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Archives of Toxicology

, Volume 91, Issue 2, pp 549–599 | Cite as

Pesticides: an update of human exposure and toxicity

  • Sara Mostafalou
  • Mohammad Abdollahi
Review Article

Abstract

Pesticides are a family of compounds which have brought many benefits to mankind in the agricultural, industrial, and health areas, but their toxicities in both humans and animals have always been a concern. Regardless of acute poisonings which are common for some classes of pesticides like organophosphoruses, the association of chronic and sub-lethal exposure to pesticides with a prevalence of some persistent diseases is going to be a phenomenon to which global attention has been attracted. In this review, incidence of various malignant, neurodegenerative, respiratory, reproductive, developmental, and metabolic diseases in relation to different routes of human exposure to pesticides such as occupational, environmental, residential, parental, maternal, and paternal has been systematically criticized in different categories of pesticide toxicities like carcinogenicity, neurotoxicity, pulmonotoxicity, reproductive toxicity, developmental toxicity, and metabolic toxicity. A huge body of evidence exists on the possible role of pesticide exposures in the elevated incidence of human diseases such as cancers, Alzheimer, Parkinson, amyotrophic lateral sclerosis, asthma, bronchitis, infertility, birth defects, attention deficit hyperactivity disorder, autism, diabetes, and obesity. Most of the disorders are induced by insecticides and herbicides most notably organophosphorus, organochlorines, phenoxyacetic acids, and triazine compounds.

Keywords

Pesticide Toxicity Chronic disease Review 

Introduction

Pesticides are a large and heterogeneous group of chemicals which have long been used to control and repel pests in different fields. Controlling pests have always been a concern for human life. The literature shows that natural and inorganic chemicals were sporadically used for this purpose, but development of new and potent organic chemical targets has brought pesticides into widespread use during the past century. Human has benefited pesticides in different fields like producing and keeping more and safe agricultural products, repelling home pests, and controlling infectious diseases among which malaria eradication program was a remarkable feature of insecticides’ use. Human exposure to pesticides can occur through different routes, including occupations dealing with production, transport, delivery and application of pesticides, residing in the places high in pesticide residue, and circulation and accumulation of pesticides in the food chain. Since pesticides were born as chemicals to be toxic for living organisms, their toxicity for human and the other animal species is inevitable. This issue becomes further apparent in the huge and growing body of epidemiological and experimental evidence on the link between exposure to pesticides and the incidence of various health disorders in human beings. Incidence of different human diseases like malignant, neurodegenerative, reproductive, developmental, respiratory, and metabolic diseases in association with exposure to pesticides has frequently become the research topic of numerous studies (Mostafalou and Abdollahi 2012a).

In the previous study, the relation between exposure to pesticides and incidence of different types of human chronic diseases was studied via a systematic review of epidemiological evidence and exploring the involved mechanisms. The results revealed that the largest share was accounted for incidence of cancers and then neurodegenerative, reproductive, and developmental disorders in association with exposure to pesticides (Mostafalou and Abdollahi 2013).

In the current work, diverse toxicities of pesticides within the context of known and prevalent human chronic diseases are updated via a systematic review.

Methodology

Article search

We performed a PubMed search of the literature on the association between pesticide exposure and human diseases. We restricted our search to articles published since 1980. The search used a combination of the following words: pesticides, cancer, bladder cancer, bone tumors, brain tumors, breast cancer, cervical cancer, colorectal cancer, eye cancer, gallbladder cancer, kidney cancer, laryngeal cancer, leukemia, lip cancer, liver cancer, lung cancer, lymphoma, melanoma, mouth cancer, multiple myeloma, neuroblastoma, esophageal cancer, ovarian cancer, pancreatic cancer, soft tissue sarcoma, stomach cancer, testicular cancer, thyroid cancer, uterine cancer, Alzheimer, Parkinson, amyotrophic lateral sclerosis (ALS), asthma, chronic bronchitis, birth defects, infertility, attention deficit hyperactivity disorder (ADHD), autism, developmental delay, diabetes, obesity, and humans. Details of the search are given in Fig. 1.
Fig. 1

Flow chart and category of the articles included and excluded in the systematic review

Article criteria

In order to identify eligible articles, the titles and abstracts and, if needed, the full text of the papers were reviewed. The following characteristics were considered as inclusion criteria for recording articles:
  1. 1.

    Written and published in English

     
  2. 2.

    Type of study as cross-sectional, case–control, cohort, ecological, and/or meta-analyses

     
  3. 3.

    Exposure assessment tool as interviews, questionnaires, geographic information system (GIS), job exposure matrix (JEM), and/or residue detection in biological samples

     
  4. 4.

    Reported association of chronic diseases with pesticide exposures

     

Data extraction

The following information was extracted from eligible papers and presented in the classified tables:
  1. 1.

    Authors

     
  2. 2.

    Publication date

     
  3. 3.

    Type of study

     
  4. 4.

    Number of samples in each study

     
  5. 5.

    Exposure assessment tool

     
  6. 6.

    Type of exposure

     
  7. 7.

    Type of specific pesticide if reported

     
  8. 8.

    Type of specific disease in each category of toxicity

     
  9. 9.

    Quantitative risk estimate as the odd ratio (OR), hazard ratio (HR), relative risk or risk ratio (RR), proportional mortality ratio (PMR), standardized mortality ratio (SMR), mortality rate ratio (MRR), and standardized incidence ratio (SIR)

     
  10. 10.

    Confidence interval for reported risk estimates

     
  11. 11.

    Significance of the risk as p value if reported

     

Results

The PubMed searches yielded a total of 7419 unique articles. The number of records for each category of toxicity in combination with pesticides was as follows; carcinogenicity 3410, neurotoxicity 1342, pulmonotoxicity 512, reproductive toxicity 833, developmental toxicity 124, metabolic toxicity 1198. After screening the titles, abstracts, and full text of the papers, the irrelevant ones were excluded and the number of remaining articles for reviewing in each category became as follows: carcinogenicity 246, neurotoxicity 58, pulmonotoxicity 33, reproductive toxicity 46, developmental toxicity 31, and metabolic toxicity 38 (Fig. 1).

Disease-based evidence on carcinogenicity of pesticides

The World Health Organization (WHO) defines cancer as a generic term for a large group of neoplastic diseases affecting each part of the body. Cancer is the leading cause of mortality worldwide with almost 8.2 million cancer-related deaths in 2012. In the same year, new cases of cancer were estimated 14 million, which is expected to increase by 70 % over the next two decades. The most common cancer-related deaths are due to lung, liver, stomach, colorectal, breast, and esophageal cancer. Cancer is the result of genetics–environmental interactions, which can be relatively induced under the effect of biological, physical, and chemical exposures (WHO 2015). The association of exposure to different classes of pesticides, including insecticides, herbicides, and fungicides with incidence of cancers has been highlighted during the past half century. Different types of surveys have targeted the link of pesticides with cancers and reported various risk estimates. The number of reports evidencing a positive association between exposure to pesticides and cancer incidence is considerable, and the relevant ones resulted from population-based human studies have been reviewed and classified according to the site of cancer (Table 1).
Table 1

Carcinogenicity of pesticides evidenced by diseases

Study

Type of study

No. of samples

Exposure assessment

Exposure

Target pesticide

OR/RR/HR

(95 % CI)

p value

Childhood brain tumors

Greenop (2013)

CC

374/1467

Questionnaire

Par.

Home pest control

1.90 (1.08–3.36)

 
     

Pat. occupation

1.36 (0.66, 2.80)

 

Searles Nielsen (2010)

CC

201/285

Interview

Res.

OPs + PON1 polymorph

OPs + FMO1 polymorph

1.8 (1.1–3.0)

2.7 (1.2–5.9)

 

Shim (2009)

CC

526/526

Interview

Par.

Herbicides

1.8 (1.1–3.1)

 

Rosso (2008)

CC

318/318

Interview

Par.

During pregnancy

After birth

1.6 (1.0, 2.5)

1.8 (1.2, 2.8)

 

Searles Nielsen (2005)

CC

66/236

Interview

Par.

+PON1 polymorph

2.6 (1.2–5.5)

 

van Wijngaarden (2003)

CC

322/321

Interview

Pat.

Insecticides

Herbicides

Fungicides

1.5 (0.9, 2.4)

1.6 (1.0, 2.7)

1.6 (1.0, 2.6)

 

Efird (2003)

CC

1218/2223

Interview

Mat.

Pesticide

2

 

Pogoda and Preston-Martin (1997)

CC

224/218

Interview

Mat.

Flea/tick pesticides

1.7 (1.1–2.6)

 

Kristensen (1996)

Co

323292

Census

Par.

3.37 (1.63–6.94)

 

Vinson (2011)

MA

40 studies

Before birth

Pat.

1.49 (1.23–1.79)

 
   

After birth

Pat.

1.66 (1.11–2.49)

 

Kunkle (2014)

MA

15 studies

3

5

Preconception

Pat.

2.29 (1.39–3.78)

 
   

In pregnancy

Pat.

1.63 (1.16–2.31)

 
  

5

7

Agricultural

Mat.

1.48 (1.18–1.84)

 
   

Non-agricultural

Mat.

1.36 (1.10–1.68)

 
  

4

5

Agricultural

Childhood

1.35 (1.08–1.70)

 
   

Non-agricultural

Childhood

1.32 (1.04–1.67)

 

Adult brain tumors

Samanic (2008)

CC

657/765

Interview

Occup.

Herbicides (in women)

2.4 (1.4, 4.3)

0.01

Provost (2007)

CC

221/442

Interview-JEM

Occup.

2.16 (1.10–4.23)

 

Lee (2005)

CC

251/498

Interview

Occup.

Metribuzin

Paraquat

Bufencarb

Chlorpyrifos

Coumaphos

3.4 (1.2–9.7)

11.1 (1.2–101)

18.9 (1.9–187)

22.6 (2.7–191)

5.9 (1.1–32)

 

Viel (1998)

Ec

89 units

GIS

Occup.

Vineyard pesticides

1.10 (1.03–1.18)

 

Rodvall (1996)

CC

192/192

Questionnaire

Occup.

In men

1.8 (0.6–5.1)

 

Figa-Talamanca (1993)

Mr

2310

Licensed users

Occup.

In men

SMR: 270 (108.6–556.9)

 

Musicco (1988)

CC

240/742

Interview

Occup.

Insecticides, fungicides

2.0

0.006

Blair (1983)

Mr

3827

Licensed users

Occup.

In men

SMR: 200

 

Neuroblastoma

Carozza (2008)

Ec

1078 counties

GIS

Res.

1.8 (1.5–2.1)

 

Giordano (2006)

Co

168

Applicators

Occup.

SMR; 529.2 (144–1368)

 

Daniels (2001)

CC

538/538

Interview

Res.

Home used

Garden used

1.6 (1.0–2.3)

1.7 (0.9–2.1)

 

Feychting (2001)

Co

235635

Census

Pat.

2.36 (1.27–4.39)

 

Littorin (1993)

Co

2370

Applicators

Occup.

Insecticides, fungicides

SMR; 2.9 (1.1, 6.2)

 

Kristensen (1996)

Co

323292

Census

Par.

2.38 (1.03–6.13)

 

Esophageal cancer

Meyer (2011)

CC

5782/5782

Workers

Occup.

1.38 (1.26–1.51)

 

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res., Occup.

MRR; 2.40 (2.34–2.45)

0.046

Jansson (2006)

CC

356/820

Airborne level

Occup.

2.3 (0.9 to 5.7)

 

Stomach cancer

Barry (2012)

Co

53588

Questionnaire

Occup.

Methyl bromide

3.13 (1.25–7.80)

0.02

Mills and Yang (2007)

Nested CC

100/210

Questionnaire

Occup.

2,4-D

Chlordane

Trifluralin herbicide

1.85 (1.05–3.25)

2.96 (1.48–5.94)

1.69 (0.99–2.89)

 

Van Leeuwen (1999)

Ec

40 states

Drinking water

Env.

Atrazine

1.45 (1.20–1.70)

<0.05

Forastiere (1993)

CC

1674/480

Questionnaire

Occup.

1.77 (0.75–4.25)

 

Colorectal cancer

Lerro (2015b)

Co

33,484

Interview

Occup.

Acetochlor

1.75 (1.08–2.83)

 

Salerno (2014)

Ec

Vercelli

GIS

Gen.

2.38 (1,76–2,87)

 

Lo (2010)

CC

421/439

Interview

Occup.

Pesticides

Insecticides

Herbicides

2.6 (1.1–5.9)

3.2 (1.5–6.5)

5.5 (2.4–12.3)

 
    

Dietary

4.6 (1.5–14.6)

 

Koutros (2009)

Co

57311

Questionnaire

Occup.

Imazethapyr

2.73 (1.42–5.25)

0.001

Kang (2008)

Co

50127

Questionnaire

Occup.

Trifluralin

1.76 (1.05–2.95)

 

van Bemmel (2008)

Co

48378

Questionnaire

Occup.

EPTC

2.09 (1.26–3.47)

<0.01

Lee (2007b)

Co

56813

Questionnaire

Occup.

Chlorpyrifos

Aldicarb

2.7 (1.2–6.4)

4.1 (1.3–12.8)

0.008

0.001

Samanic (2006)

Co

41969

Questionnaire

Occup.

Dicamba

3.29 (1.40–7.73)

0.02

Zhong and Rafnsson (1996)

Co

2449

Questionnaire

Occup.

2.94 (1.07–6.40)

 

Forastiere (1993)

CC

1674/480

Questionnaire

Occup.

2.82 (0.75–9.32)

 

Liver cancer

VoPham (2015)

CC

3034/14991

GIS

Gen.

OCs

2.76 (1.58–4.82)

0.0004

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res., Occup.

MRR; 1.49 (1.44–1.54)

 

Carozza (2008)

Ec

1078 counties

GIS

Res.

3.3 (2.1–5.0)

 

Giordano (2006)

Co

168

Applicators

Occup.

SMR; 596.3 (204–1365)

 

Gallbladder cancer

Shukla (2001)

CC

30/30

Biliary level

HCB

DDT

↑ level in cases

↑ level in cases

<0.04

<0.03

Giordano (2006)

Co

168

Applicators

Occup.

SMR; 723.8 (129–2279)

 

Pancreatic cancer

Lerro (2015b)

Co

33484

Interview

Occup.

Acetochlor

2.36 (0.98–5.65)

 

Antwi (2015)

CC

2092/2353

Questionnaire

Gen.

1.21 (1.02–1.44)

 

Andreotti (2009)

CC

93/82503

Questionnaire

Occup.

Pendimethalin

EPTC herbicide

3.0 (1.3–7.2)

2.56 (1.1–5.4)

0.01

0.01

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res., Occup.

MRR; 2.32 (2.23–2.40)

0.040

Lo (2007)

CC

194/194

Interview

Gen.

 

2.6 (0.97–7.2)

 

Ji (2001)

CC

484/2095

JEM

Occup.

Pesticides

Fungicides

Herbicides

1.4 (1.0–2.0)

1.5 (0.3–7.6)

1.6 (0.7–3.4)

0.01

Alguacil (2000)

CC

164/238

JEM

Occup.

Arsenical pesticides

Other pesticides

3.4 (0.9–12.0)

3.17 (1.1–9.2)

 

Cantor and Silberman (1999)

Mr

9961

 

Occup.

2.71

 

Forastiere (1993)

CC

1674/480

Questionnaire

Occup.

5.18 (1.55–16.7)

 

Alavanja (1990)

Nested CC

22938

Death certificate

Occup.

SMR; 133

 

Childhood leukemia

Zhang et al.(2015)

CC

248/111

Urine level

Res.

OPs

1.9 (1.2–3.1)

<0.05

Maryam et al. (2015)

CC

94/94

Interview

Par.

4.2 (2.2–7.8)

<0.001

Metayer et al. (2013)

CC

269/333

Dust sample

Res.

Chlorthal

1.57 (0.90–2.73)

0.05

Ding G et al. (2012)

CC

176/180

Urine sample

Pyrethroids

2.75 (1.43–5.29)

 

Bailey et al. (2011)

CC

388/870

Preconception

In pregnancy

After birth

Occup.

1.19 (0.83–1.69)

1.30 (0.86–1.97)

1.24 (0.93–1.65)

 

Soldin et al. (2009)

CC

41/77

Questionnaire

Mat.

Insecticides

↑ risk

0.02

Rull et al. (2009)

CC

213/268

Questionnaire

Res.

Insecticides

Herbicides

Fungicides

1.5 (0.9–2.4)

1.2 (0.8–1.9)

1.2 (0.7–2.4)

 

Carozza (2008)

Ec

1078 counties

GIS

Res.

1.2 (1.1–1.3)

 

Rudant (2007)

CC

764/1681

Questionnaire

Mat.

Pat.

Household use

Household use

2.1 (1.7–2.5)

1.5 (1.2–1.8)

 

Monge P et al. (2007)

CC

334/579

Interview

Mat.

2.2 (1.0–4.8)

 

Menegaux et al. (2006)

CC

280/280

Interview

Mat.

1.8 (1.2 to 2.8)

 

Reynolds et al. (2005)

CC

2189/4335

Questionnaire

Mat.

Metam sodium

Dicofol

2.05 (1.01–4.17)

1.83 (1.05–3.22)

 

Ma et al. (2002)

CC

162/162

Interview

Mat.

Household use

Insecticides

2.8 (1.4–5.7)

2.1 (1.3–3.5)

 

Alexander FE et al (2001)

CC

136/266

Questionnaire

Mat.

Baygon/mosquitocidal

5.14 (1.27–20.85)

0.02

Infante-Rivard et al. (1999)

CC

491/491

Questionnaire

Mat.

Insecticides

Herbicides

2.47 (1.43–4.28)

1.84 (1.32–2.57)

 

Meinert et al. (1996)

CC

173/175

Questionnaire

Par.

Garden used

2.52 (1.0–6.1)

 

Leiss and Savitz (1995)

CC

252/222

Interview

Res.

Household use

1.7 (1.2–2.4)

 

Mulder et al. (1994)

CC

14/52

Questionnaire

Res.

Pat.

6.0 (0.6–49.3)

3.2 (1.0–10.1)

 

Buckley et al (1989)

CC

204/

 

Pat. job

2.7 (1.0–7.0)

0.06

Shu et al. (1988)

CC

309/618

 

Mat. job

3.5 (1.1–11.2)

 

Chen (2015)

MA

16 studies

 

Res.

Indoor pesticides

Herbicides

1.47 (1.26–1.72)

1.26 (1.10–1.44)

 

Bailey 2014)

MA (13)

8236/14850

 

Mat.

1.01 (0.78–1.30) for ALL

1.94 (1.19–3.18) for AML

 
  

8169/14201

 

Pat.

1.20 (1.06–1.38) for ALL

0.91 (0.66–1.24) for AML

 

Vinson (2011)

MA

40 CC

 

Mat.

1.48 (1.26–1.75)

 

Van Maele-Fabry (2011)

MA

13 CC

(1966–2009)

 

Res., Mat.

1.74 (1.37–2.21)

 

Turner (2011)

MA

17 CC

(1950–2009)

 

Res.

Pesticides

Insecticides

Herbicides

1.54 (1.13–2.11)

2.05 (1.80–2.32)

1.61 (1.20–2.16)

 

Wigle (2009)

MA

31 CC

(1950–2009)

 

Mat.

Pesticides

Insecticides

Herbicides

2.09 (1.51–2.88)

2.72 (1.47–5.04)

3.62 (1.28–10.3)

 

Adult leukemia

Baumann Kreuziger (2014)

Co

195

Interview

Occup.

Agent Orange

1.8 (0.7–4.5)

0.24

Bonner (2010)

Co

57310

Questionnaire

Occup.

Terbufos

2.38 (1.35–4.21)

 

Miligi (2006)

CC

1925/1232

Questionnaire

Occup.

   

Beane Freeman (2005)

Co

23106

Questionnaire

Occup.

Diazinon

3.36 (1.08–10.49)

0.026

Cantor and Silberman (1999)

Mr

9961

 

Occup.

SMR: 3.35

 

Ciccone et al. (1993)

CC

67/246

Interview

Occup.

4.4 (1.7–11.5)

 

Brown (1990)

CC

578/1245

Interview

Occup.

Crotoxyphos

Dichlorvos

Famphur

Pyrethroids

Methoxychlor

11.1 (2.2–55.0)

2.0 (1.2–3.5)

2.2 (1.0–5.0)

3.7 (1.3–10.6)

2.2 (1.0–5.0)

 

Van Maele-Fabry (2008)

MA

14 studies

(1984–2004)

 

Occup.

1.43 (1.05–1.94)

 

Van Maele-Fabry (2007)

MA

17 Co

(1979–2005)

 

Occup.

1.21 (0.99–1.48)

 

Merhi (2007)

MA

13 CC

(1990–2005)

 

1.35 (0.9–2)

 

Hodgkin lymphoma

Navaranjan (2013)

CC

316/1506

Interview

 

Insecticides

OPs

Carcinogen pesticides

1.88 (0.92–3.87)

3.16 (1.02–9.29)

2.47 (1.06–5.75)

 

Karunanayake (2012)

CC

316/1506

Interview

 

Chlorpyrifos

1.19 (1.03–1.37)

 

Pahwa (2009)

CC

316/1506

Interview

 

Dichlorprop

6.35 (1.56–25.92)

 

Rudant (2007)

CC

130/1681

questionnaire

Mat.

Household use

4.1 (1.4–11.8)

 

Orsi et al. (2007)

CC

824/752

Interview

Occup.

2.2 (1.0–4.7)

 

van Balen et al. (2006)

CC

591/631

Interview

Occup.

Non-arsenicals

1.8 (1.1 to 2)

 

Flower (2004)

Co

17357

Questionnaire

Par.

2.56 (1.06–6.14)

 

Cerhan (1998)

Mr

88090

Death certificate

Occup.

PMR; 1.62 (1.04–2.54)

 

Persson (1993)

CC

31/93

Questionnaire

Occup.

Phenoxy herbicides

Other pesticides

2.6 (1.4–40)

2.0 (0.05–3.2)

 

Non-hodgkin lymphoma

Nordstrom (1998)

CC

121/484

Interview

Occup.

Insecticides

Herbicides

Fungicides

2.0 (1.1–3.5)

2.9 (1.4–5.9)

3.8 (1.4–9.9)

 

Schinasi (2015)

Co

76493

Questionnaire

Occup.

Insecticides

1.12 (0.95–1.32)

 

Coggon (2015)

Co

8036

Questionnaire

Occup.

Phenoxy herbicides

SMR; 1.85 (1.12–2.89)

 

Schinasi and Leon (2014)

MA

44 studies

  

OPs

Carbamates

Phenoxy herbicides

Lindane

1.6 (1.4–1.9)

1.7 (1.3–2.3)

1.4 (1.2–1.6)

1.6 (1.2–2.2)

 

Alavanja (2014)

Co

54,306

Questionnaire

Occup.

Lindane

DDT

2.5 (1.4–4.4)

1.7 (1.1–2.6)

0.004

0.02

Balasubramaniam (2013)

CC

390/1383

Interview

Occup.

3.1 (1.5–6.2)

<0.01

Karunanayake (2013)

CC

75/321

Questionnaire

Occup.

3.08 (1.26–7.53)♂

 

Boccolini Pde (2013)

Ec

552 micro-region

GIS

Gen.

MRR; 2.92 (2.74–3.11)♂

MRR; 3.20 (2.98–3.43)♀

 

Bräuner (2012)

Co

57053

Adipose tissue level

 

DDT

cis-nonachlor

Oxychlordane

1.35 (1.10–1.66)

1.13 (0.94–1.36)

1.11 (0.89–1.38)

 

Pahwa (2012a)

CC

513/1506

Interview

Occup.

Phenoxy herbicide

2.67 (0.90–7.93)

 

Viel (2011)

CC

34/34

Serum level

Res.

β-HCH

DDT

1.05 (1.00–1.12)

1.20 (1.01–1.45)

 

Bonner (2010)

Co

57310

Questionnaire

Occup.

Terbufos

1.94 (1.16–3.22)

 

Ruder and Yiin (2011)

Co

2122

Plant workers

Occup.

Pentachlorophenol

SMR; 1.77 (1.03–2.84)

 

Eriksson (2008)

CC

910–1016

Questionnaire

 

Herbicides

Phenoxy herbicides

Glyphosate

Insecticides

1.72 (1.18–2.51)

2.81 (1.27–6.22)

2.26 (1.16–4.40)

1.28 (0.96–1.72)

 

Vajdic (2007)

CC

694/694

Questionnaire

Occup.

4.23 (1.76–10.16)

 

Rudant (2007)

CC

166/1681

Questionnaire

Mat.

Pat.

Household use

Household use

1.8 (1.3–2.6)

1.7 (1.2–2.6)

 

Purdue (2007)

Co

57311

Questionnaire

Occup.

Lindane

2.6 (1.1–6.4)

0.04

Merhi (2007)

MA

13 CC

(1990–2005)

  

1.35 (1.2–1.5)

 

Chiu (2006)

CC

385/1432

Interview

Gen.

Animal insecticides

Crop insecticides

Herbicides

Fumigants

2.6 (1.0–6.9)

3.0 (1.1–8.2)

2.9 (1.1–7.9)

5.0 (1.7–14.5)

 

Miligi (2006)

CC

1925/1232

Questionnaire

Occup.

2,4-D

4.4 (1.1–29.1)

 

De Roos (2003)

CC

870/2569

Interview

Gen.

Coumaphos

Diazinon

Fonofos

Chlordane

Dieldrin

Atrazine

Glyphosate

2.4 (1.0–5.8)

1.9 (1.1–3.6)

1.8 (0.9–3.5)

1.5 (0.8–2.6)

1.8 (0.8–3.9)

1.6 (1.1–2.5)

2.1 (1.1–4.0)

 

Hardell (2002)

CC

515/1141

Questionnaire

 

Herbicides

Insecticides

Fungicides

1.75 (1.26–2.42)

1.43 (1.08–1.87)

3.11 (1.56–6.27)

 

Schroeder (2001)

CC

182/

Questionnaire

Occup.

Dieldrin

Toxaphene

Lindane

Atrazine

Fungicides

3.7 (1.9–7.0)

3.0 (1.5–6.1)

2.3 (1.3–3.9)

1.7 (1.0–2.8)

1.8 (0.9–3.6)

 

McDuffie (2001)

CC

517/1506

Interview

 

Phenoxyherbicides

Dicamba

Carbamate

OPs

1.38 (1.06–1.81)

1.88 (1.32–2.68)

1.92 (1.22–3.04)

1.73 (1.27–2.36)

 

Meinert (2000)

CC

234/2588

Interview

Par.

Insecticides

2.6 (1.2–5.7)

0.02

Buckley (2000)

CC

268/268

Interview

Res.

Household use

7.3

0.05

Hardell and Eriksson (1999)

CC

442/884

Interview

Gen.

Herbicides

Fungicides

1.6 (1.0–2.5)

3.7 (1.1–13.0)

 

Kristensen (1996)

Co

323292

Census

Par.

2.47 (1.02–6.15)

 

Clavel (1996)

CC

226/425

Interview

Occup.

1.7 (1.0–2.6)

 

Cantor (1992)

CC

622/1245

Interview

Occup.

Carbaryl

Chlordane

DDT

Diazinon

Lindane

Malathion

1.7 (0.9–3.1)

1.7 (1.0–2.9)

1.7 (1.2–2.6)

1.5 (0.9–2.5)

2.0 (1.0–3.7)

1.5 (0.8–2.7)

 

Zahm (1990)

CC

201/725

Interview

Occup.

2,4-D

1.5 (0.9–2.5)

 

Multiple myeloma

Perrotta (2013)

CC

1959/6192

JEM

Occup.

Garden/nursery use

1.50 (0.9–2.3)

 

Kachuri (2013)

CC

342/1357

Questionnaire

 

Fungicides

Probably carcinogenic

1.73 (1.00–3.00)

1.57 (0.96–2.56)

0.04

0.03

Pahwa (2012b)

CC

342/1506

Questionnaire

 

Carbamate insecticide

Captan fungicide

Carbaryl

1.90 (1.11–3.27)

2.35 (1.03–5.35)

1.89 (0.98–3.67)

 

Perrotta (2012)

CC

277/281

Questionnaire

Occup.

1.62 (1.01–2.58)

 

Landgren (2009)

Co

57310

Questionnaire

Occup.

Age >50 years

6.8 (5.0–9.3)

 

Lope (2008)

Co

2992166

Questionnaire

Occup.

In women

1.29 (0.83–2.00)

 

Merhi (2007)

MA

13 CC

(1990–2005)

 

1.16 (0.99–1.36)

 

Cerhan (1998)

Mr

88090

Death certificate

Occup.

PMR; 1.17 (0.98–1.40))

 

Kristensen (1996)

Co

323292

Census

Par.

2.03 (0.51–8.14)

 

Bone cancer

Carozza (2008)

Ec

1078 counties

GIS

Res.

2.3 (1.8–2.9)

 

Merletti (2006)

CC

96/2632

Interview

Occup.

2.33 (1.31–4.13)

 

Moore (2005)

CC

196/196

Interview

Par.

3.0 (1.1–8.1)

 

Holly (1992)

CC

43/193

Interview

Par.

6.1 (1.7–21.9)

0.002

Thorpe and Shirmohammadi (2005)

Ec

Maryland

Groundwater

Res.

Metolachlor

2.26 (0.97–5.24)

 

Soft tissue sarcoma

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res., Occup.

MRR; 1.93(1.75–2.12)

0.015

Carozza (2008)

Ec

1078 counties

GIS

Res.

1.7 (1.4–2.0)

 

Kogevinas (1995)

Nested CC

11/55

Interview

Occup.

Phenoxy herbicides

10.3 (1.2–91)

 

Leiss and Savitz (1995)

CC

252/222

Interview

Indoor

Yard treatment

4.1 (1.0–16.0)

 

Kidney/renal cancer

Karami (2008)

CC

1097/1476

Interview

Occup.

1.60 (1.00–2.55)

 

Carozza (2008)

Ec

1078 counties

GIS

Res.

3.3 (1.3–8.3)

 

Tsai (2006)

CC

303/575

Interview

Mat.

1.41 (0.91–2.20)

Wilms

Buzio et al. 2003

CC

100/200

Questionnaire

Occup.

+ GSTM1 polymorph

3.46 (1.12–10.74)

 

Buzio (2002)

CC

100/200

Questionnaire

Occup.

2.0 (0.8–4.7)

 

Hu et al. (2002)

CC

1279/5370

Questionnaire

Occup.

Pesticides

Herbicides

4.6 (1.7–12.5)

1.6 (1.3–2.0)

 

Fear (1998)

Mr

167703

 

Pat.

PMR; 1.59 (1.18–2.15)

 

Kristensen (1996)

Co

323292

Census

Par.

8.87 (2.67–29.5)

Wilms

Sharpe (1995)

CC

109/218

Interview

Pat.

Mat.

3.24 (1.2–9.0)

128.6 (6.4–2,569)

Wilms

Wilms

Mellemgaard (1994)

CC

365/396

Interview

Occup.

Insecticides/herbicides

2.2 (0.8–6.3)♂

5.7 (0.6–58)♀

 

Olshan (1993)

CC

200/233

Interview

Mat.

Household pesticide

2.16 (1.24–3.75)

 

Forastiere (1993)

CC

1674/480

Questionnaire

Occup.

Olive crop used

3.16 (1.0–12.1)

<0.1

Bladder cancer

Koutros (2015)

Co

57 310

Questionnaire

Occup.

Imazaquin herbicide

Imazethapyr herbicide

1.54 (1.05–2.26)

3.03 (1.46–6.29)

0.005

Amr (2015)

CC

953/881

 

Occup.

1.68 (1.23–2.29)

 

Matic (2014)

CC

143/114

 

Occup.

+ GSTT1 polymorphism

4.5 (0.9–22.5)

 

Sharma (2013)

CC

50/50

Blood level

 

Total-HCH, DDT

↑ risk

<0.05

Koutros (2009)

Co

57311

Questionnaire

Occup.

Imazethapyr herbicide

2.37 (1.20–4.68)

0.01

Prostate cancer

Koutros (2013a, b)

CC

776/1444

Interview

Occup.

Malathion + EHBP1-SNP

Aldrin +TET2-SNP

3.43 (1.44–8.15)

3.67 (1.43, 9.41)

 0.003

 0.006

Karami (2013)

CC

776/1444

Interview

Occup.

Parathion + Vit D gene

3.09 (1.10–8.68)

 

Koutros (2013a, b)

Co

54412

Census

Occup.

Fonofos

Malathion

Terbufos

Aldrin

1.63 (1.22–2.17)

1.43 (1.08–1.88)

1.29 (1.02–1.64)

1.49 (1.03–2.18)

0.001

0.04

0.03

0.02

Budnik et al. (2012)

MA

3 studies

 

Occup.

Methyl bromide

1.21 (0,98–1.49)

0.076

Barry (2011)

CC

776/1444

Interview

Occup.

Fonofos + CT/TT-SNP

3.25 (1.78–5.92)

 

Cockburn (2011)

CC

173/162

GIS

Res.

Methyl bromide

Organochlorines

1.62 (1.02–2.59)

1.64 (1.02–2.63)

 

Band (2011)

CC

1516/4994

JEM

Occup.

Dichlone

Maneb

Ziram

Simazine

Azinphos-methyl

Carbaryl

DDT

Diazinon

Lindane

Malathion

1.88 (1.01–3.52)

1.9 (1.09–3.30)

1.83 (1.08–3.10)

1.89 (1.08–3.33)

1.88 (1.06–3.32)

1.73 (1.09–2.74)

1.68 (1.04–2.70)

1.93 (1.21–3.08)

2.02 (1.15–3.55)

1.49 (1.02–2.18)

0.02

0.02

0.03

0.01

0.01

0.01

0.03

0.02

0.03

0.03

Koutros (2011)

CC

776/1444

Interview

Occup.

Terbufos + MPO-SNP

3.0 (1.5–6.0)

0.002

Koutros (2010a, b)

Co

52394

Census

Occup.

Private use

Commercial use

1.19 (1.14–1.25)

1.28 (1.00–1.61)

0.002

Multigner (2010)

CC

623/671

Plasma level

Gen.

Chlordecone

1.77 (1.21–2.58)

 

Christensen (2010)

Co

47822

Questionnaire

Occup.

Coumaphos

1.65 (1.13–2.38)

0.004

Bonner (2010)

Co

57310

Questionnaire

Occup.

Terbufos

1.21 (0.99–1.47)

 

Koutros (2010a, b)

CC

776/1444

Interview

Occup.

Fonofos + 8q24 variants

4.46 (2.17–9.17)

0.002

Parent (2009)

CC

49/183

Interview

Occup.

2.3 (1.1–5.1)

 

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res., Occup.

MRR; 1.66 (1.63–1.69)

0.019

Chamie (2008)

Co

13144

Veterans

Occup.

Agent Orange

2.19 (1.75–2.75)

 

Meyer (2007)

CC

405/392

Interview

Occup.

1.6 (1.2–2.2)

 

Settimi (2003)

CC

124/659

Interview

Occup.

Organochlorines

2.5 (1.4–4.2)

 

Alavanja (2003)

Co

55332

Questionnaire

Occup.

Methyl bromide

3.47 (1.37–8.76)

0.004

Mills and Yang (2003)

Nested CC

222/1110

 

Occup.

Methyl bromide

1.59 (0.77–3.30)

0.25

MacLennan (2002)

Co

2045

Workers

Occup.

Triazine herbicides

SIR; 394 (128–920)

 

Fleming (1999)

Co

33658

Applicators

Occup.

SIR; 1.91 (1.72–2.13)

 

Cerhan (1998)

Mr

88090

Death certificate

Occup.

PMR; 1.26 (1.19–1.33)

 

Dich and Wiklund (1998)

Co

20025

Applicators

Occup.

SIR; 1.13 (1.02–1.24)

 

Forastiere (1993)

CC

1674/480

Questionnaire

Occup.

2.13 (0.64–6.49)

 

Morrison (1993)

Ret. Co

1148

Acres sprayed

Occup.

Herbicides

2.23 (1.30–3.48)

<0.01

Testicular cancer

Giannandrea (2011)

CC

50/48

Serum level

Res.

DDE, HCB

3.15 (1.00–9.91)

 

Fleming (1999)

Co

33658

Questionnaire

Occup.

SIR; 2.48 (1.57–3.72)

 

Breast cancer

Parada (2016)

Mr

633

Blood level

DDT

2.72 (1.04–7.13)

 

Niehoff (2016)

Co

50884

Interview

Gen.

DDT

1.3 (0.92–1.7)

 

Lerro (2015a, b)

Co

30003

Questionnaire

Occup.

OPs

1.20 (1.01–1.43)

 

Arrebola (2015)

CC

69/56

Serum level

 

β-HCH

DDE

3.44 (1.30–9.72)

9.65 (1.81–63.33)

<0.1

<0.05

Yang (2015)

CC

75/79

Blood level

 

β-HCH, PCTA

↑ OCs level

<0.05

   

Adipose tissue

 

β-HCH, DDE, PCTA

↑ OCs level

<0.05

Tang et al (2014a, b)

CC

78/72

Serum level

Diet

DDT

1.95 (0.95–4.00)

 

El-Zaemey (2013)

CC

1743/1169

Self-report

Occup.

1.43 (1.15, 1.78)

 

Boada (2012)

CC

121/103

Serum level

 

DDD

1.008 (1.001–1.015)

0.024

Ortega Jacome (2010)

CC

110/110

Questionnaire

Res.

2.15 (1.22–3.77)

 

Teitelbaum (2007)

CC

1508/1556

Interview

Res.

1.39 (1.15, 1.68)

 

Engel (2005)

Co

30454

Questionnaire

Occup.

2,4,5-TP

Captan

2.0 (1.2–3.2)

2.7 (1.7–4.3)

 

Charlier (2003)

CC

159/250

Blood level

 

DDT

HCB

5.36 (1.89–15.19)

8.68 (2.83–26.62)

 

Mills and Yang (2005)

CC

128/640

Questionnaire

Occup.

1.41 (0.66–3.02)

 

Duell (2000)

CC

862/790

Interview

Occup.

1.8 (1.1–2.8)

 

Ovarian cancer

Lerro (2015a, b)

Co

30003

Questionnaire

Occup.

Diazinon

1.87 (1.02–3.43)

 

Koutros (2010a, b)

Co

52394

Census

Occup.

Private use

2.45 (1.12–4.65)

 

Donna (1989)

CC

 

Interview

Occup.

Triazine herbicides

2.7 (1.0–6.9)

 

Cervical cancer

Fleming (1999)

Co

33658

Questionnaire

Occup.

SIR; 3.69 (1.84–6.61)

 

Eye cancer

Abdolahi (2013)

CC

198/245

Interview

Pat.

10 years preconception

1 year preconception

1.64 (1.08–2.50)

2.12 (1.25–3.61)

 

Carozza (2008)

Ec

1078 counties

GIS

Res.

2.6 (1.9–3.5)

 

Kristensen (1996)

Co

323292

Census

Par.

3.17 (0.93–10.9)

 

Laryngeal cancer

Bravo (1990)

CC

85/170

Interview

Occup.

Insecticides

↑risk

 

Lip cancer

de Rezende Chrisman (2009)

Ec

11 states

Pesticide sales

Res. Occup.

MRR; 5.61 (4.88–6.35)

0.01

Rafnsson (2006)

Co

8311

Questionnaire

Occup.

Lindane

1.50 (1.08–2.04)♂

9.09 (1.02–32.82)♀

 

Cerhan (1998)

Mr

88090

Death certificate

Occup.

PMR; 1.58 (0.59–4.21)

 

Wiklund (1983)

Ret. Co

354228

Questionnaire

Occup.

1.83 (1.62–2.05)

 

Mouth cancer

Tarvainen L

Co

 

JEM

Occup.

1.77 (0.85–3.26)

 

Lung cancer

Lerro (2015b)

Co

33484

Interview

Occup.

Acetochlor

1.74 (1.07–2.84)

 

Zendehdel et al. (2014)

MA

5 Co

 

Occup.

Chlorophenols, phenoxyacetic acids

SMR; 1.18 (1.03–1.35)

0.014

Luqman (2014)

CC

400/800

Questionnaire

Occup.

5.1 (3.1–8.3)

 

Bonner (2010)

Co

57310

Questionnaire

Occup.

Terbufos

1.45 (0.95–2.22)

 

Samanic (2006)

Co

41969

Questionnaire

Occup.

Dicamba

2.16 (0.97–4.82)

0.02

Rusiecki (2006)

Co

50193

Questionnaire

Occup.

Metolachlor

2.37 (0.97–5.82)

0.03

Beane Freeman (2005)

Co

23106

Questionnaire

Occup.

Diazinon

2.41 (1.31–4.43)

0.005

Moore (2005)

CC

196/196

Questionnaire

Par.

Household pesticides

3.0 (1.1–8.1)♂

 

Lee (2004a, b)

Co

54383

Questionnaire

Occup.

Chlorpyrifos

2.18 (1.31–3.64)

0.002

Alavanja (2004)

Co

57284

Questionnaire

Occup.

Metolachlor

Pendimethalin

Chlorpyrifos

Diazinon

5.0 (1.7–14.9)

4.4 (1.2–15.4)

1.9 (0.9–4.0)

3.2 (1.1–8.9)

0.0002

0.003

0.03

0.04

Pesatori (1994)

Nested CC

65/294

Interview

Occup.

2.4 (1.0–5.9)

 

Brownson (1993)

CC

429/294

Interview

Occup.

2.4 (1.1–5.6)

 

Thyroid cancer

Lerro (2015a, b)

Co

30,003

Questionnaire

Occup.

Malathion

2.04 (1.14–3.63)

 

Freeman (2011)

Co

57,310

Questionnaire

Occup.

Atrazine

4.84 (1.31–17.93)

0.08

Lee (2004a, b)

Co

49,980

Questionnaire

Occup.

Alachlor

1.63 (0.42–6.37)

 

Pukkala (2009)

Co

15,000,000

Farmers

Occup.

SIR; 1.18 (1.07–1.30)

 

Skin cancer

Lerro (2015b)

Co

33,484

Interview

Occup.

Acetochlor

1.61 (0.98–2.66)

 

Segatto (2015)

CC

95/96

Interview

Occup.

2.03 (1.03–6.89)

 

Dennis (2010)

Co

52394

Questionnaire

Occup.

Maneb/mancozeb

Parathion

Carbaryl

2.4 (1.2–4.9)

2.4 (1.3–4.4)

1.7 (1.1–2.5)

0.006

0.003

0.013

Mahajan (2007)

Co

21416

Questionnaire

Occup.

Carbaryl (>175 days)

4.11 (1.33–12.75)

0.07

Fortes (2007)

CC

287/299

Interview

Indoor

2.18 (1.07–4.43)

0.027

♂: risk found in male, ♀: risk found in female, MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, PMR proportional mortality ratio, SMR standard mortality ratio, MRR mortality rate ratio, SIR standard incidence ratio, ALL acute lymphocytic leukemia, AML acute myeloblastic leukemia, ChE cholinesterase, OPs organophosphoruses, OCs organochlorines, 2,4-D 2,4-dichlorophenoxyacetic acid, 2,4,5-T 2,4,5-trichlorophenoxyacetic acid, EPTC S-ethyl-N,N-dipropylthiocarbamate, HCB hexachlorobenzene, β-HCH beta-hexachlorocyclohexane, PCTA pentachlorothioanisole, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene, DDD dichlorodiphenyldichloroethane, GST glutathione-S-transferase

Tumors of the nervous system

Brain tumors

In general, studies concerning the environmental risk factors of brain tumors are separately conducted in children and adults. The link of childhood brain tumors (CBT) with pesticides is mostly studied in the form of parental, maternal, or paternal exposures. Results of a prospective cohort study of cancer in the offspring of agricultural censuses in Norway showed that parental exposure to pesticides is associated with three times higher incidence of CBT especially in children aged under 14 years (Kristensen et al. 1996). The other case–control studies assessing exposure to different classes of pesticides via organized questionnaire-based interviews indicated that incidence of CBT was increased up to 1.3–2 times in children parentally exposed to pesticides (Efird et al. 2003; Greenop et al. 2013; Pogoda and Preston-Martin 1997; Rosso et al. 2008; Shim et al. 2009; van Wijngaarden et al. 2003). Searles Nielsen and colleagues’ studies on the role of genetic polymorphisms of PON1 and FMO1 in the link between pesticides and CBT implicated that prenatal and postnatal exposures to organophosphorus compounds and perhaps carbamates in people with reduced ability to detoxification were associated with a higher incidence of CBT (Searles Nielsen et al. 2005, 2010). However, there are other studies whose results have been meta-analyzed in some systematic reviews. A meta-analysis of 40 studies found an incidence risk of about times for CBT in children paternally exposed to pesticides (Vinson et al. 2011). In this regard, there is another study, which meta-analyzed the results of 15 studies on the association of CBT with paternal, maternal, and childhood exposures to pesticides and the highest risk estimate of CBT was reported for children whose fathers were exposed to pesticides before conception (Kunkle et al. 2014).

The link of adult brain tumors (ABT) with pesticides has been mostly studied in the populations occupationally dealing with pesticides. Since the disease has a high intrinsic severity, some researchers have reported high mortality ratio as of 200 and 270 due to brain tumors in licensed pesticide users (Blair et al. 1983; Figa-Talamanca et al. 1993). Furthermore, Viel et al. (1998) reported higher mortality ratio of brain cancer in an ecological model assessment of vineyard pesticide-exposed farmers. Some other case–control studies found an approximately doubled risk of being occupationally exposed to pesticides in cases of brain tumors compared with control. Among these studies, some reported the association of ABT with specified class of pesticides such as herbicides albeit in women (Samanic et al. 2008), and insecticides/fungicides (Musicco et al. 1988), while other evidence of risk of ABT was referred to any class of pesticides (Provost et al. 2007; Rodvall et al. 1996). In this regard, Lee and colleagues’ analysis of cases of ABT in comparison with controls revealed elevated odd ratios as 22.6, 18.9, 11.1, 5.9, and 3.4 for participants occupationally exposed to chlorpyrifos, bufencarb, paraquat, coumaphos, and metribuzin, respectively (Lee et al. 2005).

Neuroblastoma

Because of the high prevalence of neuroblastoma in infancy and childhood, its association with parental exposure to pesticide has been well studied and the relative risk of about 2.3 reported by two surveys (Feychting et al. 2001; Kristensen et al. 1996). Carozza and colleagues studied the association of childhood cancers in an ecologic analysis of geographic information system (GIS) and reported an OR of 1.8 for the association of residential exposure to pesticides and neuroblastoma in children living in agricultural areas (Carozza et al. 2008). Residential exposure has also been studied in a case–control study of neuroblastoma, and the ORs were resulted as 1.6 and 1.7 for home-used and garden-used pesticides, respectively (Daniels et al. 2001). Furthermore, elevated SMRs due to neuroblastoma were reported by two cohort studies on pesticide applicators (Giordano et al. 2006; Littorin et al. 1993).

Tumors of the digestive system

Esophageal cancer

Chrisman and colleagues’ ecological study on 11 states in Brazil regarding residential or occupational exposure to pesticides revealed an elevated MRR of 2.4 for esophageal cancer (de Rezende Chrisman et al. 2009). There are also two case–control studies on the association of esophageal cancer with occupational exposure to pesticides among which one assessing the airborne level of pesticides has given an OR of 2.3 (Jansson et al. 2006) and the other death certificate-based study reported an OR of 1.38 (Meyer et al. 2011).

Stomach cancer

A study on the link of stomach cancer with occupational exposure to pesticides in a questionnaire-based case–control analysis gave an OR of 1.77 without determining specified pesticides (Forastiere et al. 1993). But other studies in this regard have presented risk estimates of stomach cancer in association with exposure to specified pesticides. An ecological study of 40 ecodistricts in Ontario (Canada) assessed the relation between incidence of stomach cancer and environmental exposure to atrazine measured in drinking water and gave an OR of 1.45 implicated on a significant association (p value <0.05) (Van Leeuwen et al. 1999). Mills and colleagues carried out a nested case–control study on the link of stomach cancer with occupational exposure to different classes of pesticides and found elevated risks regarding 2,4-dichlorophenoxyacetic acid (2,4-D), chlordane, and trifluralin given by ORs of 1.85, 2.96, and 1.69, respectively (Mills and Yang 2007). A significant association of stomach cancer with occupational exposure to methyl bromide was also resulted by a cohort study (Barry et al. 2012).

Colorectal cancer

In two separated questionnaire-based case–control studies determining occupational exposure to generally pesticides in cases and controls, the ORs of colorectal cancer were estimated as 2.6 and 2.8. One of these studies calculated the risk estimates of colorectal cancer in association with insecticides and herbicides as well and reported ORs of 3.2 and 5.5, respectively. Further estimate was carried out regarding dietary exposure to pesticides and risk of colorectal cancer represented by an OR of 4.6 (Forastiere et al. 1993; Lo et al. 2010). Among cohort studies analyzing the risk of colorectal cancer in people occupationally exposed to pesticides, apart from one study reporting a tripled incidence ratio (Zhong and Rafnsson 1996), the others estimated the risk regarding specified species of pesticides. Aldicarb, dicamba, imazethapyrc, chlorpyrifos, S-ethyl-N,N-dipropyl thiocarbamate (eptam or EPTC), trifluralin, and acetochlor were the pesticides, arranged in order, for which elevated risk ratios of colorectal cancer reported in occupationally exposed people (Kang et al. 2008; Koutros et al. 2009; Lee et al. 2007b; Lerro et al. 2015b; Samanic et al. 2006; van Bemmel et al. 2008). Recently, Salerno et al. carried out a GIS-based ecological study focusing on the cancer risk among farmers in a province of Italy and reported a double risk of colorectal cancer which may be representative of exposure to pesticides (Salerno et al. 2014).

Liver cancer

Ecological analyses on the link of pesticides and incidence of liver cancer were carried out in two separated studies whose results implicated on the elevated OR as 3.3 for residential exposure assessed by GIS on 1078 counties (Carozza et al. 2008) and increased MRR as 1.49 for residential or occupational exposure estimated on the basis of pesticides sale in 11 states (de Rezende Chrisman et al. 2009). Moreover, a high SMR 596.3 due to liver cancer was found in a cohort study conducted on pesticide applicators (Giordano et al. 2006). VoPham et al. compared the cases of liver cancer with matched controls via a GIS-based exposure assessment tool and reported a significant association between exposure to organochlorine pesticides and the incidence of liver cancer given by the OR of 2.76 and a p value of 0.0004 (VoPham et al. 2015).

Gallbladder cancer

In a cohort study conducted by Giordano and colleagues on pesticide applicators, a high mortality ratio due to gall bladder cancer was noted with an SMR of 723.8 (Giordano et al. 2006). Further, biliary level of some organochlorine pesticides was measured in a case–control study, and an increased level of hexachlorobenzene (HCB) (p value <0.04) and dichlorodiphenyltrichloroethane (DDT) (p value <0.03) was found in the gall bladder cancer cases in comparison with controls (Shukla et al. 2001).

Pancreatic cancer

In 1990, Alavanja and colleagues published the results of cohort mortality and a nested case–control analyses of more than 22000 males. Subjects were enrolled in the life insurance program, and an estimated SMR of 133 due to pancreatic cancer among flour mill workers which were frequently exposed to pesticides (Alavanja et al. 1990). In the same decade, another study found a significantly elevated risk ratio of mortality due to pancreatic cancer among aerial pesticide applicators (Cantor and Silberman 1999). Chrisman and colleagues also reported a high mortality rate ratio of pancreatic cancer in association with per capita sales of pesticides in an ecological study conducted in 11 states of Brazil (de Rezende Chrisman et al. 2009). There are different types of case–control studies on the link between exposure to pesticides and incidence of pancreatic cancer. Regarding occupational exposure to pesticides, an OR of 5.18 was reported for pancreatic cancer by a case–control analysis (Forastiere et al. 1993). ORs including 1.2 and 2.6 were estimated for pancreatic cancer in association with regular exposure to pesticides in two separated case–control studies (Antwi et al. 2015; Lo et al. 2007). Alguacil et al. conducted a case–control study assessing exposure to pesticides via a job exposure matrix (JEM) and estimated a tripled risk of pancreatic cancer in people occupationally exposed to pesticides. In that study, arsenical pesticides were shown to be associated with higher incidence of pancreatic cancer given by OR of 3.4 (Alguacil et al. 2000). Another JEM-based case–control study found significantly elevated ORs including 1.4, 1.5, and 1.6 for pancreatic cancer due to occupational exposure to pesticides, fungicides, and herbicides, respectively (Ji et al. 2001). Occupational exposure to herbicides (EPTC and pendimethalin) was shown to be (p value <0.01) associated with double and triple risks of pancreatic cancer, respectively (Andreotti et al. 2009). Furthermore, an increased relative risk of pancreatic cancer (2.36) in association with occupational exposure to acetochlor herbicide was the finding of the Agricultural Health Study (Lerro et al. 2015b).

Tumors of the hematopoietic system

Leukemia

Similar to the brain tumors, studies concerning the link of leukemia with exposure to pesticides are separately designed and conducted with respect to the age of the target population. Regarding childhood leukemia, lots of case–control and other types of epidemiological studies have targeted the association with different routes of exposure, including residential exposure due to indoor or outdoor use of pesticides and parental exposure due to maternal or paternal activities. The results of these studies have been frequently meta-analyzed in various models, and risk of childhood leukemia regarding exposure to pesticides has been estimated. A meta-analysis of 31 case–control studies published between 1950 and 2009 reported a higher risk of leukemia in children whose mothers dealt with pesticides, insecticides, and herbicides given by ORs of 2.09, 2.72, and 3.62, respectively (Wigle et al. 2009). Another meta-analysis done by Vinson and colleagues on 40 case–control studies assessing maternal exposure to pesticides indicated an elevated OR of 1.48 for leukemia in children (Vinson et al. 2011). Regarding residential exposures, a meta-analysis of 17 case–control studies published between 1950 and 2009 found an elevated ORs including 1.54, 2.05, and 1.61 for incidence of leukemia in children exposed to pesticides, insecticides, and herbicides, respectively (Turner et al. 2011). Further, the results of 16 case–control studies assessing residential exposure in children were meta-analyzed, and 1.4 and 1.2 times elevated risks of childhood leukemia were found in respect to indoor-used pesticides and herbicides (Chen et al. 2015). A meta-analysis of 13 case–control studies published between 1966 and 2009 found an elevated risk estimate of about 1.74 for the link of childhood leukemia with maternal or residential exposure to pesticides (Van Maele-Fabry et al. 2011). Another type of meta-analysis done by Baily and colleagues pooled the results of 13 case–control studies assessing exposure to pesticides in the offspring of parents occupied in the pesticide-related jobs and found associations between childhood AML and maternal exposure, and between childhood ALL and paternal exposure, represented by elevated ORs as 1.9 and 1.2, respectively (Bailey et al. 2014).

Regarding the link of adult leukemia with pesticide exposures, several epidemiological studies have become evident so that their results have been meta-analyzed in different formats. A meta-analysis of 13 case–control studies published between 1990 and 2005 showed that exposure to pesticides and incidence of adult leukemia were associated with an OR of 1.35 (Merhi et al. 2007). Van Maele-Fabry and colleagues meta-analyzed the results of 17 cohort studies published between 1979 and 2005 and found an increased risk estimate (1.2) of leukemia in adults occupationally exposed to pesticides (Van Maele-Fabry et al. 2007). Their another meta-analysis of 14 studies published between 1984 and 2004 revealed 1.4 times higher risk of adult leukemia in association with occupational exposure to pesticides (Van Maele-Fabry et al. 2008). Occupational exposure to crotoxyphos, dichlorvos, famphur, pyrethroids, and methoxychlor was shown to be associated with higher incidence of leukemia in a case–control study (Brown et al. 1990). A high incidence of leukemia was also reported by three separated cohort studies conducted on people occupationally exposed to Agent Orange, terbufos, and diazinon with estimated risks of 1.8, 2.3, and 3.3, respectively (Baumann Kreuziger et al. 2014; Beane Freeman et al. 2005; Bonner et al. 2010). Moreover, Cantor et al. showed that the mortality ratio of leukemia was tripled in people occupationally exposed to pesticides (Cantor and Silberman 1999).

Lymphoma

Regarding the tumors of the lymphoid tissues, pesticide exposures have been mostly studied for two main categories of lymphomas, including Hodgkin lymphomas (HL) and non-Hodgkin lymphomas (NHL). Other than one cohort and one mortality studies, 7 case–control analyses have been obtained through this systematic review for HL. The cohort study calculated nearly a triple risk of HL due to parental exposure to pesticides, while the mortality study found a PMR of 1.6 for HL in people occupationally exposed to pesticides (Cerhan et al. 1998; Flower et al. 2004). Among case–control studies, those without determining a specific class of pesticides estimated ORs ranging from 1.8 to 2.2 for HL in association with occupational exposure to pesticides, while the others have reported specified ORs including 1.88, 3.16, 2.47, 4.1, and 2.6 for the link of HL with, respectively, insecticides, organophosphorus compounds, carcinogenic pesticides, household-used pesticides, and phenoxy herbicides, and more specifically, 1.19 and 6.35 for chlorpyrifos and dichlorprop (Karunanayake et al. 2012; Navaranjan et al. 2013; Pahwa et al. 2009; Persson et al. 1993; Rudant et al. 2007).

However, the number of studies targeting the link of NHL and pesticide’ exposures is much more than that of HL which may be due to higher prevalence (90 %) of NHL among lymphomas. In this systematic review, a total of 29 studies, including 20 case–control, 8 cohort, and 1 ecological analyses on the link of pesticide exposures with NHL have been collected from which 21 calculated the risk estimate regarding specified classes of pesticides.

Of seven studies not determining the type of pesticides in association with NHL, one cohort study reported RR of 2.47 due to parental exposure and one GIS-based ecological study reported MRRs of 2.9 and 3.2 due to NHL in men and women, respectively (Boccolini Pde et al. 2013; Kristensen et al. 1996). Remaining 5 studies are case–control whose results implicate on the higher incidence of NHL in people exposed to pesticides as given by ORs ranging from 1.7 to 7.3 (Balasubramaniam et al. 2013; Buckley et al. 2000; Clavel et al. 1996; Karunanayake et al. 2013; Rudant et al. 2007; Vajdic et al. 2007).

All of the studies in this systematic analysis, which have estimated the risk of NHL in association with the specified class or type of pesticides, have been designed and conducted in case–control or cohort format composed of different sample numbers. Elevated risk estimates ranging from 1.1 to 3, 1.6 to 2.9, and 1.8 to 3.8 have been reported for NHL in association with exposure to insecticides, herbicides, and fungicides, respectively. Further, five times higher incidence of NHL in people exposed to fumigants has been indicated by Chiu and colleagues (Chiu et al. 2006; Eriksson et al. 2008; Hardell and Eriksson 1999; Hardell et al. 2002; Meinert et al. 2000; Nordstrom et al. 1998; Schinasi et al. 2015; Schroeder et al. 2001).

Exposure to organophosphorus and carbamate compounds have been shown to be associated with, respectively, 1.7 and 1.9 times higher incidence of NHL by a case–control analysis, as such results have been calculated by a meta-analysis of 44 studies (McDuffie et al. 2001; Schinasi and Leon 2014). In these classes of insecticides, higher risk estimates of NHL were reported for people exposed to malathion (1.5), diazinon (1.5, 1.9), terbufos (1.9), coumaphos (2.4), fonofos (1.8), and carbaryl (1.7) (Bonner et al. 2010; Cantor et al. 1992; De Roos et al. 2003). Among organochlorine insecticides, elevated risk estimates ranging from 1.6 to 2.6, 1.2 to 1.7, 1.8 to 3.7, and 1.5 to 1.7 have been reported for lindane, DDT, dieldrin, and chlordane, respectively. The risk of NHL has also been calculated in association with exposure to the other organochlorine insecticides, including toxaphene (3.0), oxychlordane (1.1), cis-nonachlor (1.1), and beta-hexachlorocyclohexane (β-HCH) (1.05) (Alavanja et al. 2014; Brauner et al. 2012; Cantor et al. 1992; De Roos et al. 2003; Purdue et al. 2007; Schinasi and Leon 2014; Schroeder et al. 2001; Viel et al. 2011). Ruder and Yiin (2011) have shown higher mortality ratio of NHL in a cohort of plant workers who were occupationally exposed to pentachlorophenol.

The specific link of NHL and herbicides has been mostly evaluated for phenoxy class of herbicides for which elevated ORs ranging from 1.4 to 2.8 have been estimated by three separated case–control studies (Eriksson et al. 2008; McDuffie et al. 2001; Pahwa et al. 2012a). Coggon and colleagues conducted a cohort study on 8036 participants occupied in phenoxy herbicides-manufacturing plants, and the results revealed a high mortality ratio of NHL among workers (Coggon et al. 2015). The ORs as high as 1.5 and 4.4 have also been reported for the risk of NHL in people occupationally exposed to 2,4-dichlorophenoxy acetic acid (2,4-D) by two case–control studies (Miligi et al. 2006; Zahm et al. 1990). The link of NHL with exposure to other specific herbicides including atrazine and glyphosate has also been studied in three case–control studies, and increased ORs ranging from 1.6 to 1.7 and 2.1 to 2.3 have been estimated, respectively (De Roos et al. 2003; Eriksson et al. 2008; Schroeder et al. 2001).

Multiple myeloma

Similar to the other malignancies of the hematopoietic system, multiple myeloma has also been the target of epidemiological health studies linking with exposure to pesticides. This review found totally 8 relevant including 4 case–control, 3 cohorts and one mortality studies on the link between incidences of multiple myeloma and exposure to pesticides. Cerhan et al. (1998) reported a PMR of about 1.2 due to multiple myeloma among farmers who had been occupationally exposed to pesticides. The results of two separate cohort studies showed that occupational exposure to pesticides is associated with higher incidences of multiple myeloma as given by risk estimates of 1.3 and 6.8 in women and people aged more than 50, respectively (Landgren et al. 2009; Lope et al. 2008). A cohort of agricultural workers occupationally exposed to pesticides showed a doubled RR of multiple myeloma among their offspring (Kristensen et al. 1996). Two case–control studies conducted by Perrotta and colleagues without determining a specific class of pesticides have given ORs of about 1.5 and 1.6 for the incidences of multiple myeloma in people occupationally dealing with pesticides (Perrotta et al. 2012, 2013). The comparison of cases of multiple myeloma with matching controls regarding prevalence of exposure to specific types of pesticides was made by two separate studies. Their results implicate elevated ORs for fungicides (1.7), probably carcinogenic pesticides (1.6), carbamates (1.9), captan (2.3), and carbaryl (1.9) (Kachuri et al. 2013; Pahwa et al. 2012b). A meta-analysis of 13 case–control studies published between 1990 and 2005 showed an OR of about 1.2 for the risk of multiple myeloma in association with exposure to pesticides (Merhi et al. 2007).

Tumors of the bone and soft tissues

Bone tumors

There are two ecological and three case–control studies giving evidence on the link of bone cancer with exposure to pesticides. One of the ecological studies reported the link between residential exposure to pesticides and higher incidence of childhood bone tumors, while another GIS-based ecological study showed an OR of about 2.3 for bone cancers in relation to higher level of metolachlor in groundwater (Carozza et al. 2008; Thorpe and Shirmohammadi 2005). Two separate case–control studies evaluated the Ewing’s sarcoma in children and showed its positive association with parental exposure to pesticides with ORs including 3.0 and 6.1 (Holly et al. 1992; Moore et al. 2005). Comparing adult cases of bone sarcoma in adults with matching controls, 2.3 times higher incidence of occupational exposure to pesticides has been found in cases (Merletti et al. 2006).

Soft tissue sarcoma

Two ecological and three case–control studies are the results of a systematic review for the link of soft tissue sarcoma with exposure to pesticides. An ecological study assessing the rate of pesticide sales in 11 states of Brazil reported a higher MRR of soft tissue sarcoma in people of states with greater exposure to pesticides (de Rezende Chrisman et al. 2009). The GIS-based ecological study of Carozza and colleagues also indicated that residential exposure to pesticides is associated with 1.7 time higher incidence of soft tissue sarcoma (Carozza et al. 2008). Indoor exposure to pesticides, especially those used for yard treatments, was shown to be 4.1 times higher in people diagnosed with soft tissue sarcoma by a case–control study (Leiss and Savitz 1995). It should be taken into consideration the finding of a nested case–control study estimating an OR of about 10 for the risk of soft tissue sarcoma in association with occupational exposure to phenoxy herbicides (Kogevinas et al. 1995).

Tumors of the urinary system

Kidney cancer

A total of 12 including one ecological, one cohort, one mortality and 9 case–control studies have been collected by this systematic analysis regarding the relation between exposure to pesticides and the incidence of renal cancers. An ecological study conducted on health data of children residing in agriculturally intense areas in the USA revealed nearly tripled incidence risk of childhood renal carcinoma in association with residential exposure to pesticides (Carozza et al. 2008). Examining the records of childhood death revealed a PMR of about 1.6 due to kidney cancer in the offspring of fathers who had been occupationally exposed to pesticides (Fear et al. 1998). Furthermore, 8.9 times increment in the RR of Wilm’s tumors was noted in a cohort of children whose parents had been exposed to pesticides due to engagement in agricultural activities (Kristensen et al. 1996). Those case–control studies focusing on adults estimated ORs ranging from 1.6 to 5.7 for the risk of kidney cancers in relation to occupational exposure to pesticides, while the others reported ORs between 1.4 and 128.6 for the risk of childhood renal carcinoma including Wilm’s tumors in association with parental, paternal, or maternal exposure to pesticides (Buzio et al. 2002; Forastiere et al. 1993; Karami et al. 2008; Mellemgaard et al. 1994; Olshan et al. 1993; Sharpe et al. 1995; Tsai et al. 2006).

Bladder cancer

In regard to the association of bladder cancer with pesticide exposures, there have been two cohorts and three case–control studies. Two cohort studies published by Koutros and colleagues in 2009 and 2015 have shown that people occupationally exposed to imazethapyr herbicides were 2.4 and 3 times more prone to be diagnosed with bladder cancer as given by respective p values of 0.01 and 0.005 (Koutros et al. 2009, 2015). An OR of about 1.7 was estimated by a case–control study for the risk of bladder cancer in people who had been occupationally exposed to pesticides (Amr et al. 2015), even though another report has further highlighted such a risk in cases carrying the GSTT1 polymorphism (Matic et al. 2014). The remaining case–control study has implicated on a significantly higher blood concentration of HCH and DDT in bladder cancer cases when compared to matching controls (Sharma et al. 2013).

Tumors of the male reproductive system

Prostate cancer

Since the prevalence of prostate cancer in men is higher than other malignancies, the surveys on its association with exposure to pesticides are sufficiently high. In this review, there have been 25 epidemiological studies on the link of pesticide exposures with incidence of prostate cancer, of which 13 are case–control, 10 are cohort, one is mortality, and one is ecological. The results of ecological and mortality studies implicated on the high mortality ratio of prostate cancer as calculated MRR of 1.7 and PMR of 1.3, respectively (Cerhan et al. 1998; de Rezende Chrisman et al. 2009). There were three cohort studies which linked occupational exposure to pesticides with elevated SIRs for prostate cancer ranging from 1.2 to 1.9 (Dich and Wiklund 1998; Fleming et al. 1999; Koutros et al. 2010a), while the other seven cohort studies estimated the risk in association with specified classes of pesticides. Morrison and colleagues surveyed the prostate cancer mortality in a cohort of pesticide applicators retrospectively and found an increased RR (2.2) in relation to acres sprayed with herbicides (Morrison et al. 1993). Another cohort including workers of a triazine herbicides-manufacturing plant found the prostate cancer incidence and increased SIR of about 390 (MacLennan et al. 2002). Furthermore, a total of 13144 Vietnam War veterans were examined by a cohort study in regard to Agent Orange exposure, and the results showed that twice as many exposed men were identified with prostate cancer (Chamie et al. 2008). Aldrin, malathion, fonofos, terbufos, coumaphos, and methyl bromide are the other pesticides whose association with prostate cancer was studied in different cohorts and increased risk estimated including 1.5, 1.4, 1.6, 1.2, 1.6, and 3.5, respectively (Alavanja et al. 2003; Bonner et al. 2010; Christensen et al. 2010; Koutros et al. 2013b). Similarly, case–control studies estimated the risk of prostate cancer in association with or without specified classes of pesticides, and, respectively, 10 and 3 case–control studies were collected in this review. Elevated ORs including 1.6, 2.1, and 2.3 were reported in three separate case–control studies conducted in cases of prostate cancer and their matched controls in regard to occupational exposure to ever used pesticides (Forastiere et al. 1993; Meyer et al. 2007; Parent et al. 2009). Three separate case–control studies compared the cases of prostate cancer with matching controls and estimated ORs of 1.6 and 2.5 for the risk in association with exposure to organochlorines, and an OR of 1.6 twice for the risk in association with exposure to methyl bromide (Cockburn et al. 2011; Mills and Yang 2003; Settimi et al. 2003). Exposure to malathion, DDT, carbaryl, chlordecone, ziram, dichlone, azinphos, simazine, maneb, diazinon, and lindane was shown to be associated with higher incidence of prostate cancer as evidenced by ORs ranging from 1.5 to 2 by two case–control studies (Band et al. 2011; Multigner et al. 2010). The five remaining case–control studies evaluated the prostate cancer susceptibility against pesticide exposure in people carrying polymorphism of some variants. Elevated ORs including 3, 3.1, 3.2, 3.4, 3.7, and 4.5 have been estimated for the risk of prostate cancer in association with occupational exposure to terbufos in carriers of MPO-single nucleotide polymorphism (SNP), parathion in carriers of SNP in genes of vitamin D metabolism, fonofos in carriers of CT/TT-SNP, malathion in carriers of EHBP1-SNP, aldrin in carriers of TET2-SNP, and again fonofos in carriers of 8q24 variants, respectively (Barry et al. 2011; Karami et al. 2013; Koutros et al. 2010b, 2011, 2013a).

Testicular cancer

A cohort of licensed pesticide applicators in Florida was evaluated, and a 2.5 times higher SIR was reported for the risk of testicular cancer in relation to occupational exposure to pesticides (Fleming et al. 1999). Giannandrea and colleagues have also measured and compared the serum level of dichlorodiphenyldichloroethylene (DDE) and HCB in cases of testicular cancer with matching controls and observed a significant tripled risk of testicular cancer in association with higher serum levels of mentioned pesticides (Giannandrea et al. 2011).

Tumors of the female reproductive system

Breast cancer

Breast cancer is the most prevalent malignancy in female and has been frequently the topic of environmental health studies examining its association with pesticide exposures. In this systematic search, a total of 14 studies including 4 cohort and 10 case–control analyses have been reviewed. The Agricultural Health Study examined a cohort of 30454 farmers’ wives prospectively, and breast cancer SIR of 2.0 and 2.7 was calculated for those who had been exposed to 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) and captan, respectively (Engel et al. 2005). A cohort of 30003 spouses of pesticide applicators have also been the participants of another Agricultural Health Study whose results implicated on breast cancer RR of 1.2 among women who had personal use of organophosphorus insecticides (Lerro et al. 2015a). Niehoff and colleagues conducted a prospective Sister Study cohort and reported a breast cancer HR of 1.3 in women who had been aged 0–18 years before the ban of DDT in the USA (Niehoff et al. 2016). Furthermore, blood level of DDT was evaluated in relation to women’s survival following breast cancer in a prospective cohort study, and an HR of 2.7 was estimated for breast cancer-specific mortality in the highest tertile of blood DDT concentration (Parada et al. 2016). Five separate case–control studies published during 2000 and 2013 showed breast cancer ORs ranging from 1.4 to 2.1 in association with occupational or residential exposure to pesticides (Duell et al. 2000; El-Zaemey et al. 2013; Mills and Yang 2005; Ortega Jacome et al. 2010; Teitelbaum et al. 2007). The other case–control studies measured the blood concentration of organochlorine insecticides in breast cancer cases and their matched controls, and higher concentrations of DDT, DDE, dichlorodiphenyldichloroethane (DDD), β-HCH, and HCB in the blood were shown to be associated with breast cancer ORs of 5.3, 9.6, 1, 3.4, and 8.7, respectively (Arrebola et al. 2015; Boada et al. 2012; Charlier et al. 2003; Tang et al. 2014b). In addition to blood levels, Yang and colleagues reported that there is a positive association between adipose tissue levels of organochlorine insecticides, including DDE, β-HCH, and pentachlorothioanisole (PCTA) with incidence of breast cancer in women (Yang et al. 2015).

Ovarian cancer

Updated data on cancer incidence in the Agricultural Health Study revealed an ovarian cancer SIR of 2.4 in association with occupational exposure to pesticides in private sectors (Koutros et al. 2010a). Recently, the results of the Agricultural Health Study with a focus on organophosphorus insecticides have revealed that diazinon use was associated with 1.9 times higher RR of ovarian cancer among spouses of pesticides applicators (Lerro et al. 2015a). In this regard, there is also a case–control study reporting an increased ovarian cancer OR (2.7) in association with occupational exposure to triazine herbicides (Donna et al. 1989).

Cervical cancer

There is a cohort study conducted on licensed pesticide applicators in Florida which estimated a cervical cancer SIR of 3.7 in association with exposure to pesticides (Fleming et al. 1999).

Tumors of the head and neck

Eye cancer

A GIS-based ecological study conducted by Carozza and colleagues estimated an eye cancer OR of 2.6 in people residing in counties with high density of pesticides (Carozza et al. 2008). In a follow-up of cancer incidence among offspring of parents who had been involved in agricultural activities, a tripled eye cancer RR has been found in association with parental exposure to pesticides (Kristensen et al. 1996). Furthermore, a case–control study focusing on the childhood sporadic bilateral retinoblastoma has found 2.1 and 1.6 times higher risk in children whose fathers had been exposed to pesticides, respectively, 1 year and 10 years before conception (Abdolahi et al. 2013).

Laryngeal cancer

Bravo and colleagues have conducted a case–control study and found an increased occurrence of insecticide exposure in cases of laryngeal cancer compared with their matched controls (Bravo et al. 1990).

Lip cancer

Association of lip cancer with pesticide exposures has been investigated in an ecological, a mortality, and two cohort studies. Chrisman and colleagues evaluated ecologically the rate of pesticide sales in 11 states and estimated a lip cancer mortality ratio of 5.6 in males who had been residentially or occupationally exposed to pesticides (de Rezende Chrisman et al. 2009). Extracting the causes of death from death certificates of Lowa farmers revealed a PMR of 1.6 due to lip cancer in association with occupational exposure to pesticides (Cerhan et al. 1998). A retrospective cohort study of Swedish agricultural workers presented a decreased risk of most cancers among the study group except lip cancer, which was shown to be greater than the national average by a factor of almost 1.8 (Wiklund 1983). Furthermore, another cohort study carried out on a population engaged in sheep dipping indicated that occupational exposure to lindane increased the risk of lip cancer by 1.5 time in men and by 9 times in women (Rafnsson 2006).

Mouth cancer

A study converting the Census occupation to chemical exposures with a JEM-based approach revealed that occupational exposure to pesticides was associated with a mouth cancer SIR of about 1.8 in a cohort of Finns born between 1906 and 1945 (Tarvainen et al. 2008).

Miscellaneous

Lung cancer

The link of pesticide exposures with lung cancer incidences has been studied by 11 epidemiological studies of which 7 are cohort and 4 are case–control analyses collected in this review. Occupational exposure to pesticides has been linked to higher incidence of lung cancer by three separated case–control studies estimating ORs including 2.4 and 5.1 (Brownson et al. 1993; Luqman et al. 2014; Pesatori et al. 1994), while the results of another case–control study has implicated on a tripled risk of lung cancer in the sons whose parents had been exposed to household pesticides (Moore et al. 2005). All of cohort studies in this review have determined the incidence of lung cancer in association with specified types of pesticides, as such an elevated risk estimate of 1.7 has been found for occupational use of acetochlor, 1.4 for terbufos, 2.1 for dicamba, 2.4 and 5 for metolachlor, 2.4 and 3.2 for diazinon, 1.9 and 2.2 for chlorpyrifos, and 4.4 for pendimethalin (Alavanja et al. 2004; Beane Freeman et al. 2005; Bonner et al. 2010; Lee et al. 2004a; Lerro et al. 2015b; Rusiecki et al. 2006; Samanic et al. 2006).

Thyroid cancer

Searching the role of pesticide exposures in the incidence of thyroid cancer by this review resulted in 4 cohort studies, one of which found a SIR of 1.2 for the risk in farmers who had been occupationally exposed to any kind of pesticides, while the others reported thyroid cancer risk estimates of 1.6, 2, and 4.8 for occupational exposure to alachlor, malathion, and atrazine, respectively (Freeman et al. 2011; Lee et al. 2004b; Lerro et al. 2015a; Pukkala et al. 2009).

Skin cancer

Two separate case–control studies estimated skin cancer ORs of 2 and 2.2 in association with occupational use and indoor use of pesticides, respectively (Fortes et al. 2007; Segatto et al. 2015). Occupational exposure to specific classes of pesticides was evaluated in three cohort studies reporting elevated melanoma risk estimates, including 1.6 for acetochlor, 2.4 for maneb, 2.4 for parathion, and 1.7 and 4.1 for carbaryl (Dennis et al. 2010; Lerro et al. 2015b; Mahajan et al. 2007).

Disease-based evidence on neurotoxicity of pesticides

Alzheimer

Alzheimer disease is an increasing age-related neurodegenerative disease which has been shown to be associated with exposure to pesticides. Herein, six studies including three cohort, two case–control, and an ecological studies have been reviewed on the relation between Alzheimer and pesticide exposures (Table 2). The longitudinal and prospective analysis of exposures associated with incidence of Alzheimer diseases by the cohort studies revealed 1.4 and 2.4 times higher risk in people occupationally exposed to any pesticides, while exposure to organophosphorus and organochlorine compounds was shown to increase the risk by 1.5 times. In addition, an Alzheimer RR of about 4.3 in association with exposure to fumigants and defoliants had been previously reported by a cohort study (Baldi et al. 2003b; Hayden et al. 2010; Tyas et al. 2001). A GIS-based ecological study indicated that the prevalence of Alzheimer disease in people living in the areas having higher pesticide usage was two times higher than that of the others (Parron et al. 2011). Two separate case–control studies evaluated pesticide exposures in cases of Alzheimer disease and their matched controls, and the results of the first one indicated an OR of about 1.1 for the risk in relation to pesticides and fertilizers, while the second one showed that the blood level of DDE is positively associated with risk of Alzheimer disease evidenced by an OR of about 4.2 (McDowell et al. 1994; Richardson et al. 2014).
Table 2

Neurotoxicity of pesticides evidenced by disease

Study

Type of study

No. of samples

Exposure assessment

Exposure

Target pesticide

OR/RR/HR

(95 % CI)

p value

Alzheimer

McDowell (1994)

CC

258/535

 

Occup.

Pesticides, fertilizers

1.07 (1.18–3.99)

 

Tyas (2001)

Co

694

Questionnaire

Occup.

Fumigants, defoliants

4.35 (1.05–17.90)

 

Baldi (2003b)

Pros. Co

1507

Questionnaire

Occup.

2.39 (1.02–5.63)

 

Hayden (2010)

Pros. Co

3084

Questionnaire

Occup.

1.42 (1.06–1.91)

0.02

     

OPs

1.53 (1.05–2.23)

0.03

     

OCs

1.49 (0.99–2.24)

0.06

Parron (2011)

Ec

17,429

GIS

Env.

2.10 (1.96–2.25)

<0.001

Richardson (2014)

CC

86/79

Serum level

 

DDE

4.18 (2.54–5.82)

<0.001

Parkinson

Baldi (2003a)

CC

84/252

GIS

Gen.

2.2 (1.1–4.3)

 

Butterfield (1993)

CC

63/68

 

Env.

Insecticide

5.75

<0.001

     

Fumigants

5.25

0.046

     

Herbicides

3.22

0.033

Chan (1998)

CC

215/313

Questionnaire

Occup.

Exposed years

1.05 (1.01–1.09)

0.018

Costello (2009)

CC

368/341

GIS

Env.

Maneb, Paraquat

1.75 (1.13–2.73)

 

Dick (2007)

CC

959/1989

Questionnaire

Occup.

1.41 (1.06–1.88)

 

Dutheil (2010)

CC

101/234

Questionnaire

Occup.

OCs

3.50 (0.90–14.5)

 

Elbaz (2009)

CC

224/557

Questionnaire

Occup.

1.80 (1.1–3.1)

0.01

Firestone (2005)

CC

250/388

Questionnaire

Occup.

2.07 (0.67–6.38)

 

Fong (2007)

CC

153/155

Questionnaire

Occup.

1.69 (1.07–2.65)

 

Frigerio (2006)

CC

149/129

Questionnaire

Gen.

2.40 (1.1–5.4)

0.04

Gatto (2009)

CC

368/341

Well water use

Env.

Methomyl

Chlorpyrifos

Propargite

1.67 (1.00–2.78)

1.87 (1.05–3.31)

1.92 (1.15–3.20)

 

Gorrel 1998

CC

144/464

Questionnaire

Occup.

Herbicides

Insecticides

4.1 (1.37–12.24)

3.55 (1.75–7.18)

 

Hancock (2008)

CC

319/296

Questionnaire

Occup.

1.61 (1.13–2.29)

 

Manthripragada (2010)

CC

351/363

GIS

Gen.

Diazinon

Chlorpyrifos

2.2 (1.1–4.5)

2.6 (1.3–5.4)

 

Ritz (2009)

CC

324/334

Questionnaire

Occup.

Paraquat, Maneb

2.99 (0.88–1.02)

 

Tanner (2009)

CC

519/511

Questionnaire

Occup.

Pesticides

2,4-D

1.9 (1.12–3.21)

2.59 (1.03–6.48)

 

Tanner (2011)

CC

110/358

Questionnaire

Occup.

Rotenone

Paraquat

2.5 (1.2–3.6)

2.5 (1.4–4.7)

 

Wang (2011a)

CC

362/341

Ambient level

Occup.

Ziram, maneb, paraquat

3.09 (1.69–5.64)

 

Zorzon (2002)

CC

136/272

Questionnaire

Env.

Occup.

2.0 (1.1–3.5)

7.7 (1.4–44.1)

0.0237

0.0212

Ascherio (2006)

Pros. Co

143,325

Questionnaire

Occup.

1.7 (1.2–2.3)

0.002

Baldi (2003b)

Pros. Co

1507

Questionnaire

Occup.

5.63 (1.47–21.58)

 

Kamel (2007)

Pros. Co

55,931

Questionnaire

Occup.

2.3 (1.2–4.5)

0.009

Kamel (2014)

CC

89/336

Questionnaire

Occup.

Paraquat

Rotenone

4.2 (1.5–12)

5.8 (2.3–15)

 

Petrovitch (2002)

Pros. Co

7986

Questionnaire

Occup.

1.7 (0.8–3.7)

0.006

Richardson (2009)

CC

50/43

Serum level

 

β-HCH

4.39 (1.67–11.6)

 

McCann (1998)

CC

224/310

Questionnaire

Env.

Rural residency

1.8

<0.001

Lee (2012)

CC

357/754

GIS

Env.

Paraquat

1.36 (1.02–1.81)

 

Goldman et al. (2012)

CC

87/343

Questionnaire

Occup.

Paraquat

Paraquat (GSTT1*0)

1.5 (0.6–3.6)

11.1 (3.0–44.6)

 

Steenland (2013)

CS

400

Questionnaire

Occup.

2.57 (0.91–7.26)

 

Narayan (2013)

CC

357/807

Questionnaire

Res.

Household pesticide

OPs

Organothiophosphate

1.47 (1.13, 1.92)

1.71 (1.21, 2.41)

1.95 (1.17, 3.23)

 

Brouwer (2015)

Pros. Co

5000

JEM

Occup.

1.27 (0.86–1.88)

 

James and Hall (2015)

CS

332,971

Groundwater level

Env.

1 μg/L pesticides

1.03 (1.02–1.04)

 

Moisan (2015)

CC

133/298

Questionnaire

Occup.

2.56 (1.31–4.98)

 

Amyotrophic lateral sclerosis

Bonvicini (2010)

CC

41/82

Questionnaire

Occup.

3.6 (1.2–10.5)

 

Das (2012)

CC

110/240

Questionnaire

Occup.

Pesticides and insecticides

1.61 (1.27–1.99)

0.03

McGuire (1997)

CC

174/348

Questionnaire

Occup.

2.0 (1.1–3.5)

 

Morahan and Pamphlett (2006)

CC

179/179

Questionnaire

Overall

Occup.

Herbicides/pesticides

Herbicides/pesticides

1.57 (1.03–2.41)

5.58 (2.07–15.06)

 

Pamphlett (2012)

CC

614/778

Questionnaire

Occup.

Herbicides/pesticides

1.77 (1.30–2.39)

 

Qureshi (2006)

CC

95/106

Questionnaire

Occup.

↑ risk

0.03

Burns (2001)

Co

1517

JEM

Occup.

2,4-D

3.45 (1.1–11.11)

 

Deapen and Henderson (1986)

CC

1136

Questionnaire

Occup.

2.0 (0.8–5.4)

 

Savettieri (1991)

CC

46/92

Interview

Gen.

3.0 (0.4–20.3)

 

Gunnarsson (1992)

CC

92/372

Questionnaire

Occup.

1.1 (0.2–5.3)

 

Chancellor (1993)

CC

103/103

Questionnaire

Occup.

1.4 (0.6–3.1)

 

Weisskopf (2009)

Co

987,229

Questionnaire

Gen.

1.48 (0.82–2.67)

0.0004

Kamel (2012)

AHS (Co)

84,739

Questionnaire

Occup.

OCs

1.6 (0.8–3.5)

 

Su (2016)

CC

156/128

Blood level

Gen.

OCs, PCBs, BFRs

5.09 (1.85–13.99)

 

Beard (2016)

CC

621/958

Questionnaire

War Field

Agent Orange

2.80 (1.44–5.44)

 

Burns (2001)

Co

3/40600

Expert Judgment

Occup.

2,4,-D

3.45 (1.10–11.11)

 

Furby et al. (2010)

CC

108/122

Questionnaire

Occup.

3.04 (1.19–7.75)

 

Malek (2014)

CC

66/66

Questionnaire

Occup.

6.50 (1.78, 23.77)

 

Yu (2014)

CC

66/66

Questionnaire

Occup.

>30 years exposure

6.95 (1.23–39.1)

<0.05

MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, PMR proportional mortality ratio, SMR standard mortality ratio, MRR mortality rate ratio, SIR standard incidence ratio, ChE cholinesterase, OPs organophosphoruses, OCs organochlorines, 2,4-D 2,4-dichlorophenoxyacetic acid, β-HCH beta-hexachlorocyclohexane, DDE dichlorodiphenyldichloroethylene

Parkinson

Because of approximate similarity between the pathophysiology of Parkinson disease (PD) and toxicity of pesticides, there have been a huge body of epidemiological and experimental evidence on the role of pesticide exposures in the development of PD. Herein, the results of 33 epidemiological human study comprised of 26 case–control, 5 cohort, and two cross-sectional analyses have been extracted and reviewed (Table 2). The results of a screening test for neurodegenerative diseases conducted in a population-based sample from Costa Rica implicated on a Parkinson OR of about 2.6 in association with occupational exposure to pesticides, while the other cross-sectional analysis measuring the ground water level of some pesticides, including atrazine, simazine, alachlor, and metolachlor reported an increased risk of PD by 3 % for every 1.0 microg/L of pesticide in groundwater (James and Hall 2015; Steenland et al. 2013). All of five cohort studies included in this review prospectively analyzed the risk of PD in different sized samples of population and reported that occupational exposure to pesticides increases the risk of PD up to a range of 1.3–5.6 times (Ascherio et al. 2006; Baldi et al. 2003b; Brouwer et al. 2015; Kamel et al. 2007; Petrovitch et al. 2002). Among case–control studies which compared the cases of PD with their matched controls from the aspect of pesticide exposures, some generally evaluated the risk in relation to ever used pesticides and reported a total of eleven increased ORs ranging from 1.05 to 2.6 (Baldi et al. 2003a; Chan et al. 1998; Dick et al. 2007; Elbaz et al. 2009; Firestone et al. 2005; Fong et al. 2007; Frigerio et al. 2006; Hancock et al. 2008; McCann et al. 1998; Moisan et al. 2015; Zorzon et al. 2002), while the others whose number is also large enough calculated the risk of the disease in association with exposure to specific types of pesticides. In this regard, elevated Parkinson ORs have been reported for the main classes of pesticides, including two for insecticides (3.5 and 5.7), two for herbicides (3.2 and 4.1), and one for fumigant (5.2), though exposure to organochlorines and organophosphoruses has been shown to increase the risk of PD as given by ORs of 3.5 and 1.7, respectively (Butterfield et al. 1993; Dutheil et al. 2010; Gorell et al. 1998; Narayan et al. 2013). Specifically, environmental and occupational exposure to paraquat has been linked with the most frequently reported Parkinson ORs including 1.4, 1.5, 1.7, 2.5, 3, and 4.2 and then exposure to the maneb (1.7 and 3) and rotenone (2.5 and 5.8) (Costello et al. 2009; Kamel et al. 2014; Ritz et al. 2009; Tanner et al. 2011). Furthermore, a case–control study comparing the cases of PD with their matched controls regarding the ambient level of pesticides at workplace revealed that combined exposure to paraquat, maneb, and ziram was associated with a threefold increase in the risk of Parkinson (Wang et al. 2011a). Environmental exposure to methomyl, chlorpyrifos, and propargite has been compared between cases of PD and the matched controls by a GIS-based analysis of groundwater, and 1.7- to 1.9-fold elevated risks of Parkinson were estimated for usage of contaminated well water with mentioned pesticides (Gatto et al. 2009). Another GIS-based case–control study has shown that residential exposure to chlorpyrifos and diazinon increased the risk of Parkinson by more than two times (Manthripragada et al. 2010). Occupational exposure to the herbicide 2,4-D has been compared between the cases of PD and matched controls, and 2.6 times increased risk of PD in cases was estimated (Tanner et al. 2009). A 4.4 times elevated risk of Parkinson due to exposure to β-HCH was the finding of another case–control study indicating that β-HCH was more often detectable in the blood of PD cases than control (Richardson et al. 2009).

Amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive disease of the nervous system presented by muscle weakness for which the role of environmental risk factors specially pesticide exposures has been well studied. Herein, 18 studies including 15 case–control and 3 cohort analyses of the possible link between pesticide exposures and the incidence of ALS have been reviewed (Table 2). A cohort study prospectively evaluated the causes of mortality in relation to the exposures and found out an ALS RR of about 1.5 in people having more than 10 years of regular exposure to pesticides (Weisskopf et al. 2009). In addition, a mortality RR of 3.4 was attributed to the ALS among a cohort of male employees in a 2,4-D-manufacturing plant (Burns et al. 2001). A meta-analysis of the Agricultural Health study data taken from a cohort of 84,739 private pesticide applicators revealed that ALS was associated with occupational exposure to pyrethroid, organochlorines, herbicides, and fumigants evidenced by elevated ORs including 1.4, 1.6, 1.6, and 1.8, respectively, (Kamel et al. 2012). Ten case–control studies included in this review reported the link of pesticide exposures with elevated ALS risk estimates ranging from 1.1 to 6.9 (Bonvicini et al. 2010; Chancellor et al. 1993; Deapen and Henderson 1986; Furby et al. 2010; Gunnarsson et al. 1992; Malek et al. 2014; McGuire et al. 1997; Qureshi et al. 2006; Savettieri et al. 1991; Yu et al. 2014). Three separate studies comparing the cases of ALS with controls regarding occupational exposures, estimated higher risk of the disease relevant to the industrial use of herbicides/pesticides (1.8 and 5.6) and insecticides/pesticides (1.6) (Das et al. 2012; Morahan and Pamphlett 2006; Pamphlett 2012). A case–control study of US military veterans has shown that war field exposure to Agent Orange increased the risk of ALS given by OR of 2.8 (Beard et al. 2016). Furthermore, measuring the blood level of organochlorine pesticides in cases of ALS and their controls revealed that cumulative exposure was significantly associated with ALS evidenced giving an OR of about 5.1 (Su et al. 2016).

Disease-based evidence on pulmonotoxicity of pesticides

Asthma

The link of environmental and occupational exposures with asthma has long been discovered, and so the role of pesticide exposures in the etiology of the disease has been well studied in both children and adults. Herein, the results of 18 studies including 7 cross-sectional, 7 cohort, and 4 case–control survey on the relation of pesticide exposures with incidence of asthma have been reviewed (Table 3). Among cross-sectional analyses, two have evaluated the risk of asthma in association with occupational and para-occupational exposure to any kind of pesticides and increased risk of the disease has been found (ORs up to 4.6) (Bener et al. 1999; Salameh et al. 2003), while the other study evaluated death data and found an elevated mortality ratio (3.4) associated with asthma in people occupationally exposed to pesticides (Beard et al. 2003). Three cross-sectional studies have measured the serum levels of dioxin, DDE, and cholinesterase enzyme in the participants and reported higher incidence of asthma in exposure to Agent Orange, DDE, and anticholinesterase insecticides, including organophosphoruses and carbamates as evidenced by ORs of 1.6, 3.7, and 1.9, respectively. Albeit, the reported risk of DDE was estimated in combination with polychlorinated biphenyls (PCBs) and HCB in children exposed after birth (Kang et al. 2006; Karmaus et al. 2001; Ndlovu et al. 2014). Further, an asthma prevalence OR of 1.8 in association with exposure to carbamate insecticides has been previously estimated by a questionnaire-based cross-sectional study (Senthilselvan et al. 1992).
Table 3

Pulmonotoxicity of pesticides evidenced by disease

Study

Type of study

No. of samples

Exposure assessment

Exposure

Target pesticide

OR/RR/HR

(95 % CI)

p value

Asthma

Senthilselvan (1992)

CS

1939

 

Occup.

Carbamate

1.8 (1.1–3.1)

0.02

Kang (2006)

CS

2927

Serum Dioxin

Occup.

Agent Orange

1.62 (1.28–2.05)

>0.05

Bener (1999)

CS

196

 

Occup.

↑ risk

<0.008

Salameh (2006)

CC

262/110

Interview

Occup.

4.98 (1.07–23.28)

0.02

Beard (2003)

CS

3983

Death Data

Occup.

3.45 (1.39–7.10)

 

Hoppin (2008)

Co

25,814

Questionnaire

Occup.

1.46 (1.14–1.87)

 

Hoppin (2009)

Co

19,704

Questionnaire

Occup.

Coumaphos

2.34 (1.49–3.70)

 
     

Heptachlor

2.01 (1.30–3.11)

 
     

Parathion

2.05 (1.21–3.46)

 
     

Mix (CCl4/CS2)

2.15 (1.23–3.76)

 
     

Ethylene dibromide

2.07 (1.02–4.20)

 

Sunyer (2005)

Co

468

Cord serum

Mat.

DDE

2.63 (1.19–4.96)

 

Sunyer (2006)

Co

462

Cord serum

Mat.

DDE

1.18 (1.01–1.39)

 

Karmaus et al. (2001)

CS

343

Blood level

Mat.

DDE

3.71 (1.10–12.56)

 

Tagiyeva (2010)

Co

13,971

Questionnaire

Par. job

Biocides/fungicides

1.47 (1.14–1.88)

 

Salam (2004)

CC

279/412

Interview

Env.

Pesticides

2.39 (1.17–4.89)

 
     

Herbicides

4.58 (1.58–5.56)

 

Salameh (2003)

CS

3291

Questionnaire

Para-Occup.

4.61 (2.06–10.29)

 

Meng (2016a, b)

CC

60/60

Indoor dust

Res.

DDE

1.82 (1.00–3.32)

0.04

Meng (2016a, b)

CC

620/218

Pooled serum

 

DDE

1.02 (1.01–1.03)

0.0004

     

α-HCH

1.06 (1.02–1.10)

0.001

Ndlovu et al. (2014)

CS

211

Blood ChE

Occup.

ChE inhibitor

1.93 (1.09–3.44)

 

Yi et al. (2014)

Ret. Co

111,726

GIS

Occup.

Agent Orange

1.04 (1.01–1.08)

0.015

Hansen (2014b)

Co

965

Mat. serum

Mat.

HCB

1.92 (1.15, 3.21)

 

Exacerbated asthma

Henneberger (2014)

Co

926

Questionnaire

Occup.

Pendimethalin

2.1 (1.1–4.1)

 
     

Aldicarb

10.2 (1.9–55)

 

Chronic bronchitis

Hoppin (2007)

Co

20,908

Questionnaire

Occup.

Heptachlor

1.50 (1.19–1.89)

 

Salameh (2006)

CC

262/110

Interview

Occup.

15.92 (3.50–72.41)

<0.0001

Tual et al. (2013)

Co

14,441

Questionnaire

Occup.

1.63

<0.05

Valcin (2007)

Co

21,541 women

Questionnaire

Occup.

Dichlorvos

1.63 (1.01, 2.61)

 
     

DDT

1.67 (1.13, 2.47)

 
     

Cyanazine

1.88 (1.00, 3.54)

 
     

Paraquat

1.91 (1.02, 3.55)

 
     

Methyl bromide

1.82 (1.02, 3.24)

 

Yi et al. (2014)

Ret. Co

111,726

GIS

Occup.

Agent Orange

1.05 (1.02–1.08)

0.015

Wheeze

Hoppin (2002)

Co

20,468

Questionnaire

Occup.

Parathion

1.5 (1.0–2.2)

 
     

Atrazine

1.5 (1.2–1.9)

 

Hoppin (2006a, b)

Co

89,000

Questionnaire

Occup.

Chlorpyrifos

1.48 (1.0–2.2)

0.02

Hoppin (2006a, b)

Co

2255

Questionnaire

Occup.

Chlorimuron-ethyl

1.62 (1.25, 2.10)

 

Salameh (2003)

CS

3291

Questionnaire

Res.

2.73 (1.85–4.05)

 

Xu (2012)

CS

14,065

Questionnaire

Res.

Household use

1.39 (1.08–1.78)

 

Gascon (2014)

Co

405

Mat. serum

Mat.

HCB

1.58 (1.04–2.41)

 
     

DDE

1.35 (1.07–1.71)

 

Lower respiratory tract infections (LRTIs)

Sunyer (2010)

Co

520

Mat. serum

Mat.

DDE

2.40 (1.19–4.83)

 

Gascon (2012)

Co

1455

Mat. serum

Mat.

DDE

1.33 (1.08–1.62)

 

Gascon (2014)

Co

405

Mat. serum

Mat.

HCB

1.89 (1.10–3.25)

 

MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, ChE cholinesterase, OPs organophosphoruses, HCB hexachlorobenzene, α-HCH alpha-hexachlorocyclohexane, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene

Two separate case–control studies reported asthma ORs of 2.4 and 5 in association with, respectively, environmental and occupational exposure to any kind of pesticides, while 4.6 for environmental exposure to herbicides (Salam et al. 2004; Salameh et al. 2006). Recently, Meng et al. measured and compared the concentration of pesticides in indoor dust and blood samples taken from cases of asthma and controls and published two separate case–control studies reporting higher incidence of asthma in association with exposure to DDE (ORs 1.02 and 1.8) and alpha-hexachlorocyclohexane (α-HCH) (OR of 1.06) (Meng et al. 2016a, b).

Hoppin and colleagues have analyzed data from the Agricultural Health Study and once reported an asthma OR of about 1.5 in female farmers exposed to any pesticide, and once again estimated asthma ORs including 2.3, 2, 2.05, 2.15, and 2.1 in male farmers exposed to coumaphos, heptachlor, parathion, mixed CCl4/CS2, and ethylendibromide, respectively (Hoppin et al. 2008, 2009). In addition, the Agricultural Health Study on a cohort of pesticide applicators with active asthma showed that the symptoms were exacerbated due to occupational exposure to pendimethalin (OR: 2.1) and aldicarb (OR: 10.2) (Henneberger et al. 2014). A cohort of Korean Vietnam veterans have been retrospectively evaluated to determine diseases’ prevalence by a GIS-based model assessment of exposure, and an asthma OR of 1.04 was estimated for exposure to Agent Orange (Yi et al. 2014). The link of childhood asthma in association with parental occupation has been evaluated by a birth cohort study, and higher incidence of asthma was found in children whose parents occupationally exposed to biocides/fungicides as given by an OR of 1.5 (Tagiyeva et al. 2010). Measuring the cord serum concentration of DDE taken from two cohorts of offspring and their follow-up by Sunyer and colleagues indicated that prenatal exposure to DDE increased the incidence of childhood asthma as the ORs were estimated to be 1.2 and 2.6 (Sunyer et al. 2006; Sunyer et al. 2005). Moreover, the results of a prospective cohort study measuring the maternal serum concentration of organochlorines with 20-year follow-up revealed that prenatal exposure to HCB was associated with an asthma HR of 1.9 in the offspring (Hansen et al. 2014b).

Chronic bronchitis

Regarding the role of pesticide exposures in chronic bronchitis, the results of a case–control plus 4 cohort studies have been reviewed (Table 3). The comparison of occupational exposure to pesticides between cases and controls resulted in a significantly elevated OR of 15.9 for chronic bronchitis (Salameh et al. 2006). Besides, findings from the French AGRICAN cohort study has shown that pesticide poisoning and pesticide exposures among potato farmers were significantly associated with risk of chronic bronchitis (OR 1.6) (Tual et al. 2013). The other three cohort studies determined the risk of chronic bronchitis in association with specified types of pesticides, as a chronic bronchitis OR of 1.5 was estimated for heptachlor usage by pesticide applicators involved in the Agricultural Health Study (Hoppin et al. 2007). Such a risk of chronic bronchitis has also been found by the Agricultural Health Study on non-smoking farm women who had been exposed to dichlorvos, DDT, methyl bromide, cyanazine, and paraquat with respective ORs including 1.6, 1.7, 1.8, 1.9, and 1.9 (Valcin et al. 2007). Further, exposure of a cohort of Korean Vietnam veterans to Agent Orange was shown to be significantly associated with increased risk of chronic bronchitis with estimated OR of 1.05 (Yi et al. 2014).

Wheeze

Wheeze as a typical symptom of the most respiratory disorders has also been the focus of environmental health studies assessing its risk in relation to pesticide exposures. In this regard, the results of two cross-sectional plus 4 cohort studies have been presented in this review (Table 3). Two questionnaire-based cross-sectional analyses have indicated that residential exposure to pesticides increased the risk of wheeze in children with ORs of 1.4 and 2.7 (Salameh et al. 2003; Xu et al. 2012). Hoppin and colleagues made three separated analyses on data from the Agricultural Health Study and reported that occupational exposure to parathion, atrazine, chlorpyrifos, and chlorimuron-ethyl were associated with increased incidence of wheeze with ORs ranging from 1.5 to 1.6 (Hoppin et al. 2002, 2006a, b). Measurement of maternal serum concentration of persistent organic pollutants (POPs) in a cohort study indicated that incidence of wheeze in the offspring prenatally exposed to DDE and HCB was increased with respective ORs including 1.3 and 1.8 (Gascon et al. 2014).

Low respiratory tract infections (LRTIs)

LRTIs in relation to pesticide exposures have been studied in three separate cohorts of children whose mothers’ serum concentration of organochlorines was measured (Table 3), and the results implicated on elevated risk of LRTIs in association with prenatal exposure to DDE (ORs 1.3 and 2.4) and HCB (OR 1.9) (Gascon et al. 2012, 2014; Sunyer et al. 2010).

Disease-based evidence on reproductive toxicity of pesticides

Infertility

There are various types of reproductive disorders in both males and females which may be resulted in infertility or not. Infertility has been defined as the inability to reproduce naturally and has been well studied in relation to the environmental risk factors such as pesticides. The search for the link of human infertility with pesticide exposures has brought totally 9 relevant studies, including two cross-sectional, five case–control, and two cohort analyses in this review (Table 4). One of the cross-sectional studies has measured the level of organochlorines in cord blood of the couples enrolled in a French birth cohort (PELAGIE) and concluded that the time-to-pregnancy increased in association with higher serum concentrations of DDE (Chevrier et al. 2013). The other study is questionnaire based and reported early abortion ORs of 1.4 and 1.5 in the women exposed to phenoxy and atrazine herbicides before conception, while such an exposure to glyphosate and thiocarbamates in women resulted in late abortion ORs of 1.7 and 1.8 (Arbuckle et al. 2001).
Table 4

Reproductive toxicity of pesticides evidenced by disease

Study

Type of study

No. of samples

Exposure assessment

Exposure

Target pesticide

OR/RR/HR

(95 % CI)

p value

Found risk

Infertility

Bastos (2013)

CC

15/21

Blood level

DDE

69 %

0.001

Infertility♀

Arbuckle (2001)

CS

2110

Questionnaire

Mat.

2,4-D & 2,4,5-T

1.5 (1.1–2.1)

 

Early abortion

     

Triazines

1.4 (1.0–2.0)

 

Early abortion

     

Glyphosate

1.7 (1.0–2.9)

 

Late abortion

     

Thiocarbamate

1.8 (1.1–3.0)

 

Late abortion

Pant (2007)

CC

50/50

Semen level

HCH, DDT

<0.05

Infertility

      

<0.05

↓ sperm count

↓ sperm motility

Greenlee (2003)

CC

322/322

Interview

Occup.

Herbicides

27 (1.9–380)

  
     

Fungicides

3.3 (0.8–13)

  

Upson (2013)

CC

248/538

Serum level

 

HCH

Mirex

1.3 (0.8–2.4)

1.5 (1.0–2.2)

 

Endometriosis

Sanin (2009)

Co

2592

GIS

Res.

Glyphosate

0.15 (0.12–0.18)

 

↑ TTP

Smith (1997)

CC

281/216

Questionnaire

Occup.

 

3.02 (1.10–8.29)

  

Cohn (2003)

Co

289

Serum level

Mat.

DDT

32 %

 

↑ TTP

Chevrier (2013)

CS

3421

Cord blood

 

DDE

 

↑ TTP

Semen disquality

Swan (2003)

CC

50/36

Urine sample

Arachlor

30 (4.3–210)

 

↓ sperm count,

↓ Sperm motility,

↓ sperm morphology

     

Diazinon

16.7 (2.8–98)

  
     

Atrazine

11.3 (1.3–98.9)

  

Aneck-Hahn (2007)

CS

311

Blood level

DDE

−0.02

0.001

↓ Sperm motility

      

−0.0003

0.02

↓ Ejaculate volume

      

1.001

0.03

Oligozoospermia

      

1.001

0.02

Asthenozoospermia

Celik-Ozenci (2012)

CS

40

Blood level

Occup.

Abamectin

 

↓ Sperm motility

↓ Sperm maturity

De Fleurian (2009)

CC

314/88

Questionnaire

Occup.

 

3.6 (0.8–15.8)

 

Oligospermia, asthenospermia, or teratospermia

Perry (2007)

CS

17

Urine level

Occup.

Pyrethroids, OPs

 

↓ sperm count

Perry (2011)

CC

94/95

Urine level

 

OPs

1.30 (1.02–1.65)

 

↓ sperm count

↓ Sperm motility

Ji et al (2011)

CS

240

Blood level

 

Pyrethroids

−0.27

0.27

<0.001

<0.001

↓ sperm count

↑ sperm DNA damage

Recio-Vega (2008)

Co

52

Urine level

Occup.

OPs

 

↓ sperm count

Khan (2010)

CC

50/50

Blood level

HCH

 

↓ sperm count

Yq deletion

Meeker JD et al. (2008)

CS

207

Blood level

Pyrethroids

 

↓ sperm count

↓ sperm motility

↑ sperm DNA damage

Messaros (2009)

CS

336

Blood level

DDE, DDT

 

↓ sperm count

↓ sperm motility

↑ sperm morphology

Miranda-Contreras (2013)

CS

100

Blood level

(ChE activity)

OPs, carbamates

 

↑ sperm DNA damage

↓ sperm parameters

↑ FSH, LH

Xia et al. (2008)

CC

376

Urine level

Pyrethroids

2.04 (1.02–4.09)

0.027

↓ sperm count

Yucra (2008)

CS

62

Urine level

Occup.

OPs

 

↓ semen volume

↑ semen pH

Birth defects

Gemmill (2013)

Co

442

GIS

Mat.

Methyl bromide

−113.1 g

−0.85 cm

−0.33 cm

 

↓ birth weight

↓birth length

Head circumference

Sathyanarayana (2010)

Co

2246

Questionnaire

Mat.

Carbaryl

−82 (−132, −31)

 

↓ birth weight

Burdorf (2011)

Co

8880

JEM

Mat.

2.42 (1.10–5.34)

 

↓ birth weight

Brender (2010)

CC

184/225

Interview

Mat.

2 (1.2–3.1)

 

Neural tube defects

Brucker-Davis (2008)

CC

56/69

Colostrum

Mat.

DDE

  

Cryptorchidism

Chevrier C ET AL. 2011

Co

579

Urine level

Mat.

Atrazine

1.5 (1.0–2.2)

1.7 (1.0–2.7)

 

↓ fetal growth

Head circumference

de Siqueira (2010)

Ec

26 states

Pesticide use

Par.

0.045

0.004

↓ birth weight

congenital abnormality

Dugas (2010)

CC

471/490

Interview

Mat.

Insecticides

1.8 (1.06–3.11)

 

Hypospadias

Perera (2003)

CS

263

Plasma level

Mat.

Chlorpyrifos

0.01

0.003

↓ birth weight

↓ birth length

Ren (2011)

CC

80/50

Placental level

Mat.

DDT

α-HCH

5.19 (1.70–15.82)

3.89 (1.26–11.97

 

Neural tube defects

Rocheleau (2009)

MA

9 studies

JEM

Mat.

1.36 (1.04–1.77)

 

Hypospadias

    

Pat.

1.19 (1.00–1.41)

  

Whyatt (2004)

CS

314

Cord blood

 

Chlorpyrifos/diazinon

<0.05

↓ birth weight

↓ birth length

Waller (2010)

CC

805/3616

Surface water

Mat.

Atrazine

1.6 (1.10–2.34)

0.014

Gastroschisis

Michalakis (2014)

CS

29

Hair sample

Par.

DDT

HCH

DMP

0.009

0.037

0.071

Hypospadias

Kielb et al. (2014)

CC

871/2857

JEM

Mat.

1.88 (1.16–3.05)

 

Gastroschisis

Makelarski (2014)

CC

502/2950

JEM

Mat.

Insecticides + Herbicides

2.1 (1.0–4.1)

 

Spina Bifida

Jørgensen (2014)

Co

600000

JEM

Mat.

1.31 (1.21–1.53)

 

Cryptorchidism

Carmichael (2013)

CC

690/2195

GIS

Mat.

Aldicarb

Dimethoate

Phorate

2.69 (1.04–6.96)

2.45 (1.36–4.39)

2.76 (1.19-6.44)

 

Hypospadias

Changed sex ratio and maturation and hormones

Tiido (2005)

CS

149

Blood level

Occup.

DDE

1.6 (0.8–2.5)

<0.001

Yq fraction

Tiido (2006)

CS

547

Blood level

Res.

DDE

<0.001

Yq fraction

Den Hond (2011)

CS

1679

Blood level

HCBDDE

 

Pubertal staging (men)

Meeker (2009)

CS

161

Blood level

 

Pyrethroids

<0.05

<0.03

<0.09

↑ FSH

↓ inhibin B

↓ testosterone

Meeker (2006)

CS

268

Blood level

 

Chlorpyrifos

Carbaryl

Naphthalene

 

↓ testosterone, FAI and LH

♂: risk found in male, ♀: risk found in female, MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, ChE cholinesterase, OPs organophosphoruses, DMP dimethyl phosphate, 2,4-D 2,4-dichlorophenoxyacetic acid, 2,4,5-T 2,4,5-trichlorophenoxyacetic acid, HCB hexachlorobenzene, α-HCH alpha-hexachlorocyclohexane, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene, FAI free androgen index, FSH follicle-stimulating hormone, LH luteinizing hormone

There have been two questionnaire-based case–control studies, one of which calculated an infertility OR of about 3 in females occupationally exposed to any kind of pesticides, while increased ORs of 3.3 and 27 were estimated by the other study for female infertility in association with occupational exposure to fungicides and herbicides, respectively (Greenlee et al. 2003; Smith et al. 1997). Two case–control studies published in 2013 compared the blood level of organochlorines between cases of infertile women with controls and cases of endometriosis with controls and reported significantly higher incidence of infertility in association with DDE exposure, while elevated endometriosis ORs of 1.3 and 1.5 were estimated for respective exposure to HCH and mirex (Bastos et al. 2013; Upson et al. 2013). Cases of infertile men were also compared with controls regarding semen concentration of organochlorines, and significantly elevated risk of infertility as well as lower sperm count and motility has been found in association with higher levels of HCH and DDT in the semen (Pant et al. 2007).

Furthermore, there is an infertility-targeted cohort study measuring the maternal serum concentration of DDT and DDE, which has shown increased time-to-pregnancy in daughters of women exposed to DDT (Cohn et al. 2003). Increased time-to-pregnancy in women living in the glyphosate condensed areas has also been reported by a cohort study applying a GIS approach for assessing the exposure to the pesticide in Colombian regions (Sanin et al. 2009).

Low quality of semen

Some characteristics of the semen are critical determinants of male fertility, and lowered quality of the semen has been studied in association with exposure to pesticides (Mehrpour et al. 2014). Herein, a total of 14 studies including 8 cross-sectional, 5 case–control, and one cohort analyses on the role of pesticide exposure in the lowered quality of the semen have been reviewed (Table 4). Blood concentration of organochlorines was measured in two cross-sectional and one case–control studies, and their results implicated on the lowered quality of the semen characterized by decreased sperm count and motility, decreased volume of ejaculation, oligozoospermia, asthenozoospermia, and Yq deletion in association with exposure to DDE, DDT, and HCH for different values (Aneck-Hahn et al. 2007; Khan et al. 2010; Messaros et al. 2009). The incidence of oligozoospermia, asthenozoospermia, and teratospermia in association with occupational exposure to any used pesticides has also been reported by a questionnaire-based case–control study (De Fleurian et al. 2009). In association with organophosphorus and pyrethroid insecticides, different studies have measured their blood or urine concentration in human and linked their exposure to lowered sperm count and motility, increased sperm DNA damage, and disrupted volume and pH of the semen (Meeker et al. 2009; Perry et al. 2007, 2011; Recio-Vega et al. 2008; Yucra et al. 2008). In addition to DNA damage and low quality of the sperm, increased levels of the follicle-stimulating hormone (FSH) and luteinizing hormone (LH) have been reported by a cross-sectional study assessing the exposure via the enzymatic activity of acetylcholinesterase and butyrylcholinesterase in the blood (Miranda-Contreras et al. 2013). Swan and colleagues compared cases having low sperm count, motility, and morphology with controls regarding biomarkers of pesticide exposure and found that arachlor, diazinon, and atrazine were more often detectable in the urine of cases than that of controls with respective ORs including 30, 16.7, and 11.3 (Swan et al. 2003). Lowered sperm motility and maturity have also been found in people occupationally exposed to abamectin (Celik-Ozenci et al. 2012).

Birth defects

Birth defects, also known as congenital disorders or anomalies, have different types, e.g., low birth weight and length, cryptorchidism, hypospadias, neural tube defect, spina bifida, gastroschisis, and head circumference, and a substance inducing birth defects is called teratogen. There has been remarkable evidence on the teratogenicity of pesticides in human of which 18 relevant studies including 3 cross-sectional, 8 case–control, 5 cohort, and one ecological have been presented in this review (Table 4). Association of low birth weight with maternal exposure to pesticides, regardless of the type, with an OR of 2.4 has been reported by a JEM-based cohort study (Burdorf et al. 2011). Further, a questionnaire-based analysis of a cohort in the Agricultural Health Study indicated that maternal exposure to carbaryl lowered the birth weight as given by an OR of −82 g (Sathyanarayana et al. 2010). Such a risk plus lower birth length have been linked to maternal exposure to chlorpyrifos and diazinon by two separate cross-sectional studies (Perera et al. 2003; Whyatt et al. 2004). In addition to lower birth weight and length, head circumference has been reported by two cohort studies examining the offspring whose mothers were exposed to atrazine and methyl bromide (Chevrier et al. 2013; Gemmill et al. 2013). In this regard, an ecological study conducted in 26 states of Brazil revealed that there are significant correlations between pesticide use in the agriculture and low birth weight as well as congenital abnormality (de Siqueira et al. 2010).

The risk of neural tube defect has been shown to be doubled due to maternal exposure to pesticides by a questionnaire-based case–control study, while another study comparing the cases with controls regarding the placental level of organochlorines reported that maternal exposure to DDT and α-HCH is associated with neural tube defect with respective ORs 5.2 and 3.9 (Brender et al. 2010; Ren et al. 2011). Moreover, an almost doubled risk of spina bifida has been estimated for maternal exposure to insecticides and herbicides by a JEM-based case–control study (Makelarski et al. 2014).

A cryptorchidism HR of 1.3 has been estimated by a JEM-based cohort study among the sons of mothers engaged in horticulture and farming (Jorgensen et al. 2014). Further, comparing the cases with controls regarding maternal exposure to organochlorines indicated that DDE had been more often detectable in the colostrum of mothers whose son suffered from cryptorchidism (Brucker-Davis et al. 2008).

Elevated hypospadias OR (1.8) in association with maternal exposure to insecticides was estimated by a questionnaire-based case–control study (Dugas et al. 2010). In addition, the results of a GIS-based case–control study showed that maternal exposure to aldicarb, dimethoate, and phorate increased the risk of hypospadias with respective ORs of 2.7, 2.4, and 2.8 (Carmichael et al. 2013). Michalakis and colleagues have evaluated parental exposure to organochlorines and organophosphates by measuring their level in the hair samples and concluded that chronic exposure of parents to DDT, HCH, and organophosphoruses was associated with higher incidence of hypospadias in the offspring (Michalakis et al. 2014). There has also been a meta-analysis of 9 studies whose results gave elevated hypospadias ORs of 1.4 and 1.2 in the boys whose, respectively, mothers and fathers had been occupied in the jobs dealing with pesticides (Rocheleau et al. 2009).

Gastroschisis, another type of birth defect, has also been linked to prenatal exposure to pesticides by a JEM-based case–control study estimating an OR of about 1.9 (Jorgensen et al. 2014). Further, Waller and colleagues reported that the incidence of gastroschisis increased in the offspring whose mothers were residing in the areas with high concentration of atrazine in the surface water (Waller et al. 2010).

Changed sex ratio, maturation, and hormones

There is sporadic evidence on pesticide-induced sexual dysfunction, some of which relevant to the reproduction have been presented in this review (Table 4). Tiido and colleagues conducted two separate cross-sectional studies examining pesticide exposure via their blood level measurement and concluded that exposure to DDE was significantly associated with the Y-chromosome fraction in human sperm (Tiido et al. 2005, 2006). Higher concentration of DDE and HCB in the blood samples was shown to link with disruption of pubertal staging in men (Den Hond et al. 2011). Regarding sexual hormone alteration, two separate cross-sectional studies carried out by Meeker and colleagues reported an increased level of FSH accompanying a decreased level of inhibin B, testosterone, LH, and free androgen index (FAI) in association with exposure to pyrethroids, chlorpyrifos, carbaryl, and naphthalene (Meeker et al. 2006, 2009).

Disease-based evidence on developmental toxicity of pesticides

Attention deficit hyperactivity disorder (ADHD)

ADHD is a neurodevelopmental disorder manifested by behavioral problems such as attention difficulty, hyperactivity, troubled relationship, and lowered self-esteem. There has been recently ongoing evidence on the role of environmental risk factors such as pesticide exposure in the incidence of ADHD, as such 11 epidemiological studies published during the last decade have been reviewed here. They include 4 cross-sectional, 6 cohort, and a case–control analyses on the link of ADHD with exposure to pesticides (Table 5). Elevated ORs of 1.5 and 5.1 for ADHD have been linked with organophosphoruses by two cross-sectional studies examining the exposure via urine and blood samples (Bouchard et al. 2010; Suarez-Lopez et al. 2013). Comparing the cases of ADHD with control regarding exposure to organophosphoruses indicated that the biomarkers of organophosphoruses were 2–3 times more detectable in the urine sample of the cases than that of controls (Yu et al. 2016). Furthermore, a cohort study measuring the biomarkers of organophosphoruses in the urine samples of the mothers revealed an OR of 1.3 for the risk of ADHD in association with maternal exposure to organophosphoruses (Marks et al. 2010). Another cohort study measuring the urine concentration of organophosphoruses indicated that maternal exposure to chlorpyrifos increased the risk of ADHD in boys and attention deficit (AD) in girls with respective ORs 5.5 and 5.8 (Fortenberry et al. 2014). The link between prenatal exposure to chlorpyrifos and higher incidence of ADHD with a risk estimate of 6.5 was resulted from a cohort study examining the exposure via blood level measurement of the pesticides (Rauh et al. 2006).
Table 5

Developmental toxicity of pesticides evidenced by diseases

Study

Type of study

Sample no.

Exposure assessment

Exposure

Associated target

OR/RR/HR

(95 % CI)

p value

Found disorder related to

ADHD

Wagner-Schuman (2015)

CS

687

Urine level

 

Pyrethroid

2.42 (1.06–5.57)

  

Bouchard (2010)

CS

1139

Urine level

 

OPs

1.55 (1.14–2.10)

  

Yu (2016)

CC

97/110

Urine level

 

OPs

Two-threefold

<0.05

 

Marks (2010)

Co

323

Urine level

Mat.

OPs

1.3 (0.4–2.1)

  

Rauh (2006)

Co

254

Plasma

Mat.

Chlorpyrifos

6.50 (1.09–38.69)

  

Suarez-Lopez (2013)

CS

307

Blood ChE

OPs (boys)

5.14 (0.84–31.48)

 

Neurodevelopment

Sioen (2013)

Co

270

Cord blood

Mat.

DDE

9.95 (1.37–72.35)♀

0.023

Behavioral

Sagiv (2010)

Co

607

Cord blood

Mat.

DDE

1.8

  

Sagiv (2008)

Co

788

Cord blood

Mat.

DDE

↑ risk

0.03

Irritability

Fortenberry (2014)

Co

187

Urine level

Mat.

Chlorpyrifos

5.55 (−0.19, 11.3)♂

5.81 (−0.75, 12.4)♀

0.06

0.08

ADHD

AD

Xu (2011)

CS

2546

Urine level

 

Trichlorophenol

1.77 (1.18–2.66)

0.006

 

Autism

Eskenazi (2007)

Co

531

Urine level

Mat.

OPs

–3.5 (–6.6–0.5)

 

Mental

Braun (2014)

Co

175

Blood, urine

Mat.

Chlordane

4.1 (0.8–7.3)

  

Cheslack-Postava (2013)

CC

75/75

Serum

Mat.

DDE

1.79 (0.52–6.21)

0.36

 

Roberts (2007)

CC

465/6975

GIS

Mat.

OCs

6.1 (2.4–15.3)

  

Keil (2014)

CC

407/262

Interview

Mat.

Imidacloprid

1.3 (0.78–2.2)

  

Shelton (2014)

CC

486/316

Questionnaire

Mat. (3rd)

Mat. (2nd)

Mat. (3rd)

OPs

Chlorpyrifos

Pyrethroids

2.0 (1.1–3.6)

3.3 (1.5–7.4)

1.87 (1.02–3.43)

  

Developmental Delay

Andersen (2015)

Co

133

Interview

Mat.

  

Neurobehavioral

Bosma (2000)

Co

830

Questionnaire

Occup.

2.02 (1.27–3.20)

 

Cognitive

Ribas-Fitó (2003)

Co

92

Cord blood

Mat.

p,p′-DDE

−3.5

−4.01

 

Mental

Psychomotor scale

Viel et al. (2015)

Co

428

Urine level

Pyrethroids

 

<0.01

Verbal

Memory

Zhang (2014)

Co

249

Urine level

Mat.

OPs

−1.78 (−2.12, −1.45

 

Neurobehavioral

Bouchard et al. (2011)

Co

329

Urine level

Mat.

OPs (DAP)

−5.6 (−9.0, −2.2)

<0.01

IQ

Engel (2011)

Co

404

Urine level

Mat.

OPs

  

Cognitive

Engel (2007)

Co

311

Urine level

Mat.

Malathion

2.4 (1.55–3.24)

 

Abnormal reflexes

Young (2005)

Co

381

Urine level

Mat.

OPs (DAP)

4.9 (1.5–16.1)

 

Abnormal reflexes

Horton (2012)

Co

725

Cord blood

Mat.

Chlorpyrifos

−1.71 (−3.75 to 0.32)

 

Working memory

Rauh (2011)

Co

265

Cord blood

Mat.

Chlorpyrifos

1.4

2.8

0.064

0.001

Full-scale IQ

Working memory

Harari (2010)

CS

87

Interview

Mat.

−7.1 (−12.5, −1.6)

5.32 (1.03–27.62)

6.62 (1.02–42.93)

<0.05

<0.05

<0.05

Motor speed

Motor coordination

Visual memory

Torres-Sánchez (2013)

Co

203

Serum

Mat.

DDE

−1.37 (−2.56 to 0.19

–0.80 (−1.52 to 0.08)

<0.05

<0.05

Cognitive index

Memory

Dallaire (2012)

Co

153

Cord blood

Mat.

Chlordecone

−0.19 (−0.35,−0.03)

1.25 (1.07–1.45)

0.02

0.002

Cognitive

Motor

   

Breast milk

Mat.

Chlordecone

−0.14 (−0.29, −0.01)

0.07

Cognitive

♂: risk found in male, ♀: risk found in female, MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, ChE cholinesterase, OPs organophosphoruses, DDE dichlorodiphenyldichloroethylene, DAP dialkyl phosphate, ADHD attention deficit hyperactivity disorder, AD attention deficit, IQ intelligence quotient

In association with pyrethroids, there is a cross-sectional study measuring their biomarkers in the urine and calculated an ADHD risk estimate of 2.4 in relation to exposure to pyrethroids (Wagner-Schuman et al. 2015).

Three separate cohort studies evaluated the cord blood concentration of organochlorines and found a higher incidence of ADHD complications such as irritability and behavioral problems in association with prenatal exposure to DDE (Sagiv et al. 2008, 2010; Sioen et al. 2013). In addition, higher concentration of trichlorophenol has been detected in the urine samples taken from children having ADHD for which an OR of 1.8 has been estimated by a cross-sectional study (Xu et al. 2011).

Autism

Autism has also been recently studied in relation to pesticide exposures for which 6 relevant studies, including two cohorts and 4 case–control analyses, all implicating on maternal exposures, have been brought in this review (Table 5). A GIS-based case–control study reported an autism OR of 6.1 in association with organochlorines, as such a risk with estimated ORs including 1.8 and 4.1 has been, respectively, reported for DDE and chlordane by two blood-measuring studies, one of which was case–control and the other one was cohort (Braun et al. 2014; Cheslack-Postava et al. 2013; Roberts et al. 2007).

Urine sample analysis for biomarkers of organophosphoruses was performed in a cohort of young Mexican–American children, and the results implicated on decreased mental development indices (beta −3.5 points per tenfold increase in prenatal biomarkers of organophosphoruses) at 24 months of age (Eskenazi et al. 2007). In addition, the Childhood Autism Risks from Genetics and Environment (CHARGE) study compared the cases with control regarding residential proximity to agricultural pesticides during pregnancy and reported that exposure to organophosphoruses and pyrethroids during the third trimester and chlorpyrifos during the second trimester of pregnancy was associated with increased risk of autism (ORs ranging from 1.9 to 3.3) in the offspring (Shelton et al. 2014). An autism OR of 1.3 in association with maternal exposure to imidacloprid has also been found by a questionnaire-based case–control study (Keil et al. 2014).

Developmental delay

Developmental impairments, manifested by different features such as cognitive, memory, verbal, visual, behavioral, and motor dysfunctions, have been evaluated in association with pesticide exposures by 14 epidemiological studies, including 13 cohorts as well as one cross-sectional analyses brought in this review (Table 5). The results of a questionnaire-based cross-sectional study implicated on impaired motor speed, motor coordination, and visual memory in association with maternal exposure to any kind of pesticides (Harari et al. 2010). Maternal and occupational exposures to ever used pesticide have also been shown to link with, respectively, neurobehavioral deficits and cognitive dysfunction by two separate cohort studies (Andersen et al. 2015; Bosma et al. 2000). All of the remaining 10 cohort studies have evaluated the risk of developmental impairments in association with maternal exposure to specified classes of pesticides measured in biological samples. Urine sample analysis was performed for detecting biomarkers of organophosphoruses as well as malathion itself by five cohort studies whose results implicated on reduced neurobehavioral development, cognitive development, and intelligence quotient (IQ) as well as increased abnormal reflexes in children having maternal exposure to the mentioned pesticides (Bouchard et al. 2010; Engel et al. 2007, 2011; Young et al. 2005; Zhang et al. 2014). Furthermore, maternal exposure to chlorpyrifos, measured by cord blood analysis in two separate cohort studies, was shown to be associated with lower working memory and full-scale IQ in childhood (Horton et al. 2012; Rauh et al. 2011).

Regarding developmental impairments in relation to organochlorines, there are two cohort studies on maternal exposure to DDE which has been linked with reduced mental and psychomotor scale, general cognitive index, and memory function (Ribas-Fito et al. 2003; Torres-Sanchez et al. 2013). There is another cohort study analyzing cord blood and breast milk samples and reported both decreased cognitive and motor development due to prenatal and decreased cognitive development due to postnatal exposure to chlordecone (Dallaire et al. 2012).

Disease-based evidence on metabolic toxicity of pesticides

Diabetes

Diabetes has become epidemic because of its prevalent risk factors, including Western diet and physical inactivity in the modern life, though the environmental risk factors, particularly pesticide exposures, have also been linked to its development (Bahadar et al. 2014; Mostafalou and Abdollahi 2012c). Herein, a total of 28 studies including 19 cross-sectional, three case–control, five cohort, and an ecological analyses of the link between human exposure to various pesticides and incidence of diabetes have been reviewed (Table 6). Except one questionnaire-based cross-sectional study estimating gestational diabetes OR of 2.2 in association with occupational exposure to any kind of pesticides (Saldana et al. 2007), the other studies reported the risk of diabetes in relation to specified classes of pesticides. The cross-sectional association of the serum concentration of organochlorines with diabetes and insulin resistance was investigated using data resulted from the National Health and Examination Survey 1999–2002, and adjusted ORs for diabetes and insulin resistance were estimated as 37.7 and 7.5, respectively (Lee et al. 2006, 2007a). Recently, a meta-analysis of 22 studies on the link of exposure to pesticides with incidence of human diabetes resulted in a risk estimate of about 1.7 for organochlorines (Evangelou et al. 2016). Among organochlorines specifically associated with diabetes, the highest number of evidence belongs to the DDE given 11 elevated diabetes risk estimates ranging from 1.3 to 12.7 in 7 cross-sectional, 2 case–control, and 2 cohort studies examining the exposure via blood sample analysis (Airaksinen et al. 2011; Codru et al. 2007; Cox et al. 2007; Lee et al. 2011a; Philibert et al. 2009; Rignell-Hydbom et al. 2007, 2009; Son et al. 2010; Turyk et al. 2009a, b; Ukropec et al. 2010). Furthermore, there has been a published meta-analysis of 18 studies evaluating the incidence of diabetes in relation to DDE, and a significant elevated risk estimate of 1.3 has been analyzed (Tang et al. 2014a). The other organochlorines for which elevated diabetes risk estimates have been found include DDT with 5 reported ORs ranging from 1.9 to 10.6, HCB with five reported ORs ranging from 2.8 to 6.8, trans-nonachlor with 5 reported ORs ranging from 2.2 to 8.1, oxychlordane with four reported ORs ranging from 2 to 6, heptachlor with three reported ORs ranging from 1.7 to 3.1, β-HCH with two reported ORs including 2.1 and 8.2, mirex with two reported ORs including 2.1 and 3.7, aldrin with an OR of 1.5, dieldrin with an OR of 2, chlordane with an OR of 1.6, and alachlor with an OR of 1.3 (Airaksinen et al. 2011; Codru et al. 2007; Cox et al. 2007; Everett et al. 2007; Gasull et al. 2012; Kim et al. 2014; Lee et al. 2010, 2011a; Montgomery et al. 2008; Patel et al. 2010; Son et al. 2010; Starling et al. 2014; Ukropec et al. 2010; Wu et al. 2013). Moreover, a cross-sectional association of occupational exposure to pentachlorophenol with hyperglycemia manifested by fasting blood glucose higher than 100 mg/dl has been found in retired workers of a pentachlorophenol-manufacturing plant (Chang et al. 2012).
Table 6

Metabolic toxicity of pesticides evidenced by diseases

Study

Type of study

No. of samples

Exposure assessment

Exposure

Target pesticide

OR/RR/HR

(95 % CI)

p value

Found risk

Diabetes

Lee (2006)

CS

2016

Serum level

OCs

37.7 (7.8–182)

<0.001

 

Kim (2003)

CS

1378

Military record

Agent Orange

2.69

  

Yi et al. (2014)

Ec

111726

GIS

Occup.

Agent Orange

1.04 (1.01–1.07)

  

Kim (2014)

CS

50

VAT/SAT

DDT

9.0 (1.3–62.9)

0.02

 

Son (2010)

CC

40/40

Serum

Oxychlordane

Trans-nonachlor

Heptachlor epoxide

Hexachlorobenzene

β-HCH

Mirex

DDE

DDT

6.0 (1.3–517.4)

8.1 (1.2–53.5)

3.1 (0.8–12.1)

6.1 (1.0–36.6)

8.2 (1.3–53.4)

3.7 (0.9–15.8)

12.7 (1.9–83.7)

10.6 (1.3–84.9)

<0.01

0.02

0.05

0.03

0.02

0.08

<0.01

0.02

 

Wang (2011b)

CS

3080

Questionnaire

Occup.

Pyrethroids

1.48 (1.23–1.77)

<0.001

 

Chang (2012)

CS

1167

Retired workers

Occup.

Pentachlorophenol

7.22 (4.04–12.90)

 

↑FBG

Malekirad (2013)

CS

374

Questionnaire

Occup.

OPs

<0.001

↑FBG

Hansen (2014a)

CS

208

Questionnaire

Occup.

Pyrethroids

18.5 (5.5–62.5)

 

↑HbA1c

Starling (2014)

Co

13,637

Interview

Occup.

Fonofos

Phorate

Parathion

Dieldrin

2,4,5-T/2,4,5-TP

1.56 (1.11–2.19)

1.57 (1.14–2.16)

1.61 (1.05–2.46)

1.99 (1.12–3.54)

1.59 (1.00–2.51)

  

Patel (2010)

CS

503–3318

EWAS

Heptachlor epoxide

1.7

<0.001

 

Lee (2010)

Nested CC

90/90

Serum level

trans-Nonachlor Oxychlordane

Mirex

4.8 (1.7–13.7)

2.0 (0.8–5.0)

2.1 (0.8–5.5)

0.06

 

Montgomery (2008)

Co

33,457

Questionnaire

Occup.

(>100 days)

Aldrin

Chlordane

Heptachlor

Trichlorfon

Alachlor

Cyanazine

1.51 (0.88–2.58)

1.63 (0.93–2.86)

1.94 (1.02–3.69)

2.47 (1.10–5.56)

1.31 (1.11–1.55)

1.38 (1.10–1.72)

0.08

0.05

0.02

0.02

0.001

0.004

 

Lee (2007a)

CS

749

Serum level

OCs

7.5 (2.3–23.9)

<0.01

↑HOMA-IR

Saldana (2007)

CS

11,273

Questionnaire

Occup.

2.2 (1.5–3.3)

 

Gestational

Airaksinen (2011)

CS

1988

Serum level

Oxychlordane

trans-Nonachlor

DDE

2.08 (1.18–3.69)

2.24 (1.25–4.03)

1.75 (0.96–3.19)

 

T2DM

Philibert (2009)

CS

101

Serum level

DDE

6.1 (1.4–27.3)

  

Ukropec (2010)

CS

2047

Serum level

DDE

DDT

1.86 (1.17–2.95)

2.48 (1.77–3.48)

  

Gasull (2012)

CS

886

Serum level

HCB

2.8

  

Rignell-Hydbom (2007)

CS

543

Serum level

DDE

1.3 (1.1–1.6)

  

Everett (2007)

CS

1830

Serum level

DDT

2.69 (1.35–5.36)

  

Cox (2007)

CS

1303

Serum level

Oxychlordane

trans-Nonachlor

DDE

DDT

β-HCH

3.1 (1.1–9.1)

2.9 (1.3–6.4)

2.6 (1.2–5.8)

1.9 (1.0–3.7)

2.1 (1.0–4.3)

  

Codru (2007)

CS

352

Serum level

DDE

HCB

6.2 (1.8–21.9)

6.8 (2.3–20.3)

  

Turyk (2009a)

CS

503

Serum level

DDE

3.6

0.009

 

Lee (2011a, b)

Co

725

Serum level

trans-Nonachlor, DDE, HCB

3.4 (1.0–11.7)

0.03

 

Turyk (2009b)

Co

471

Serum level

p,p′-DDE

7.1 (1.6–31.9)

  

Wu (2013)

Co

1095

Serum level

HCB

3.1 (1.3–7.7)

  

(Rignell-Hydbom 2009)

Nested CC

39/39

Serum level

DDE

5.5 (1.2–25.0)

 

T2DM

Tang (2014a, b)

MA

18 studies

DDE

1.33 (1.15–1.54)

0.0007

 

Evangelou (2016)

MA

22 studies

OCs

1.68 (1.37, 2.07)

8 × 10−7

 

Obesity

Bachelet (2011)

CS

1055

Serum level

DDE

1.39 (1.13–1.70)

 

↑BMI

Jakszyn (2009)

CS

953

Serum level

DDE, β-HCH, HCB

  

↑BMI

Lee (2006)

CS

2016

Serum level

OCs

 

<0.01

↑BMI

Lee (2012)

CS

970

Serum level

DDE

DDE

HCB

trans-Nonachlor

1.7 (0.9–3.1)♀

2.6 (1.1–5.7)♂

3.4 (1.6–7.5)♂

2.5 (1.1–5.6)♂

<0.05

<0.01

<0.01

0.04

 

Dirinck (2011)

CS

145

Serum level

β-HCH

 

<0.001

<0.05

↑BMI

↑HOMA-IR

Ibarluzea (2011)

CS

1259

Serum level

HCB, β-HCH

 

<0.001

 

Lee (2011a, b)

Co

5115

Serum level

DDE, DDT

 

0.05

 

Glynn (2003)

CS

205

Serum level

DDE

β-HCH

HCB

3.9 (1.3–6.6)

3.8 (2.1–5.6)

1.1 (0.5–2.3)

  

♂: risk found in male, ♀: risk found in female, MA meta-analysis, CC case–control, CS cross-sectional, Co cohort, Ec ecological, Mr mortality, Ret. retrospective, Pros. prospective, Occup. occupational, Env. environmental, Mat. maternal, Pat. paternal, Par. parental, Res. residential, Gen. general, GIS geographic information system, JEM job exposure matrix, OR odd ratio, RR relative risk, HR hazard ratio, EWAS environment-wide association study, OPs organophosphoruses, OCs organochlorines, 2,4-D 2,4-dichlorophenoxyacetic acid, 2,4,5-T 2,4,5-trichlorophenoxyacetic acid, HCB hexachlorobenzene, β-HCH beta-hexachlorocyclohexane, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene, VAT visceral adipose tissue, SAT subcutaneous adipose tissue, FBG fasting blood glucose, HbA1c Hemoglobin A1c, HOMA-IR homeostatic model assessment—insulin resistance, T2DM type 2 diabetes mellitus, BMI body mass index

Regarding organophosphoruses, there is a questionnaire-based cross-sectional study reporting that occupational exposure to organophosphorus insecticides is significantly associated with hyperglycemia (Malekirad et al. 2013). Parathion, phorate, fonofos, and trichlorfon are organophosphorus insecticides for which, respectively, elevated risk estimates including 1.6, 1.6, 1.6, and 2.6 have been calculated by two separate questionnaire-based cohort studies (Montgomery et al. 2008; Starling et al. 2014).

Occupational exposure to pyrethroids has also been evaluated by two questionnaire-based cross-sectional studies, one of which reported significantly elevated diabetes OR of 1.5, while the other estimated an OR of 18.5 in association with a 5.6 % increase in HbA1c (Hansen et al. 2014a; Wang et al. 2011b).

A cohort study conducted by Montgomery and colleagues indicated that occupational exposure to the herbicide cyanazine is significantly associated with increased risk of diabetes given by an OR of about 1.4 (Montgomery et al. 2008). Occupational exposure to the phenoxy herbicides has also been linked with elevated incidence of diabetes with an estimated HR of 1.6 by a questionnaire-based cohort study (Starling et al. 2014). Furthermore, association of diabetes with exposure to Agent Orange was revealed by a cross-sectional and an ecological study estimating respective ORs of 2.7 and 1.04 among Korean Vietnam veterans (Kim et al. 2003; Yi et al. 2014).

Obesity

Obesity, a condition involving excessive body fat, may not be categorized alone as a disease, but increases the risk of other serious health problems, and recent environmental health studies have shown that obesity may have other risk factors than excess calorie intake and physical inactivity. Exposure to pesticides especially those categorized as persistent organic pollutants has been linked to increased incidence of obesity by epidemiological studies, some of which including 7 cross-sectional and a cohort analyses have been reviewed in this study (Table 6). All of these studies have evaluated exposure to different organochlorine via blood sample analysis of participants, and higher risk of obesity, manifested by increased body mass index (BMI), has been linked with DDE, DDT, HCB, β-HCH, trans-nonachlor, and oxychlordane exposure (Bachelet et al. 2011; Dirinck et al. 2011; Glynn et al. 2003; Ibarluzea et al. 2011; Jakszyn et al. 2009; Lee et al. 2006, 2011b, 2012).

Discussion and conclusion

Our systematic review of 43 human diseases divided into six broad groups of toxicities in association with exposure to pesticides shows that recorded evidence belongs to the, in order from the highest to the lowest, carcinogenicity, neurotoxicity, reproductive toxicity, metabolic toxicity, pulmonotoxicity, and developmental toxicity of pesticides (Fig. 2). Further, carcinogenicity is considered as the most reported toxicity studied in relation to each class of pesticides, including insecticides, herbicides, fungicides, and fumigants (Fig. 3).
Fig. 2

Schematic diagram showing the weight of evidence on the toxicities of pesticides. ND not determined

Fig. 3

Schematic charts showing the percent of toxicities attributed to each category of pesticides. ND not determined

The link of cancer incidence with human exposure to pesticides has been presented based on 28 cites of cancers divided into nine body organ systems among which the most studied associations are related to the malignancies of the hematopoietic system notably leukemia and lymphoma. Brain tumors, prostate cancer, breast cancer, colorectal cancer, pancreatic cancer, and lung cancer have then the most prevalent evidence in association with exposure to pesticides. Among studies focusing on the link of cancers with specified class of pesticides, insecticides have been located in the first place, followed by herbicides, fungicides, and fumigants (Table 7). It should be noted that insecticides and herbicides are generally considered as the most used pesticides which may explain the differences in the rate of their association with cancer incidences (Mostafalou et al. 2013). In the same way, the differences in the prevalence of cancers can exemplify the different degrees of correlation between pesticide exposures and incidence of each site of cancers. Nevertheless, the body of evidence on this link is so huge that the role of pesticides in cancer development cannot be doubted. In addition to epidemiological evidences, such a confirmation can also be derived from experimental studies investigating the mechanisms by which carcinogenicity of pesticides is mediated.
Table 7

Association of cancer incidence with different classes of pesticides

Cancers of

Association with

Any pesticide (no.)

Targeted class of pesticides (no.)

Chemical class of pesticides (no.)

Single pesticides

Nervous system

19

Insecticides (1)

Herbicides (1)

Fungicides (1)

OPs (1)

Carbamates (1)

Chlorpyrifos, bufenacarb, paraquat, coumaphos, metribuzin

Digestive system

19

Insecticides (1)

Herbicides (2)

Fungicides (1)

OCs (1)

Atrazine, 2,4-D, chlordane, trifluralin, methyl bromide

Aldicarb, dicamba, imazethapyrc, chlorpyrifos, S-ethyl-N,N-dipropyl, thiocarbamate, trifluralin, acetochlor, HCB, DDT, arsenicals, EPTC, pendimethalin, acetochlor

Hematopoietic system

30

Insecticides (4)

Herbicides (5)

Fungicides (2)

Fumigants (1)

OPs (2)

Carbamates (2)

OCs (1)

Pyrethroids (1)

Phenoxy (3)

Crotoxyphos, dichlorvos, famphur, methoxychlor, terbufos, diazinon, Agent Orange, chlorpyrifos, dichlorprop, malathion, diazinon, terbufos, coumaphos, fonofos, carbaryl, lindane, DDT, dieldrin, chlordane, toxaphene, oxychlordane, cis-nonachlor, β-HCH, pentachlorophenol, atrazine, glyphosate, 2,4-D, captan, carbaryl

Bone and soft tissues

7

Phenoxyacetic acid (1)

Metolachlor

Urinary system

12

 

Imazethapyr, HCH, DDT

Male reproductive

9

Herbicides (1)

OCs (2)

Triazines (1)

Agent Orange, aldrin, malathion (2), fonofos (2), terbufos (2), coumaphos, methyl bromide (3), DDT, carbaryl, chlordecone, ziram, dichlone, azinphos, simazine, maneb, diazinon, parathion, DDE, HCB

Female reproductive

7

OPs (1)

Triazines (1)

2,4,5-T, captan, DDT (3), DDE (2), DDD, β-HCH (2), HCB, PCTA, diazinon

Head & neck

7

Insecticides (1)

Lindane

Lung cancer

4

Acetochlor, terbufos, dicamba, metolachlor, diazinon, chlorpyrifos, pendimethalin

Thyroid cancer

1

Alachlor, malathion, atrazine

Skin cancer

2

Acetochlor, maneb, parathion, carbaryl

OPs organophosphoruses, OCs organochlorines, 2,4-D 2,4-dichlorophenoxyacetic acid, 2,4,5-T 2,4,5-trichlorophenoxyacetic acid, EPTC S-ethyl-N,N-dipropylthiocarbamate, HCB hexachlorobenzene, HCH hexachlorocyclohexane, PCTA pentachlorothioanisole, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene, DDD dichlorodiphenyldichloroethane

As known, heritable changes in the genes controlling cell cycle, via genetic or epigenetic mechanisms, are responsible for cancer initiation by chemical carcinogens. During the past half century, the progress of molecular biology techniques has made it possible to largely investigate carcinogenicity of widely used chemicals, particularly pesticides. Various pathways leading to genetic or epigenetic alterations of the cell have been explored regarding pesticides tested ex vivo, in vitro, in vivo, and in human. Since genetic damages at the level of both DNA and chromosomes are considered as likely mechanisms of carcinogenicity, the huge body of evidence on genotoxicity of pesticides brought a global concern on carcinogenesis of these chemicals on which human life has become so dependent (Mostafalou and Abdollahi 2012b; Shadnia et al. 2005). In addition to genetic toxicity, epigenetic alterations, including the methylation and acetylation of DNA and its accompanying proteins, histon, have been shown to be induced by some classes of pesticides specially those categorized as endocrine disruptors (Maqbool et al. 2016).

Neurotoxicity has been ordered as the second ranked toxicity of pesticides according to the associations brought in this review, which have been derived from evidence related to the link of pesticides with just three neurodegenerative diseases including Alzheimer, Parkinson, and ALS (Table 8). In comparison with the other toxicities, this can be indicative of a high susceptibility to the neurotoxicity of pesticides, though the incidence of age-related neurodegenerative diseases including Alzheimer and Parkinson itself has been increased, somewhat, due to elevated life expectancy of human in today’s world. It should be noted that the primary mechanism of toxicity for the main groups of pesticides, particularly insecticides such as organochlorines, organophosphoruses, and carbamates, is through targeting components of the nervous system (Abdollahi and Karami-Mohajeri 2012; Karami-Mohajeri et al. 2014). However, evidence on the neurotoxicity of pesticides specifically brought in this review shows that the risk of insecticides is somehow similar to that of herbicides among which the most frequently reported evidences are related to the link of paraquat and Parkinson disease. Perhaps, such inspirations to search the link of paraquat with Parkinson by environmental health scientists originate from the use of this herbicide as a drug to induce Parkinson disease in experimental investigating models. In fact, paraquat acts through overproduction of reactive oxygen species which is held in common with toxicity of many other pesticides, and this can give a clue to trace the role of such pesticides in Parkinson disease.
Table 8

Association of non-cancerous human toxicities with different classes of pesticides

Disease

Association with

Any pesticide (no.)

Targeted class of pesticides (no.)

Chemical class of pesticides (no.)

Single pesticides

Alzheimer

3

Herbicides (1)

Fumigants (1)

OPs (1)

OCs (1)

DDE

Parkinson

17

Insecticides (2)

Herbicides (2)

Fungicides (1)

OPs (1)

OCs (1)

Atrazine, simazine, alachlor, metolachlor, paraquat (7), maneb (3), rotenone (2), ziram, methomyl, chlorpyrifos (2), propargite, diazinon, 2,4-D, β-HCH

ALS

11

Insecticides (1)

Herbicides (2)

Fumigants (1)

OCs (2)

Pyrethroids (1)

2,4-D, Agent Orange

Asthma

6

Herbicides (1)

Fumigants (1)

OPs (1)

Carbamates (2)

Agent Orange (2), DDE (2), coumaphos, heptachlor, parathion, CCL4/CS2, ethylendibromide, pendimethalin, aldicarb, HCB

Chronic bronchitis

2

Heptachlor, dichlorvos, DDT, methyl bromide, cyanazine, paraquat, Agent Orange

Wheeze

2

Parathion, atrazine, chlorpyrifos, chlorimuron-ethyl, DDE, HCB

LRTIs

 

DDE (2), HCB

Infertility

1

Herbicides (1)

Fumigants (1)

Phenoxyacetic acid (1)

DDE (3), atrazine, glyphosate (2), thiocarbamates, HCH (2), mirex, DDT (2)

Low quality of semen

1

OPs (5)

Carbamates (1)

Pyrethroids (2)

DDT, DDE, HCH, arachlor, diazinon, atrazine, abamectin

Birth defects

6

Insecticides (2)

Herbicides (1)

OPs (1)

Carbaryl, chlorpyrifos, diazinon, atrazine (2), methyl bromide, DDT (2), HCH (2), DDE, aldicarb, dimethoate, phorate,

Changed sex functions

Pyrethroids (1)

DDE (2), HCB, chlorpyrifos, carbaryl, naphthalene

ADHD

OPs (5)

Pyrethroids (1)

Chlorpyrifos, DDE (3), trichlorophenol

Autism

OCs (1)

OPs (2)

Pyrethroids (1)

DDE, chlordane, chlorpyrifos, imidacloprid

Developmental delay

3

OPs (1)

Malathion, chlorpyrifos, DDE (2), chlordecone

Diabetes

1

OCs (3)

OPs (1)

Pyrethroids (1)

Phenoxyacetic acid (1)

DDE (12), DDT (5), HCB (5), trans-nonachlor (5), oxychlordane (4), heptachlor (3), β-HCH (2), mirex (2), aldrin, dieldrin, chlordane, alachlor, pentachlorophenol, parathion, phorate, fonofos, trichlorfon, cyanazine, Agent Orange (2)

Obesity

DDE, DDT, HCB, β-HCH, trans-nonachlor, oxychlordane

The number of associations is brought in the parentheses

OPs organophosphoruses, OCs organochlorines, 2,4-D 2,4-dichlorophenoxyacetic acid, 2,4,5-T 2,4,5-trichlorophenoxyacetic acid, HCB hexachlorobenzene, β-HCH beta-hexachlorocyclohexane, DDT dichlorodiphenyltrichloroethane, DDE dichlorodiphenyldichloroethylene, DDD dichlorodiphenyldichloroethane

Reproductive and metabolic toxicities have been ordered as the next prevalent toxicities of pesticides in both of which insecticides have adopted the most associations. In these toxicities, the highest share is allocated to the organochlorine insecticides whose physicochemical properties such as high lipid solubility and crossing biological membranes made environmental health scientist much suspicious to their disrupting effects on endocrine and reproductive systems (Table 8). In addition, their dioxin-like biological effect on the nuclear receptors, particularly aryl hydrocarbon receptors, which are involved in the metabolic pathways, has provided enough stimulation to search the role of organochlorine insecticides in the metabolism at cellular or the whole organism level. Although most of the organochlorine insecticides have been widely banned, their ability to persist in the environment for a long period of time made environmentalists to continue their research on the health problems associated with human exposure. For example, lots of evidence on the metabolic disrupting effects of persistent organochlorine insecticides within the context of insulin resistance such as diabetes and obesity have been gathered during the past two decades in which there was no extensive use of these chemicals formally (Karami-Mohajeri and Abdollahi 2011). These metabolic effects of organochlorine insecticides have been attributed to their ability to easily cross through biological membranes and accumulate in adipose tissues which can lead to the inflammation in insulin-responsive tissues (Mostafalou 2016). Furthermore, there is lots of experimental evidence on the role of organophosphorus insecticides in disrupted metabolism of glucose in both insulin-secreting and insulin-responsive tissues which have been implicated in prediabetic effects of this chemical class of pesticides (Jamshidi et al. 2009; Mostafalou et al. 2012b; Nili-Ahmadabadi et al. 2013; Pakzad et al. 2013; Rahimi and Abdollahi 2007; Teimouri et al. 2006; Pournourmohammadi et al. 2005).

Polmunotoxicity exhibited by diseases such as asthma and chronic bronchitis in association with occupational and environmental exposures has a long history of evidence, and pesticide exposure in this case had a similar pattern. But the association of pesticide exposures with childhood respiratory problems such as asthma and low respiratory tract infections has been recently much considered in regard to maternal or parental exposure to pesticides.

In this context, it should be noted that the link of pesticide exposures with developmental toxicity manifested by ADHD, autism, and developmental delays has been recently evidenced in the population studies concerning maternal or paternal exposure to pesticides in children. Although the lifetime of such an issue is almost short, a remarkable amount of studies have been conducted on the role of parental exposure to pesticides in developmental deficits presented in children. In this regard, most of the associations have been attributed to insecticides particularly organophosphoruses which have been widely used during the last few decades. The proven neural and oxidative stress-induced toxicities of organophosphoruses (Abdollahi et al. 2004a; Akhgari et al. 2003; Bayrami et al. 2012; Ranjbar et al. 2002) have inspired toxicologist to investigate the role of parental exposures in developmental and neuro-developmental disorders such as ADHD and autism, which have recently become prevalent in children, and positive associations have been traced for such risks.

Taken together, going through the mechanistic evidence on the toxicity of pesticides in association with human health disorders clears some common mechanisms, including oxidative stress, mitochondrial dysfunction, inflammatory responses, immune dysregulation, and endocrine disruption (Abdollahi et al. 2004b; Karami-Mohajeri and Abdollahi 2013; Mokarizadeh et al. 2015). In this way, induction of oxidative stress has been much highlighted in the studies focusing on the protective role of antioxidants such as cysteine and selenium against toxic effects of pesticides so that antioxidant therapy has been proposed and investigated for management of pesticide poisoning in human (Fakhri-Bafghi et al. 2016; Mostafalou et al. 2012a; Shadnia et al. 2011). Unveiling the link of oxidative stress with aging and age-related diseases, and inflammation with obesity and metabolic disorders is instances for ongoing exploration on the role of theses mechanisms in rising human diseases (Abdollahi et al. 2014). Given that these mechanisms and the others are gradually scrutinized in the pathology of newly focused diseases, it would be important that future studies pursue the current state of the science on the toxicity of pesticides with systematic approaches coordinated with new discoveries in the modality of human diseases.

Notes

Acknowledgments

This invited paper is the outcome of an in-house financially non-supported study. The authors wish to thank Iran National Science Foundation (INSF).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest.

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