies of the three PYR urinary metabolites,

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especially DBCA and 4F3PBA, were generally lower in our sample population than those

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reported by a study in Canadian children. Different detection frequencies may be attributed to

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differences in LODs. Our LODs for DBCA and 4F3PBA were higher than those used in the

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Canadian study, but the LOD for 3-PBA was lower than those used in Canadian and

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American studies21. Our sample population and their living habits are different from western

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countries, which may explain the discrepancies in detection rates. The greater detection

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frequency of TCP indicates the wide use of chlorpyrifos in Nanjing.

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In China, more and more parents are sending their children to a variety of early education

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classes. This additional education significant impacted the intelligence test scores; therefore,

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our models using increased outside school education expenses as a potential factors reflects

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the current social education situation.

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After adjusting for sex, age and outside school education expenses, the urinary 3-PBA

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level was significantly associated with cancellation test score when 3-PBA concentration was

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treated as a continuous variable. When treated as dichotomous variables, the urinary 3-PBA

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has significant relationship with scores on the Chinese Binet and arithmetic tests in the

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adjusted models. It was showed that exposure to pyrethroid pesticides has a significant

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impact on the figure discrimination, arithmetic calculation, working memory and verbal

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discrimination. A previous study in French children reported similar findings, specifically

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3-PBA concentrations were negatively associated with verbal comprehension and working

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memory scores29. In addition, 3-PBA levels were significantly associated with Chinese Binet

315

test scores. Thus, pyrethroid pesticides impact multiple intellectual abilities.

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There are multiple mechanisms to explain the neurotoxicity of PYR. PYRs are known to

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affect a variety of voltage- and ligand-gated ion channels, such as voltage-gated sodium,

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calcium and chloride channels. Voltage-gated sodium channels are considered the primary

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target for the neurotoxic actions of PYR30. Previous studies reported that exposure to PYR

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affects the secretion of certain neurotransmitters in the animal brain. Early-life exposure to

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permethrin (a PYR) caused a significant reduction in serotonin (5-HT) in the prefrontal

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cortex and impaired working memory in rats31. The prefrontal cortex plays a significant role

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in the working memory of humans. Exposure to PYR may affect working memory by

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keeping the prefrontal cortex in a hypometabolic state.

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The urinary TCP concentration (metabolite level was used as a dichotomous variable) was

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significantly associated with Arithmetic test scores after adjusting for sex, age and outside

327

school education expenses, indicating that OP exposure may affect the ability of arithmetic

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calculation and working memory. TCP is a specific metabolite of chlorpyrifos. Similarly

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Rauh’s report found that deficits in the Working Memory Index and Full-Scale IQ of children

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7 years of age were a function of prenatal chlorpyrifos exposure. The working memory of

331

male rats was impaired after exposure to high doses of chlorpyrifos32.

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In this study, children living adjacent to an agricultural field had higher urinary

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concentrations of TCP and 3-PBA when compared with those living far away from an

334

agricultural field. However, there were no significant differences in the urinary

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concentrations of TCP and 3-PBA between those living adjacent to a green park and those

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that did not. These findings indicate that OPs and PYRs are mainly used in agricultural fields

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rather than green parks. Children living adjacent to an agricultural field have more

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opportunities for contact with pesticides33. Spraying of pesticides may be an important

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contributor to high exposure rates34. Pesticides used in the agricultural field can be

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inadvertently introduced into the home through various routes35. When children are playing

341

in an agricultural field or even at home, the soil and dust may contain residual pesticides, and

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exposure through the skin can cause high levels of pesticide metabolite concentrations in

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children36.

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The main active ingredient in mosquito repellent incense is PYR. Therefore, children

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exposure to mosquito repellent incense indoors showed higher urinary 3-PBA concentrations.

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Residue in food is the main exposure source of pesticides27, 37. Soaking vegetables and

347

fruits before washing can reduce pesticide residues38. Increasing the vegetable and fruit

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soaking time decreased the concentrations of 3-PBA and TCP. Suggestive of an improvement

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in health consciousness, our survey found that more than half of the families spend time

350

soaking fruits and vegetables before washing.

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The frequency of indoor pesticide smell was higher in regions adjacent to pesticide

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production factories and coincided with higher levels of urinary metabolites. Due to the

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moderate persistence of OPs and PYRs in soil39, indoor dust and suspended solids can

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contain pesticide residues after the use of insecticide aerosols indoors40,41. Pesticides residues

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in indoor dust and suspended solids can enter the body through the respiratory tract and skin;

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indeed, pesticide use indoors and urinary metabolites levels showed a significant positive

357

correlation.

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There are several limitations of our study. Although we collected the urine of children in

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urban and rural areas, the sample size was relatively small. In China, climate and soil

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conditions differ across provinces. Pesticide usage conditions also have regional differences.

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To investigate pesticide exposure in the general Chinese child population, the collection of

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urine samples from multiple provinces is necessary. Due to limited funds and research time,

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we measured the urinary metabolites in only one spot urine sample. The differences in

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metabolite levels during the high- and low-use seasons are unknown. In addition, we did not

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measure the indoor air conditions of the children’s homes. OP and PYR concentrations in the

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air are an important exposure characteristic. Although we used a replacement characteristic

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(frequency of smelling pesticides indoors) in our study, actual measured values are more

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accurate.

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Our findings suggest that exposure to organophosphate and pyrethroid pesticides have a

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significant impact on a child's working memory and verbal comprehension. In our study,

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urinary TCP levels moderately correlated with urinary 3-PBA levels (Pearson correlation

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coefficient was 0.406, P