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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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Environmental Science & Technology

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Urinary Metabolites of Organophosphate and Pyrethroid

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Pesticides and Neurobehavioral effects in Chinese Children

3 4

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 §

10

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

18 19 20 21 22 23 24 25

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ACS Paragon Plus Environment


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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

31

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

32

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

33

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

34

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

37

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

38

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

39

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

40

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,

42

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

43

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

44

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

69

increased.

70

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

4


children

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

175

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

177

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

178

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

181

(GC-MS-MS).

182

For

the

PYR

assessment, acid

three

urinary

(4F3PBA),

a

metabolites

183

4-fluoro-3-phenoxybenzoic

metabolite

184

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

7


acid

were

measured:

of

cyfluthrin;

(cis-DBCA),

a


185

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

187

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

189

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.

195

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.

198 199

Data Analysis

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

201

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

213

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.

222 223

Results

224 225

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

243

rate.

244 245

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

250

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,

255

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,

257

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

263

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

264

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

265

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

266

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

267 268

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

270

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

271

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

274

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

275

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

276

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

277

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

278

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

279

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

281

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

282

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

283

models.

284 285

Discussion

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286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

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

295

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

296

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

297

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

298

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

300

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

301

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

302

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

303

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

304

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

305

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

308

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

309

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

310

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

312

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

313

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

314

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

315

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

316

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

317

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

318

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

319

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

320

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

321

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

322

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

323

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

324

keeping the prefrontal cortex in a hypometabolic state.

325

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

326

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

328

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

329

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

330

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.

332

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

333

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

335

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

13



336

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

337

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

338

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

339

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

340

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

342

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

343

children36.

344

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

345

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

346

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

348

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

349

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

350

soaking fruits and vegetables before washing.

351

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

352

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

353

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

354

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

355

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

356

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

357

correlation.

358

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

359

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

360

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

362

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

363

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

364

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

365

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

366

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

367

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

368

accurate.

369

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

370

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

371

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

372

coefficient was 0.406, P

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