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. Author manuscript; available in PMC: 2022 Aug 1.
Published in final edited form as: Environ Res. 2021 May 11;199:111276. doi: 10.1016/j.envres.2021.111276

Pesticide Use and Kidney Function Among Farmers in the Biomarkers of Exposure and Effect in Agriculture Study

Joseph J Shearer 1, Dale P Sandler 2, Gabriella Andreotti 1, Kazunori Murata 3, Srishti Shrestha 2, Christine G Parks 2, Danping Liu 1, Michael C Alavanja 1, Ola Landgren 4,5, Laura E Beane Freeman 1, Jonathan N Hofmann 1
PMCID: PMC8489787  NIHMSID: NIHMS1703039  PMID: 33989625

Abstract

BACKGROUND

Pesticides have been reported to be associated with malignant and non-malignant kidney disease. Few studies have examined the relationship between individual pesticides and kidney dysfunction.

OBJECTIVE

We evaluated the associations of pesticide use with measured kidney function among male pesticide applicators in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study, a subcohort in the Agricultural Health Study.

METHODS

Serum creatinine was measured in 1,545 BEEA participants and estimated glomerular filtration rate (eGFR) was calculated with the chronic kidney disease epidemiology collaboration (CKD-EPI) equation. Using reported information on lifetime use of 41 pesticides, multivariable linear and logistic regression was used to examine associations with eGFR modeled continuously and with CKD (eGFR <60 mL/min/1.73 m2), respectively. Models were adjusted for possible confounding factors related to kidney function and correlated pesticides.

RESULTS

Lower eGFR was observed among pesticide applicators who ever used the herbicides pendimethalin (−3.7%, 95% confidence interval (CI): −5.8%, −1.5%), atrazine (−3.7%, 95% CI: −6.9%, −0.4%), and dicamba (−2.8%, 95% CI: −5.3%, −0.2%) compared with never users of each pesticide. Ever use of pendimethalin (odds ratio (OR)=1.6, 95% CI: 1.1, 2.2) and atrazine (OR=1.8, 95% CI: 1.0, 3.0) was also associated with elevated odds of CKD, with an exposure-response association between intensity-weighted lifetime days of pendimethalin use and CKD among active farmers (N=1,302; ptrend=0.04). Atrazine use within the last year was associated with lower eGFR and elevated odds of CKD when compared with never users, and we observed exposure-response associations with intensity-weighted lifetime days among recent users. Use of several other pesticides was associated with higher eGFR.

DISCUSSION

These results suggest that two widely used herbicides, pendimethalin and atrazine, may be associated with altered kidney function among pesticide applicators. Our findings for these herbicides are consistent with observed associations with end-stage renal disease in the Agricultural Health Study.

Introduction

Chronic kidney disease (CKD) is a progressive disorder that affects over 30 million adults in the US (CDC 2017) and millions more worldwide (Jha et al. 2013; Valdivia-Rivera et al. 2018). CKD can lead to the development of end-stage renal disease (Coresh et al. 2014) and has been associated with risk of renal cell carcinoma (RCC, the most common form of kidney cancer) (Lowrance et al. 2014), as well as a range of other adverse health outcomes such as increased infections and cardiovascular disease (CDC, 2020). Beyond established risk factors for CKD (e.g., diabetes, hypertension), certain pesticides have been hypothesized to contribute to CKD development (Kataria et al. 2015; Soderland et al. 2010).

In the Agricultural Health Study (AHS), a large prospective cohort of licensed pesticide applicators (97% male) and their spouses (99% female) in Iowa and North Carolina (Alavanja et al. 1996), several specific pesticides have been associated with end-stage renal disease (Lebov et al. 2015; Lebov et al. 2016) and, more recently, with RCC (Andreotti et al. 2020). However, only a fraction of individuals with reduced kidney function progress to end-stage disease or RCC, and other factors may contribute to that progression, limiting the inferences that can be drawn. Furthermore, previous epidemiologic studies examining kidney function in relation to occupational pesticide use (Garcia-Trabanino et al. 2015; Jayasumana et al. 2015; Orantes et al. 2011; Sanoff et al. 2010) or environmental exposure to pesticides (Ghosh et al. 2017; Siddarth et al. 2014; Siddharth et al. 2012) have had limited information on specific pesticides or factors affecting levels of exposure). Despite the experimental animal evidence suggesting certain pesticides may be associated with kidney dysfunction (Hamdi et al. 2019; Liu et al. 2014; Tripathi and Srivastav 2010; Uyanikgil et al. 2009), and the observed associations between certain pesticides and malignant and non-malignant kidney disease in the AHS, it remains unclear whether exposure to specific pesticides may contribute to early-stage alterations in kidney function that may ultimately lead to clinically manifest kidney damage.

To address this gap in the literature, we examined associations between use of specific pesticides and altered kidney function in a large population of male pesticide applicators in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study, a molecular epidemiologic subcohort within the AHS.

Methods

Study population.

Male pesticide applicators ≥50 years of age residing in Iowa and North Carolina (N=1,681) were enrolled in BEEA between 2010 and 2017, as described (Hofmann et al. 2015). Eligible participants had completed the enrollment AHS questionnaire (1993–1997) and two follow-up interviews (1999–2003 and 2005–2010). Written informed consent was collected from each participant prior to BEEA enrollment. Institutional Review Board approval of the BEEA protocol was obtained from the National Cancer Institute and other participating institutions. Of the 1,660 BEEA participants with available sera selected for a previous investigation (Hofmann et al. 2021), there were 1,545 who had residual serum volume with no evidence of lipemia or hemolysis; we evaluated kidney function based on serum creatinine measurements in these remaining samples.

Exposure assessment.

Lifetime history of use of 50 pesticides was obtained from questionnaires administered at AHS enrollment and follow-up, as well as from an interview at the time of enrollment in BEEA. Based on these data, we characterized pesticide exposures using several different metrics. First, we assessed lifetime pesticide use (ever/never) from the AHS and BEEA questionnaires, limiting our analyses to 41 pesticides with ≥20 exposed cases of CKD (i.e., 18 herbicides, 19 insecticides, 2 fungicides, and 2 fumigants). We then assessed quartiles of cumulative intensity-weighted lifetime days (IWLDs) of use for each pesticide based on an algorithm developed specifically for the AHS (Coble et al. 2011). Briefly, using information from each questionnaire/interview, IWLDs were computed by incorporating information on frequency of use (e.g., average days of use per year and years of use) and multiplying that by an intensity-weighting factor that considered application method, mixing of pesticides, repairing pesticide application equipment, and use of personal protective equipment. For each participant, pesticide-specific IWLDs from the AHS and BEEA questionnaires were combined to estimate total cumulative IWLDs for each pesticide. Participants who indicated use of a specific pesticide but for whom we did not have more detailed information about frequency and intensity of exposure were excluded from analyses utilizing IWLDs. Finally, we examined the timing of pesticide use by categorizing individuals as never users (no reported use throughout AHS or BEEA), former users (reported use from AHS questionnaires but not at BEEA enrollment), and recent users (reported use in the last 12 months prior to BEEA interview/phlebotomy).

Kidney function assessment.

At BEEA enrollment, serum was collected from each study participant by a trained phlebotomist, and samples were shipped for aliquoting and storage at −80°C; creatinine has been reported to be stable after long-term sample storage at this temperature (Elliot et al. 2008). More details regarding sample collection and processing in the BEEA study have been described elsewhere (Hofmann et al. 2015). Banked sera were retrieved from the biorepository and sent to the Protein Laboratory at Memorial Sloan Kettering Cancer Center, where serum creatinine levels were measured using an Abbott Architect Chemistry c8000 analyzer. The coefficient of variation for blinded duplicate quality control samples (N=58) of serum creatinine was 3.7%. To assess kidney function, we calculated the estimated glomerular filtration rate (eGFR) for each participant using the CKD-EPI creatinine equation (Levey et al. 2009), which combines measured serum creatinine levels with information on age, gender, and race. Using the calculated eGFR values, we also created a dichotomous outcome variable defining participants with an eGFR <60 mL/min/1.73 m2 as having CKD, consistent with published clinical cutoffs (KDIGO 2013). Supplemental analyses were conducted further stratifying participants with CKD into those with GFR category G3a (eGFR 45 to <60 mL/min/1.73 m2) and GFR category G3b or higher (eGFR <45 mL/min/1.73 m2).

Statistical analysis.

For our main analyses, associations between individual pesticide use (ever/never) and kidney function were evaluated by both natural log-transformed eGFR (continuous) and CKD status (yes/no). For pesticides that were shown to be associated with both altered eGFR and CKD status, we performed further analyses based on quartiles of IWLDs, and we also evaluated temporal patterns of pesticide use (never, former, or recent use) when there were at least 20 cases of CKD in each of these strata. Multivariable linear regression was used to estimate the percent difference in the geometric mean eGFR and 95% confidence intervals (95% CIs) among individual pesticide users compared to never users. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% CIs of CKD status in relation to use of individual pesticides. All models were adjusted for age at phlebotomy (continuous), state of residence (IA or NC), body mass index (continuous), history of diabetes (yes/no), history of hypertension (yes/no), alcohol consumption (none, <5, or 5+ drinks in the last 7 days), smoking status (never, former, current), and correlated pesticides (Pearson’s ρ>0.40; Table S1). We also performed analyses without adjustment for body mass index, hypertension, and diabetes, as pesticides may influence kidney function through effects on these factors. Tests of exposure-response trends across quartiles in analyses of both eGFR and CKD were performed using the intra-quartile median IWLD treated as a continuous variable in the models. We also evaluated results restricted to participants who reported performing farming activities and/or applying pesticides occupationally within the 12 months prior to BEEA enrollment. Sensitivity analyses restricting to non-Hispanic whites (N=1,502) and excluding those with a history of reported kidney disease (N=23) or autoimmune disorders (N=91) did not substantively influence our results (data not shown). All statistical analyses were performed using SAS version 9.4 (Cary, NC). All tests were two-sided with alpha=0.05.

Results

Study population characteristics.

Seventy-seven percent of the study participants resided in Iowa, 39% had a body mass index ≥30 kg/m2, 45% reported a history of hypertension, and 14% reported a history of diabetes (Table 1). The median (minimum-maximum) eGFR of the study population was 83 (11–114) mL/min/1.73 m2, with 13% of participants characterized as having CKD. Participants with CKD were more likely than those without CKD to report known risk factors for diminished kidney function (e.g., increased age, diabetes, and hypertension). Eighty-four percent of our study participants reported actively farming within the last 12 months; the prevalence of CKD among active farmers and non-active farmers was 11% and 23%, respectively.

Table 1.

Select BEEA enrollment characteristics and chronic kidney disease

Characteristic Total (N=1545) N(%) Chronic Kidney Diseasea
No (N=1341) N(%) Yes (N=204) N(%) p-valueb
State
 Iowa 1185 (77) 1040 (78) 145 (71) 0.04
 North Carolina 360 (23) 301 (22) 59 (29)
Age category
 50–59 482 (31) 474 (35) 8 (4) <0.0001
 60–69 549 (36) 494 (37) 55 (27)
 ≥70 514 (33) 373 (28) 141 (69)
Body mass index (kg/m2)
 <25 252 (16) 214 (16) 38 (19) 0.41
 25–29.99 683 (44) 601 (45) 82 (40)
 ≥30 610 (39) 526 (39) 84 (41)
Tobacco smoking
 Never 912 (59) 806 (60) 106 (52) 0.02
 Former 565 (37) 473 (35) 92 (45)
 Current 68 (4) 62 (5) 6 (3)
Alcohol consumption (last 7 days)
 None 770 (50) 644 (48) 126 (62) 0.0003
 <5 420 (27) 370 (28) 50 (25)
 5+ 355 (23) 327 (24) 28 (14)
History of hypertension
 No 849 (55) 781 (58) 68 (33) <0.0001
 Yes 696 (45) 560 (42) 136 (67)
History of diabetes
 No 1321 (86) 1176 (88) 145 (71) <0.0001
 Yes 224 (14) 165 (12) 59 (29)
Active farmerc
 No 243 (16) 187 (14) 56 (27) <0.0001
 Yes 1302 (84) 1154 (86) 148 (73)
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Note: due to rounding total % may not equal 100%.

a

Defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2.

b

Chi-square test for homogeneity.

c

Reported farming activities or occupational pesticide use within 12 months prior to BEEA enrollment.

Ever use of pesticides and kidney function.

Statistically significant differences in kidney function (i.e., eGFR levels or CKD status) were observed among participants reporting ever use of six individual pesticides on AHS or BEEA questionnaires when compared to never users (Table 2). Associations with lower eGFR were observed for ever use of the herbicides pendimethalin (−3.7%, 95% CI: −5.8%, −1.5%), atrazine (−3.7%, 95% CI: −6.9%, −0.4%), and dicamba (−2.8%, 95% CI: −5.3%, −0.2%). Both pendimethalin (OR = 1.6, 95% CI: 1.1, 2.2) and atrazine (OR = 1.8, 95% CI: 1.0, 3.0) were also associated with elevated odds of CKD. When restricted to active farmers, the odds of CKD among atrazine users was further elevated (OR = 2.6, 95% CI: 1.2, 5.4) compared to never users (Table S2). When examining CKD among those with greater impairment in kidney function (GFR category G3b or higher; eGFR <45 mL/min/1.73 m2), the odds of CKD among atrazine users was also further elevated (OR = 2.1, 95% CI: 0.9, 4.9) compared to never users (Table S3). We observed associations with higher eGFR for ever use of the insecticide malathion (3.5%, 95% CI: 0.7%, 6.5%) and the fumigant methyl bromide (5.3%, 95% CI: 0.8%, 10.0%) when compared to never users (Table 2). Malathion and methyl bromide, as well as diazinon, were associated with reduced odds of CKD. These patterns of association were similar in analyses: 1) stratified by age at BEEA enrollment/phlebotomy (<70 years, ≥70 years; Table S4); 2) further adjusted for alcohol consumption at AHS enrollment in 1993–1997 (Table S5); and 3) not adjusted for body mass index, hypertension, or diabetes (Table S6).

Table 2.

Associations between ever use of individual pesticides and kidney function among male pesticide applicators enrolled in the Biomarkers of Exposure and Effect in Agriculture Studya

eGFR
CKD
Pesticide Nexposed/Nunexposed Percent Change (95% CI)b NCKD/Nexposedc OR (95% CI)d
HERBICIDES
 Atrazine 1320/225 −3.7 (−6.9 to −0.4) 180/1320 1.8 (1.0 to 3.0)
 Dicamba 996/549 −2.8 (−5.3 to −0.2) 120/996 1.1 (0.7 to 1.6)
 Cyanazine 789/756 1.5 (−1.0 to 4.0) 98/789 1.0 (0.7 to 1.5)
 Chlorimuron-Ethyl 616/929 0.6 (−1.9 to 3.1) 45/616 0.9 (0.7 to 1.4)
 Metolachlor/S-Metolachlor 824/721 −0.7 (−2.9 to 1.6) 104/824 1.2 (0.9 to 1.8)
 EPTC 282/1263 1.0 (−1.8 to 4.0) 28/282 0.8 (0.5 to 1.3)
 Alachlor 957/588 −1.0 (−3.2 to 1.4) 124/957 1.2 (0.8 to 1.7)
 Metribuzin 726/819 −2.6 (−5.3 to 0.2) 96/726 1.0 (0.7 to 1.6)
 Paraquat 388/1157 −1.8 (−4.4 to 0.9) 60/388 1.2 (0.8 to 1.8)
 Petroleum Distillates 840/705 2.1 (−0.1 to 4.4) 108/840 1.0 (0.7 to 1.4)
 Pendimethalin 734/811 −3.7 (−5.8 to −1.5) 103/734 1.6 (1.1 to 2.2)
 Imazethapyr 661/884 −1.8 (−4.2 to 0.6) 74/661 1.1 (0.7 to 1.6)
 Glyphosate 1443/102 3.2 (−1.3 to 7.9) 182/1443 0.9 (0.5 to 1.6)
 Silvex 196/1349 −0.8 (−4.5 to 3.0) 34/196 1.1 (0.7 to 1.9)
 Butylate 622/923 1.7 (−1.0 to 4.4) 79/622 0.8 (0.5 to 1.2)
 Trifluralin 716/829 −1.2 (−3.8 to 1.5) 101/716 1.3 (0.9 to 1.9)
 2,4-D 1358/187 1.7 (−1.7 to 5.3) 172/1358 0.8 (0.5 to 1.3)
 2,4,5-T 471/1074 −1.7 (−4.5 to 1.1) 82/471 0.9 (0.6 to 1.3)
INSECTICIDES
 Permethrin 614/931 −0.6 (−2.9 to 1.7) 60/614 0.8 (0.6 to 1.2)
 Terbufos 755/790 0.6 (−1.7 to 3.0) 90/755 0.9 (0.7 to 1.4)
 Fonofos 463/1082 −0.7 (−3.2 to 1.8) 62/463 1.3 (0.9 to 1.9)
 Lindane 442/1103 −0.4 (−2.8 to 2.1) 58/442 0.9 (0.6 to 1.3)
 Carbofuran 566/979 0.2 (−2.0 to 2.6) 80/566 1.0 (0.7 to 1.4)
 Chlorpyrifos 847/698 1.5 (−0.7 to 3.8) 94/847 0.9 (0.6 to 1.2)
 Malathion 1255/290 3.5 (0.7 to 6.5) 155/1255 0.7 (0.5 to 1.0)
 Methyl Parathion 250/1295 2.0 (−1.0 to 5.2) 37/250 0.9 (0.6 to 1.4)
 Carbaryl 888/657 1.8 (−0.5 to 4.3) 117/888 0.8 (0.5 to 1.1)
 Diazinon 536/1009 1.8 (−0.8 to 4.4) 69/536 0.7 (0.5 to 1.0)
 Phorate 598/947 1.0 (−1.4 to 3.5) 76/598 0.9 (0.6 to 1.3)
 Aldrin 345/1200 0.4 (−2.8 to 3.8) 67/345 0.9 (0.6 to 1.4)
 Chlordane 451/1094 −1.1 (−3.9 to 1.8) 80/451 1.3 (0.9 to 1.9)
 Dieldrin 127/1418 0.7 (−3.7 to 5.4) 26/127 0.9 (0.5 to 1.5)
 DDT 402/1143 2.2 (−0.6 to 5.2) 83/402 0.8 (0.5 to 1.1)
 Heptachlor 341/1204 −1.3 (−4.4 to 1.9) 68/341 1.2 (0.8 to 1.8)
 Toxaphene 244/1301 1.8 (−1.6 to 5.3) 40/244 0.8 (0.5 to 1.3)
 Coumaphos 179/1366 0.3 (−3.0 to 3.8) 21/179 0.9 (0.6 to 1.6)
 Dichlorvos 257/1288 0.3 (−2.6 to 3.4) 35/257 1.3 (0.8 to 1.9)
FUNGICIDES
 Captan 225/1320 0.0 (−3.1 to 3.2) 32/225 1.2 (0.7 to 1.8)
 Metalaxyl 361/1184 −1.4 (−4.2 to 1.6) 47/361 1.1 (0.7 to 1.6)
FUMIGANTS
 Methyl Bromide 198/1347 5.3 (0.8 to 10.0) 22/198 0.4 (0.2 to 0.8)
 Tetrachloride/Carbon Disulfide 121/1424 −2.0 (−6.0 to 2.1) 26/121 1.1 (0.7 to 1.9)
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Notes: CKD, chronic kidney disease; CI, confidence interval; eGFR, estimated glomerular filtration rate; OR, odds ratio.

a

Analysis included a total of 1545 BEEA participants, of which 204 were classified as having CKD (i.e., estimated glomerular filtration rate <60 mL/min/1.73 m2)

b

Multivariable linear regression models were used to estimate the percent change in the geometric mean estimated glomerular filtration rate and 95% confidence intervals among individual pesticide users compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

c

Nckd/Nexposed refers to the number of participants with CKD out of the number of participants exposed to a specific pesticide.

d

Multivariable logistic regression models were used to estimate odds ratios and 95% confidence intervals for associations between individual pesticide users and chronic kidney disease status compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

Bold results denote a P-value <0.05

IWLDs for select pesticides and kidney function.

The associations between kidney function and quartiles of IWLDs for pesticides associated with altered eGFR levels and CKD status in analyses of ever/never use are summarized in Table 3 for the total population and after restricting to active farmers. High IWLDs of pendimethalin use was associated with elevated odds of CKD compared to never users (fourth quartile of IWLDs of use vs. no use: ORQ4=1.9, 95% CI: 1.0, 3.6, ptrend=0.05), and this association was more apparent among active farmers (fourth quartile of IWLDs of use vs. no use: ORQ4=2.2, 95% CI: 1.1, 4.6, ptrend=0.04). For atrazine, there was no evidence of a trend of increased risk of CKD with increased IWLDs of use when compared to never users; however, among active farmers, atrazine was significantly associated with CKD at all exposure levels (ORs all greater than 2). High use of malathion was associated with higher eGFR (fourth quartile of IWLDs of use vs. no use: 6.8%, 95% CI: 2.9%, 10.9%, ptrend=0.003) and decreased risk of CKD (fourth quartile of IWLDs of use vs. no use: ORQ4=0.4, 95% CI: 0.2, 0.7, ptrend=0.005). The association with malathion was similar after restricting to active farmers. Methyl bromide use was not associated with altered kidney function across any IWLD exposure level compared to never users, among the total or active farming populations.

Table 3.

Associations between cumulative intensity-weighted lifetime days of use across select pesticides and kidney function

Total Population Active Farmers a
eGFR
 CKD
 eGFR
 CKD
Pesticide IWLDb Nc Percent Change (95% CI)d Ne OR (95% CI)f Nc Percent Change (95% CI)d Ne OR (95% CI)f
HERBICIDES
 Pendimethalin 0 811 Ref 101 Ref 654 Ref 70 Ref
28–310 115 −4.9 (−8.9 to −0.8) 22 1.9 (1.0 to 3.4) 104 −4.5 (−8.5 to −0.4) 17 1.7 (0.9 to 3.3)
>310–836 112 −4.2 (−8.3 to 0.0) 16 1.6 (0.8 to 3.0) 102 −4.9 (−8.9 to −0.7) 14 1.7 (0.8 to 3.4)
>836–2140 113 −4.3 (−8.3 to −0.1) 16 1.5 (0.8 to 2.9) 99 −3.7 (−7.7 to 0.6) 11 1.4 (0.7 to 2.9)
>2140–34554 113 −2.8 (−6.9 to 1.5) 16 1.9 (1.0 to 3.6) 98 −3.2 (−7.3 to 1.1) 13 2.2 (1.1 to 4.6)
p trend g 0.16 0.05 0.14 0.04
 Atrazine 0 225 Ref 24 Ref 153 Ref 10 Ref
25–1587 324 −3 (−6.7 to 0.8) 49 1.7 (0.9 to 3.1) 261 −3.9 (−8.0 to 0.3) 34 2.8 (1.2 to 6.2)
>1587–4340 325 −5 (−8.7 to −1.2) 47 2.0 (1.1 to 3.7) 276 −5.0 (−9.0 to −0.8) 31 2.6 (1.1 to 6.0)
>4340–9799 322 −1.9 (−5.8 to 2.0) 41 1.5 (0.8 to 2.8) 287 −2.8 (−6.9 to 1.5) 35 2.3 (1.0 to 5.1)
>9799–127520 324 −3.2 (−7.0 to 0.7) 41 1.7 (0.9 to 3.1) 302 −4.0 (−8.0 to 0.2) 37 2.6 (1.1 to 5.8)
p trend g 0.75 0.76 0.61 0.48
INSECTICIDES
 Malathion 0 290 Ref 49 Ref 21 8 Ref 4 1 Ref
20–385 207 4.1 (0.2 to 8.1) 24 0.7 (0.4 to 1.3) 184 4.5 (0.4 to 8.6) 19 0.6 (0.3 to 1.3)
>385–1080 207 1.9 (−1.8 to 5.9) 30 0.8 (0.5 to 1.4) 179 1.6 (−2.3 to 5.8) 25 0.8 (0.4 to 1.5)
>1080–2940 205 3.0 (−0.8 to 7.0) 27 0.7 (0.4 to 1.3) 169 4.6 (0.4 to 8.9) 17 0.6 (0.3 to 1.1)
>2940–117600 204 6.8 (2.9 to 10.9) 17 0.4 (0.2 to 0.7) 175 7.0 (2.9 to 11.4) 12 0.3 (0.2 to 0.7)
p trend g 0.003 0.005 0.004 0.01
FUMIGANTS
 Methyl Bromide 0 1347 Ref 182 Ref 11 51 Ref 13 4 Ref
7–257 49 3.9 (−2.8 to 11.0) 4 0.4 (0.1 to 1.4) 31 5.8 (−2.1 to 14.3) 0 —h
>257–960 49 5.8 (−1.3 to 13.5) 6 0.6 (0.2 to 1.6) 39 2.6 (−4.8 to 10.6) 5 1.0 (0.3 to 3.0)
>960–2410 49 6.8 (−0.5 to 14.5) 6 0.4 (0.1 to 1.1) 40 1.2 (−6.1 to 9.1) 4 0.4 (0.1 to 1.6)
>2410–102000 49 4.8 (−2.3 to 12.5) 6 0.4 (0.2 to 1.2) 39 0.1 (−7.2 to 8.0) 5 0.6 (0.2 to 1.9)
p trend g 0.31 0.12 0.90 0.39
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Notes: CKD, chronic kidney disease; CI, confidence interval; eGFR, estimated glomerular filtration rate; IWLD, cumulative intensity-weighted lifetime days; OR, odds ratio.

a

Reported farming activities or occupational pesticide use within the last 12 months.

b

Cumulative value across all reported use from Agricultural Health Study and Biomarkers of Exposure and Effect in Agriculture study interviews.

c

Number of individuals who provided additional information on application method and use of personal protective equipment for individual pesticides (sum of participants are unique to each pesticide).

d

Multivariable linear regression models were used to estimate the percent change in the geometric mean estimated glomerular filtration rate and 95% confidence intervals among individual pesticide users compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

e

Number of individuals characterized as having chronic kidney disease (i.e., an estimated glomerular filtration rate <60 mL/min/1.73 m2).

f

Multivariable logistic regression models were used to estimate odds ratios and 95% confidence intervals for associations between individual pesticide users and CKD status compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

g

Based on intra-quartile median values of intensity-weighted lifetime days

h

No OR estimated due to lack of CKD cases in strata

Bold results denote a P-value <0.05

Temporal patterns of atrazine use and kidney function.

A total of 349 BEEA participants reported using atrazine within the past 12 months (recent users), nearly all of whom also reported prior atrazine use from earlier AHS questionnaires (N=340; 97% of recent users); another 971 participants reported past use only (former users). We performed analyses evaluating associations between kidney function and atrazine use among those with former and recent use, respectively, relative to never users in the overall study population, and with total cumulative IWLDs of atrazine use in separate models stratified by recent and former atrazine use with never users as the referent category. The results of these analyses are summarized in Table 4. Associations with altered kidney function were observed for both former and recent atrazine users but were most apparent among those with recent use. Compared with never users, those with recent atrazine use had a lower eGFR (−5.1%, 95% CI −8.8%, −1.2%) and elevated odds of CKD (OR=2.2, 95% CI: 1.1, 4.3). In analyses focused on those with CKD and greater impairment of kidney function (GFR category G3b or higher; eGFR <45 mL/min/1.73 m2), we observed a stronger (although non-statistically significant) association with recent atrazine use (OR=3.0, 95% CI: 0.9, 9.8) compared to never users (Table S3). Furthermore, among participants with recent atrazine use, we observed exposure-response associations with increasing IWLDs of use compared to never users (Table 4). Recent atrazine users in the highest quartile of cumulative IWLDs of atrazine use had both lower eGFR (−6.6%, 95% CI: −11.0%, −2.0%, ptrend=0.01) and elevated odds of CKD (OR=2.4, 95% CI: 1.1, 5.4, ptrend=0.03). Participants who reported only former use of atrazine had lower eGFR (−3.3%, 95% CI: −6.6%, 0.0%) and increased odds of CKD (OR=1.7, 95% CI: 1.0, 2.9) when compared to never users, although there was no evidence of an exposure-response trend with cumulative IWLDs among former users.

Table 4.

Associations between recent or former atrazine use and kidney function

eGFR
Percent Change (95% CI) a 		CKD
OR (95% CI)b
Atrazine Usec NCKD/Ntotal Overall IWLDs Overall IWLDs
NEVER 24/225 Ref Ref
FORMER d 151/971 −3.3 (−6.6 to 0.0) 1.7 (1.0 to 2.9)
 Low 89/565 −4.1 (−7.5 to −0.7) 1.8 (1.1 to 3.2)
 Mid 32/217 −1.1 (−5.2 to 3.2) 1.4 (0.7 to 2.6)
 High 28/179 −0.6 (−4.9 to 4.0) 1.4 (0.7 to 2.8)
 ptrende 0.19 0.71
RECENT d 29/349 −5.1 (−8.8 to −1.2) 2.2 (1.1 to 4.3)
 Low 7/84 −3.7 (−9.0 to 1.9) 2.0 (0.8 to 5.4)
 Mid 9/105 −3.8 (−8.8 to 1.4) 2.1 (0.8 to 5.2)
 High 13/145 −6.6 (−11.0 to −2.0) 2.4 (1.1 to 5.4)
 ptrende 0.01 0.03
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Notes: CKD, chronic kidney disease; CI, confidence interval; eGFR, estimated glomerular filtration rate; IWLDs, intensity weighted lifetime days; OR, odds ratio

a

Multivariable linear regression models were used to estimate the percent change in the geometric mean estimated glomerular filtration rate and 95% confidence intervals among individual pesticide users compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

b

Multivariable logistic regression models were used to estimate odds ratios and 95% confidence intervals for associations between atrazine users and chronic kidney disease status compared to never users, controlling for age at interview, state of residence, body mass index, diabetes, hypertension, smoking status, alcohol consumption, and correlated pesticides.

c

Never use: no reported atrazine use on any AHS or BEEA questionnaires; Former use: reported no atrazine use within the last 12 months on BEEA questionnaire and had previously reported using atrazine on at least one AHS questionnaire (enrollment or follow up interviews); Recent Use: reported using atrazine within the last 12 months on the BEEA questionnaire.

d

Low: 25–4340 IWLDs; Mid: >4340–9799 IWLDs; High: >9799–127520 IWLDs

e

Based on intra-strata median values of IWLDs

Bold results denote a P-value <0.05

Discussion

This study of occupationally exposed pesticide applicators is, to our knowledge, the first to evaluate early stage alterations in kidney function in relation to a wide range of specific pesticides. We found ever use of the herbicides pendimethalin, atrazine, and dicamba was associated with reduced eGFR. We also observed associations with CKD for use of pendimethalin and atrazine, with greater than two-fold elevated odds for high lifetime use of these herbicides among active farmers. On the other hand, we also observed associations with higher eGFR and reduced odds of CKD for several pesticides.

Herbicides.

We evaluated use of 18 herbicides and observed reduced kidney function among applicators with a history of pendimethalin, atrazine, or dicamba use. Forty-eight percent of study participants reported using pendimethalin, which is a commonly used herbicide in the US for both agricultural and residential purposes (US EPA 2017). Our findings for pendimethalin align with the results of a previous AHS investigation of 55,580 male pesticide applicators that reported an elevated risk of end-stage renal disease (hazard ratio=2.1, 95% CI: 1.2, 3.8, ptrend=0.004) among participants within the highest tertile of pendimethalin use when compared to never users (Lebov et al. 2016). In a recent investigation of RCC risk among pesticide applicators in the AHS (Andreotti et al. 2020), results of a 20 year-lagged exposure analysis demonstrated suggestive evidence of an elevated risk among those in the highest tertile of use compared with never users (relative risk=1.7, 95% CI 0.9, 3.2, ptrend=0.05). Recent animal studies have observed oxidative stress and DNA damage in the kidney following exposure to pendimethalin (Ahmad et al. 2018), but additional molecular studies are needed to further characterize potential mechanisms given the widespread use of this chemical.

Atrazine remains one of the most widely used herbicides in our study population, despite being banned in the European Union due concerns related to widespread water contamination (European Commission 2004). Our finding that ever use of atrazine may be associated with diminished kidney function is in line with previous efforts within the AHS that have shown an association between lifetime use of atrazine and both malignant and non-malignant kidney disease (Andreotti et al. 2020; Lebov et al. 2016). In overall analyses of cumulative IWLDs, there was not an apparent exposure-response association, but atrazine was associated with higher risk of CKD at all levels of use among active farmers. The associations between atrazine use and diminished kidney function were especially apparent for applicators who reported using this herbicide within 12 months prior to enrollment in BEEA; among these recent users (nearly all of whom also used atrazine previously), we observed statistically significant exposure-response associations with lower eGFR and increased risk of CKD for higher cumulative IWLDs of atrazine use. We also observed suggestive evidence that use of atrazine, in particular recent use, may be associated with more advanced CKD (i.e., GFR category G3b or higher). These results suggest that continued atrazine use over an applicator’s working lifetime may be associated with kidney dysfunction.

As with pendimethalin, the biological mechanisms through which atrazine may influence kidney health are not well understood. Atrazine has been shown to be a potent endocrine disrupting chemical (Kucka et al. 2012) that can activate the hypothalamic-pituitary-adrenal axis (Fraites et al. 2009). Activation of this axis has been associated with progression of kidney disease (Asao et al. 2016). Additional animal studies also suggest that atrazine exposure may cause kidney damage through DNA damage and oxidative stress (Abarikwu 2014; Pino et al. 1988). Despite the experimental evidence, a longitudinal study of atrazine applicators did not find associations between urinary atrazine metabolites and markers of oxidative stress (Lerro et al. 2017). Future investigations with timed atrazine exposures and biomarkers related to kidney damage are needed to further elucidate the potential mechanisms through which atrazine may be associated with kidney disease.

Overall, ever use of dicamba was associated with lower eGFR among pesticide applicators. However, we did not find evidence of associations with CKD for dicamba in analyses of ever use, or with CKD or eGFR for IWLDs of dicamba use (data not shown). The lack of association with CKD aligns with previous epidemiologic evidence within the AHS that showed no significant relationship with end-stage renal disease among applicators or their spouses with regard to lifetime use of dicamba (Lebov et al. 2015; Lebov et al. 2016). It is possible that the observed association with dicamba and eGFR among ever users may reflect subclinical effects to the kidney. There is some experimental evidence to support this, including animal studies of acute exposure to dicamba that have shown the kidneys are the major route of elimination and exposure may cause damage to the kidney tubular epithelium (Mukherjee et al. 2010). Acute damage to the tubular epithelium has been suggested as a potential mechanism through which subclinical kidney damage can progress to CKD (Liu et al. 2018).

In the larger AHS cohort, several other herbicides (alachlor, metolachlor, and paraquat) were also associated with risk of end-stage renal disease among pesticide applicators (Lebov et al. 2016), and husbands’ use of paraquat was also associated with risk of end-stage renal disease among female spouses (Lebov et al. 2015). High lifetime use of paraquat was also associated with an increased risk of RCC in 20-year lagged analyses among pesticide applicators (Andreotti et al. 2020). In our investigation, we observed somewhat lower eGFR among applicators who reported using each of these herbicides compared with never users, although differences were not statistically significant.

Insecticides.

We evaluated lifetime use of 19 individual insecticides. None of these insecticides was associated with diminished kidney function, whereas malathion was associated with higher kidney function and both malathion and diazinon were associated with lower odds of CKD. These were unexpected findings as the limited data from animal models (Karmakar et al. 2016; Selmi et al. 2018; Shah and Iqbal 2010) and case studies of accidental poisonings (Albright et al. 1983; Dive et al. 1994; Yokota et al. 2017) have suggested malathion and diazinon may be associated with kidney damage. Furthermore, the prior studies of end-stage renal disease in the AHS did not find decreased risk associated with use of malathion or diazinon (Lebov et al. 2015; Lebov et al. 2016). Use of the pyrethroid insecticide permethrin was previously associated with risk of end-stage renal disease among pesticide applicators in the AHS, but was not associated with eGFR or CKD in our investigation.

Fumigants and fungicides.

No associations between fungicides assessed and kidney function were observed. Ever use of the fumigant, methyl bromide, was however associated with higher eGFR and lower risk of CKD. Use of methyl bromide (EPA 2018) has largely been phased out or banned in the US since 2005 and the percentage of BEEA participants reporting recent use was less than 0.1%. The decreased risk of CKD found for methyl bromide is not supported by results from the earlier investigations of end-stage renal disease in the cohort (Lebov et al. 2015; Lebov et al. 2016). Furthermore, previous literature suggests methyl bromide is nephrotoxic (National Research Council 2010). This unexpected finding in our study should be interpreted cautiously given the limited number of individuals who reported using methyl bromide and had CKD (N=22) and could possibly reflect healthy worker survivor bias given the long-time interval since the use of this fumigant.

Strengths and limitations.

A major strength of this study was the ability to investigate associations between prospectively assessed lifetime use of individual pesticides and early alterations to kidney function within a large cohort of occupationally exposed pesticide applicators. Self-reported pesticide use and intensity metrics have been shown to be correlated with urinary biomarkers of exposure among AHS participants (Thomas et al. 2010), suggesting bias due to exposure misclassification may not be a major concern in this population. We were able to further control for a range of co-exposures (e.g., correlated pesticides) and possible factors related to kidney function (e.g., age, hypertension, diabetes, obesity, and alcohol consumption). While we were unable to control for other potentially important factors related to kidney health such as hydration status, albuminuria, or physical activity, there is no reason to suggest these factors would be related to use of some specific pesticides (but not others). Furthermore, the observed associations were generally similar or stronger among those still actively farming; as such, we have no reason to think that these would be important confounding factors. We assessed CKD status based on a single blood draw. Typically, CKD is diagnosed after measurements indicate that eGFR <60 mL/min/1.73 m2 is sustained for at least three months, which may have resulted in an overestimation of CKD in our study (Bottomley et al. 2011).

Conclusions.

Lifetime use of several herbicides was associated with lower kidney function within this cohort of occupationally exposed pesticide applicators from the US. Our findings provide new insights into the potential role of specific pesticides – in particular atrazine and pendimethalin – in the development of kidney disease. The observed associations with atrazine and pendimethalin are notable in light of available evidence regarding biologic plausibility and consistency with previous findings for malignant and non-malignant kidney disease (Lebov et al. 2016; Andreotti et al. 2020). Findings for other pesticides for which limited a priori evidence was available should be interpreted more cautiously and warrant confirmation in future studies. Furthermore, our results for atrazine and pendimethalin underscore the importance of using appropriate personal protective equipment and following other best application practices to minimize potential exposures while handling pesticides. With continued widespread use of these herbicides, most notably atrazine, elucidating the mechanisms through which they may influence the development of kidney disease is of major public health importance.

Supplementary Material

1

Highlights.

  • Both lifetime and recent use of atrazine were associated with lower kidney function, with exposure-response associations for intensity-weighted lifetime days among recent atrazine users

  • Lifetime use of several other herbicides (pendimethalin, dicamba) was also associated with lower kidney function

  • The observed associations with lower kidney function for use of atrazine and pendimethalin are consistent with prior findings for risk of end-stage renal disease in the Agricultural Health Study

Acknowledgements

This work was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute (Z01 CP 010119) and National Institute of Environmental Health Sciences (Z01 ES 049030). Dr. Ola Landgren and Dr. Kazunori Murata are supported by the Memorial Sloan Kettering Core Grant (P30 CA008748). We would like to thank Amy Miller, Kate Torres, Sandor Balogh, Himanshi Singh, and Marsha Dunn (Westat, Rockville, Maryland), and Debra Podaril, Debra Lande, and Jennifer Hamilton (University of Iowa) for study coordination, data management, and field research efforts. We also thank Anne Taylor and Peter Hui (Information Management Services, Rockville, Maryland) for data management and analytic support. The authors gratefully acknowledge the ongoing participation of the Agricultural Health Study participants that made this work possible.

Footnotes

Declaration of competing financial interests (CFI) The authors declare they have no competing financial interests.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Disclaimer

JJS contributed to this manuscript while employed at the National Cancer Institute and is currently employed at the U.S. Food and Drug Administration. This manuscript reflects the views of the authors and should not be construed to represent the U.S. Food and Drug Administration’s views or policies.

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