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Table 2 Studies from Sri Lanka and other non-Mesoamerican countries assessing the role of pesticides in CKD

From: Pesticide exposures and chronic kidney disease of unknown etiology: an epidemiologic review

Reference & country

Study design

Population

Exposure assessment

Case definition/outcome(s)

Main findings

Pesticide association

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Validity and explanation valuea

Sri Lanka

Peiris-John et al., 2006 [87]

Sri Lanka

Cross-sectional

4 groups: 23 OP-exposed farmers with chronic renal failure (CRF) vs 18 unexposed patients with CRF vs 239 OP-exposed farmers without CRF vs 50 unexposed fishermen without CRF

Red blood cell acetyl cholinesterase (AChE) levels (U/g) as proxy of organophosphate exposures

CRF (not further specified)

Significant differences in AChE levels: exposed CRF (18.6 U/g) < unexposed CRF (26.6) < exposed non-CRF (29.1) < non-exposed non-CRF (32.6)

Possible association between long-term low-level OP-exposures, cholinesterase levels and CKD

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Exploratory aim with unconventional cross-sectional design; inadequate selection of study participants; high risk of bias from exposure misclassification; high risk of confounding

Explanation value: low

Wanigasuriya et al., 2007 [36]

Sri Lanka

Hospital- based case – control (prevalent cases)

183 CKDu cases (136 M, 47 F), 200 controls among HT and DM patients (139 M, 61 F), age 36-67

Questionnaire:

Farmer yes/no

Pesticide exposure yes/no

Drinking water source (well-water home, well-water field, pipe born)

SCr > 2 mg/dL

Bivariate analyses:

Males:

OR farmer = 4.68 [2.50- 8.82)

OR pesticides = 2.94 [1.73-5.01]

OR drinking well-water field = 1.72 [0.92-3.22]

Females:

OR farmer = 1.28 [0.55-2.99)

OR pesticides: 0 cases

OR drinking well-water home = 4.24 [1.51-12.32]

Multivariate logistic regressions: NO associations for farming, pesticide use and drinking well-water

No associations in multivariate analyses with farming, pesticide use and well-water

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Prevalent cases; high risk of bias from exposure misclassification; inadequate reporting of statistical analyses and pesticide results

Explanation value: low

Athuraliya et al., 2011 [19]

Sri Lanka

Cross-sectional population-based survey with case –control analyses

6153 (2889 M, 3264 F): age >19

á…Ÿ

CKDu endemic area Medawachchiya 2600

Two non-endemica areas Yatinuwara708

Hambantota 2844

á…Ÿ

109 CKDu patients in Medawachchiya (66 M, 43 F)

Questionnaire

-Farmer yes/no

-Spraying or handling agrochemicals yes/no

Proteinuric chronic kidney disease

Entire study population:

Adj OR farmer 2.6 (1.9–3.4)

Adj OR agrochemical exposure 2.3 (1.4–3.9)

Medawachchiya (CKDu region)

Adj OR farmer 2.1 (1.4–3.3)

Adj OR agrochemical exposure 1.1 (0.7–1.9)

á…Ÿ

Yatinuwara (non-CKDu region)

Adj OR farmer 1.5 (0.5–3.9)

Adj OR agrochemical exposure 1.6 (0.8–3.2)

á…Ÿ

Hambantota (non-CKDu region)

Adj OR farmer 1.6 (1.0–2.7)

Adj OR agrochemical exposure 5.6 (2.3–13.2)

Pesticide use was not associated to proteinuric CKD in the CKDu region, but it was associated to CKD of known causes in one of the two non-CKDu regions.

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Cross-sectional, crude pesticide exposure assessment, misclassification of disease

Explanation value: medium

Wanigasuriya et al., 2011 [92]

Sri Lanka

Cross-sectional population-based survey with case –control analyses

886 (461 M, 425 F) household members aged ≥18

Questionnaire:

Farmer yes/no

Pesticide spraying yes/no

Drinking water source

Micro-proteinuria

Bivariate analyses:

OR farmer = 1.38 [0.71- 2.70)

OR pesticides = 1.01 [0.60-1.72]

OR well-water in the field = 1.79 [1.07-3.01]

á…Ÿ

Multivariate logistic regression:

OR pesticides = 0.43 [0.21-0.90]

OR well-water in the field = 1.92 [1.04-3.53]

Positive association with drinking from well-water in the field

Negative association with pesticide spraying

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Cross-sectional, crude pesticide exposure assessment, misclassification of disease

Explanation value: medium

Jayasumana et al., 2015 [95]

Sri Lanka

Hospital-based case-control (prevalent cases)

125 cases (89 M, 36 F), 180 controls (98 M, 82 F)

Questionnaire:

Usual occupation last 10 years, farming yes/no

Use of fertilizer and specific pesticides over last 10 years yes/no

(organophosphates, paraquat, MCPA, glyphosate, bispyribac, carbofuran, mancozeb and other common pesticides)

Glyphosate, metals and hardness measured in water of serving and abandoned wells

CKDu

Bivariate logistic regression with significantly increased ORs for farming, use of fertilizers, and use of organophosphates, paraquat, MCPA, glyphosate, bispyribac and mancozeb

á…Ÿ

Multivariate logistic regression:

OR drinking well water = 2.52 [1.12-5.70]

OR history drinking water from abandoned well = 5.43 [2.88-10.26]

OR pesticide application = 2.34 [0.97- 5.57]

OR use of glyphosate = 5.12 [2.33-11.26]

á…Ÿ

Water hardness: abandoned wells: very high; serving wells: moderate to hard; reservoir and pipeline: soft

Glyphosate concentration in water from abandoned well significantly higher than in serving wells (median 3.2 μg/L and 0.6 μg/L, respectively).

Positive association with pesticide applications

Positive association with use of glyphosate

Positive association with drinking well-water and, especially, with history of drinking water from abandoned (with hardest water and highest glyphosate levels)

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Prevalent cases; relatively good case ascertainment; specific, unquantified pesticide exposure assessment

Exposure response for glyphosate in water; control of potential confounders

Explanation value: high

Other countries

Kamel & El-Minshawy, 2010 [6]

Egypt

Hospital-based case-control (prevalent cases)

216 ESRD cases (141 M, 75 F) from unknown cause

220 random controls (152 M, 68 F) from other patients

Questionnaire:

Rural residency yes/no

Drinking unsafe (non-pipe) water yes/no

Farming occupation yes/no

Pesticide exposures by any mean yes/no

ESRD of unknown cause (clinical exams)

Bivariate analyses: rural living, drinking unsafe water, being a farmer and pesticide exposure associated with ESRD (p < 0.001)

Multivariate analyses (model not specified):

OR pesticide exposure 2.08 [1.42 – 3.06]

Possible association with pesticide exposures

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Prevalent cases; no data to evaluate potential selection bias; crude exposure assessment, statistical methods not well described

Explanation value: low

Siddharth et al., 2012 [75]

India

Note: this study is an interim report of Siddarth et al., 2014 [76]

Hospital-based case-control (prevalent cases)

150 CKD cases (77 M, 73 F): patients attending nephrology departments

96 controls (51 M, 45 F): staff or persons accompanying CKD patients in the hospital

Age 30-50

Levels of organochlorine (OC) pesticides in blood

CKDu: eGFr <60 ml/min/1.73m2 for >3 months

Oxidative stress markers

Significantly higher blood levels in cases for α–HCH, γ-HCH, total HCH, α-endosulfan, β-endosulfan, aldrin, p,p’-DDE, and TPL.

Among cases, adjusted Spearman correlations between eGFR and different pesticide analytes varied between −0.07 and −0.23 (significant for γ-HCH, total HCH and aldrin). When adjusting additionally for levels of other analytes, the association with eGFR remained significant only for aldrin. In addition, significant correlation between eGFR and TPL (r = −0.26).

Association of blood levels of OCs (from environmental exposures) with CKDu, mediated partially through genotype

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Prevalent cases; specific and quantitative assessment for non-occupational exposures to OCs, study in a non-CKDu setting; some potential for inverse causation; low risk for confounding

Explanation value: high

Siddarth et al., 2014 [76]

India

Hospital-based case-control (prevalent cases)

270 cases (140 M, 130 F): patients attending nephrology departments

270 age and sex matched controls: staff or persons accompanying CKD patients in the hospital

Concentrations of organochlorine pesticides in blood

GST genotyping

CKDu: eGFR <90 ml/min/1.73m2 with or without proteinuria, for 3 months

Cases had significantly higher blood concentrations of α–HCH, γ-HCH, total HCH, α-endosulfan, β-endosulfan, aldrin, p,p’-DDE, and total pesticides

Significant associations with CKDu for 3rd versus 1st tertile for α-HCH (OR = 2.52), γ-HCH (OR = 2.70), total-HCH (OR = 3.18), aldrin (OR = 3.07), α-endosulfan (OR = 2.99), and β-endosulfan (OR = 3.06). Total pesticides 3rd to 1st tertile OR = 2.73 [(1.46–9.47).

CKDu patients having either one null or two null genotypes tend to accumulate majority of pesticides, whereas in healthy controls only in the subset with both null genotypes for some pesticides.

Lebov et al., 2016 [97]

USA

Cohort (follow-up since 1993-1997)

55,580 licensed pesticide applicators (320 ESRD)

Self-administered questionnaires:

Ordinal categories of intensity-weighted lifetime days for 39 specific pesticides

Pesticide exposure resulting in medical visit or hospitalization

Diagnosed pesticide poisoning

High level pesticide exposure event

ESRD

Significantly increased HR for highest category of use vs non-users and significant exposure-response trends:

Alachlor HR = 1.51 [1.08-2.13], p for trend 0.015

Atrazine HR = 1.52 [1.11-2.09], p for trend 0.008

Metolachlor HR = 1.53 [1.08-2.13], p for trend 0.008

Paraquat HR = 2.15 [1.11-4.15], p for trend 0.016

Pendimethalin HR = 2.13 [1.20-3.78], p for trend 0.006

Permethrin HR = 2.00 [1.08-3.68], p for trend 0.031

More than one medical visit due to pesticide use HR = 2.13 [1.17 - 3.89], p for trend for increasing number of doctor visits 0.04.

Hospitalization due to pesticide use HR = 3.05 [1.67 to 5.58]

Association between use of specific pesticides and ESRD

Association between ESRD and exposures resulting in medical visits or hospitalization and ESRD

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Large cohort with long follow-up; study in non-CKDu endemic regions; specific and quantitative exposure assessment; multiple comparisons; low risk for confounding

Explanation value: high

Lebov et al., 2015 [96]

USA

Cohort (follow-up since 1993-1997)

31,142 wives of licensed pesticide applicators (98 ESRD)

Self-administered questionnaires or telephone interview

-direct exposures (n = 17,425): ordinal categories of intensity weighted lifetime use of any pesticide, 10 specific pesticides and 6 chemical classes

-Indirect pesticide exposures (husband’s pesticide use) among wives without personal use (n = 13,717)

-Indicators of residential pesticide exposure

ERSD

Highest category of cumulative lifetime-days of pesticide use in general vs never personal use: HR 4.22 [1.26-14.2]

Exposure-response trends for husband’s use of paraquat HR 1.99 [1.14-3.47] and butylate HR 1.71 [1.00-2.95]

No excess risk for indicators of residential exposures

Association between direct general pesticide use and husband’s use of paraquat and ESRD in women

No associations with residential exposures

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Large cohort with long follow-up; study in non-CKDu endemic regions; specific and quantitative exposure assessment; multiple comparisons; low risk for confounding

Explanation value: high

Aroonvilairat et al., 2015 [98]

Thailand

Cross-sectional

64 workers of orchids (30 M, 34 F) and 60 controls (33 M, 27 F)

Mixing and spraying pesticides during work at orchard for at least three months

Difference in BUN and SCr

BUN (mg/dL) exposed 12.64 ± 3.7 (3.7% abnormal) vs BUN unexposed 12.43 ± 2.9 (1.7% abnormal), p = 0.76

SCr (mg/dL) exposed females 0.86 ± 0.11 (3.7% abnormal) vs unexposed females 0.82 ± 0.11 (2.9% abnormal), p = 0.11

SCr exposed males 1.09 ± 0.11 (0% abnormal) vs unexposed males 1.09 ± 0.10 (0% abnormal), p = 0.95

No association between occupation in highly pesticide exposed farming and decreased kidney function

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Cross-sectional; crude exposure assessment, selection of study population not well described; no confounding adjustment

Explanation value: low

  1. Abbreviations: AChE red blood cell acetylcholinesterase, ACR albumin to creatinine ratio, ANOVA analysis of variance, CKD chronic kidney disease (u, of unknown etiology), BUN blood urea nitrogen, CRF chronic renal failure, DB diabetes, DW drinking water, DDE dichlorodiphenyldichloroethylene, eGFR glomerular filtration rate, ESRD end-stage renal disease, F female, GST glutathione-S-transferase, HCH hexachlorocyclohexane, HT hypertension, M male, MVLR multivariate logistic regression, OP organophosphate pesticides, SCr serum creatinine
  2. aExplanation value: The study’s ability to address potential associations between pesticdes and CKD or CKDu. For details see Additional file 2: Table S1 and the main text