Pesticides, Rheumatic Diseases, and Emerging Environmental Threats: A Scoping Review of Epidemiological and Mechanistic Evidence

Introduction

Pesticides are extensively used in agriculture, for disease vector control, and in urban settings, leading to widespread occupational and environmental exposure.¹ These exposures have been associated with increased risks of asthma, cancer, kidney dysfunction, and Parkinson’s disease.^2–5 Another important group of conditions associated with pesticide exposure includes autoimmune diseases such as inflammatory bowel disease and multiple sclerosis.^6,7 Growing evidence also indicates potential associations with rheumatic diseases, primarily those of autoimmune etiology, for example, rheumatoid arthritis, systemic lupus erythematosus, and Sjogren’s syndrome.^8–10 This evidence is supported by studies indicating that some pesticides can alter immune responses, triggering oxidative stress, inflammatory processes and autoimmunity.^11,12The inflammatory response triggered by pesticides has been extensively studied and is potentially associated with the production of reactive species (RS) and mitochondrial dysfunction.¹³ For instance, pesticides that disrupt the electron transport chain can lead to loss of oxidative phosphorylation, mtDNA depletion, and increased RS.^13,14 These changes trigger early inflammatory mediators, which, over time, may contribute to chronic inflammation.¹⁴ While studies using animal models have explored how pesticides affect cytokine production, lymphocyte subtypes, and immune responses in various mice models of autoimmune disease (RA: Collagen-Induced Arthritis; SLE: NZB/NZW F1)^15,16, similar mechanistic investigations specific to other rheumatic diseases are lacking.

Changing weather patterns, particularly widespread environmental shifts such as rising temperatures, altered precipitation patterns, and elevated atmospheric CO₂ levels, can significantly reshape the life cycle dynamics of agricultural pests and influence patterns of pesticide use.^17,18 This is because climate change appears to alter toxicokinetic and toxicodynamic characteristics in pests, increasing detoxification and reducing pesticide bioavailability at target sites.^19,20 Extreme weather events such as heat waves, drought, or flooding, may periodically lead to unexpected or more extensive pesticide use to cope with acute threats to crops and livestock, though exact effects may be unpredictable depending on timing or counter active effects on the pesticide lifecycle.^21,22 Among the most significant impacts are the expansion of pest geographic ranges, increased overwintering survival, and a higher prevalence of invasive species and vector-borne diseases.¹⁷ Furthermore, increasing use of pesticides may lead to resistance, necessitating the use of more pesticides and/or combinations of pesticides that results in higher exposure for farmers and laborers, and increased levels in drinking water and food sources. Together, these factors may lead to greater reliance on chemical pest control and increased risks of human occupational and environmental exposures. In other words, emerging environmental threats are directly linked to the increased use of pesticides by the agricultural, public, and private sectors, resulting in large-scale contamination of homes, workplaces, air, water, and foods, thereby raising exposure levels and associated health risks among the general population and patients (Figure 1).

Fig 1.

Climate Change, Pesticide Use, and Environmental Health Impacts

In recent years, epidemiological studies have investigated associations between pesticide exposure and autoimmune rheumatic diseases. However, little is known about the potential role of pesticides in other inflammatory rheumatic diseases. In this context, the aim of this scoping review is to synthesize both epidemiological and mechanistic evidence of pesticide effects on rheumatic diseases, identify research gaps, and highlight potential implications for health professionals and public policy, and the need for adaptive strategies in the face of potential increasing exposures related to shifts in weather patterns and extremes.

History

Early epidemiological studies suggested a potential association between pesticide exposure and immune dysregulation, evidenced by the presence of specific autoantibodies, altered lymphocyte subset mitogenic responses, and changes in cytokine production amongst agricultural and industrial workers.^23–27 These immunological alterations may be linked to immunosuppression, potentially contributing to cancer development, or to immunostimulation, possibly playing a role in the onset of autoimmune diseases, thereby providing biological plausibility for the epidemiological findings.^28,29 In this context, immune-mediated rheumatic diseases, such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), have been considered potential outcomes of chronic immune dysregulation induced by pesticide exposure.^30,31 However, the role of pesticides in the etiology and progression of rheumatic diseases remains poorly understood and underexplored.

Definitions

Pesticides:

Chemicals utilized to control, repel, or eradicate pests in agriculture, vector control, and urban environments. This category also includes complex mixtures and persistent organic pollutants resulting from such applications.

Rheumatic Diseases:

A diverse group of conditions characterized by inflammation and degeneration affecting joints, muscles, and connective tissues. These include autoimmune conditions such as rheumatoid arthritis and lupus, as well as other inflammatory disorders.

Scoping review:

A scoping review is a type of research synthesis that aims to map the main findings and gaps in the literature on a broad topic. It is especially useful in emerging or complex fields, where studies may vary in design and outcomes. Unlike systematic reviews, it does not usually assess study quality but helps guide future research and policy.

Background

Environmental stressors may expand the geographic range and survival of agricultural pests, as well as the prevalence of invasive species.¹⁷ These changes may lead to increased pesticide use and, consequently, greater human exposure to these chemicals. The literature suggests increasing interest in the potential role of pesticides in developing rheumatic diseases, particularly those of autoimmune origin.²⁸ However, assessing the extent of existing knowledge across both epidemiological and mechanistic domains is essential to better understand this issue and provide informed guidance for clinical practice and public health policy. A broader examination of rheumatic diseases beyond the most frequently studied conditions is also necessary, given the shared pathophysiological mechanisms through which pesticides may exert their effects. In this context, a scoping review is a valuable approach to synthesizing available evidence, identifying research gaps, and highlighting implications for health professionals and policymakers.

Methods

This scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. The article was guided by the Population, Concept, and Context framework, which defined the population as occupationally and environmentally exposed to pesticides, as well as experimental studies using in vivo and in vitro mammalian models exposed to pesticides. The concept focused on the association between pesticide exposure and rheumatic diseases, along with pesticide-related effects such as oxidative stress, dysbiosis, epigenetic alterations, and immunotoxicity in experimental studies. The context included clinical trials, cohort studies, case-control studies, cross-sectional studies, and mechanistic research.

Studies were included if they assessed the association between pesticide exposure and rheumatic diseases, as well as impacts on disease onset, severity, serological markers, outcomes, or patient care. Experimental studies involving in vivo and in vitro pesticide exposure in animals published in English were also eligible. Exclusion criteria included studies involving children or adolescents, expert opinions, narrative reviews, systematic reviews, meta-analyses, case reports, case series, other scoping reviews, comments, letters, conference abstracts, and studies for which the full text was unavailable.

A systematic search of PubMed, Scopus, and Embase databases was performed between March 26 and 27, 2025, covering publications from 2000 to 2025. Keyword combinations included controlled vocabulary such as Medical Subject Headings (MeSH) and Embase thesaurus terms (Emtree). Titles and abstracts were screened according to predefined inclusion and exclusion criteria with Rayyan software support. Figure 1 below presents the data from the initial database searches through to the final number of articles included in the article. A total of 1,345 records were identified through databases and registers. After removing 557 duplicates, 788 records remained for screening. Of these, 708 were excluded based on title and abstract screening, and 79 full-text reports were sought for retrieval, all of which were successfully retrieved and assessed for eligibility. Additionally, 19 records were identified through citation searching, of which 10 were eligible from citation searching. Among the 79 reports assessed from databases, 43 were excluded. Ultimately, 36 new studies were included in the article, along with 10 reports of newly included studies identified through citation searching. (Figure 2).

Fig. 2.

PRISMA flow diagram of selection of studies for inclusion in the scoping review

Results

Table 1 presents epidemiological evidence on rheumatoid arthritis (RA) and exposure to pesticides and agricultural work. Of the 15 studies, seven were cohort (Co) studies, while the remaining were split between four cross-sectional (CS) and three case-control (CC) designs. Exposure assessments included job-exposure matrices (JEM), questionnaires, national census data, death certificates, and pesticides biomarkers such as 3-phenoxybenzoic acid (3-PBA) and N, N-diethyl-m-toluamide carboxylic acid (DCBA). Some studies used gas chromatography-mass spectrometry (GC-MS) to identify pesticide metabolites. Outcome assessments were based on self-report, physician-confirmed diagnoses, confirmation of self-report based on use of disease-modifying antirheumatic drugs (DMARDs), hospital records, or national health data. Most studies used logistic regression for analysis, while others employed Cox proportional hazards models, log-binomial models, standardized incidence ratios (SIR), or the Mantel-Haenszel chi-square test. Overall, the findings suggest a positive association between farming occupations and increased RA risk. Some studies identified specific classes or pesticide active ingredients or measured levels of pesticide metabolites.

Table 1.

Epidemiological evidence linking rheumatoid arthritis (RA) to pesticide and agricultural exposures

Author	Study design; country	Exposure Assessment	Outcome Assessment	Statistical Methods	Clinical Associations
Lundberg et al. 199432	Co –population; Sweden	JEM	Incident RA; hospital discharge diagnoses	HRR	Male farmers had a marginally significant ↑ HRR (RR= 1.3, 95% CI 1.0–1.6) vs. the general population
Lee et al. 200233	PM – population; USA	Death certificate data	ICD-9 codes	M-H chi-square	Higher RA* mortality in male crop vs. livestock farmers (PMR= 134, 95% CI 112–160)
Olsson et al. 200434	CC – population-based; Sweden	Quest.	Recent RA cases	LR	Odds of RA in farmers (OR= 2.4, 95% CI 1.1–5.2) and farm workers (OR= 2.2, 95% CI 1.3–3.5)
De Roos et al. 200535	CC – spouses of farmers; USA	Quest.	Self-reported RA cases validated by medical records.	LR	Non-significant association between lindane use and RA
Gold et al. 200736	CC – population; USA	Death certificate data	ICD-9 code, underlying or contributing	LR	Farming occupations were associated with ↑ RA mortality (OR= 1.3, 95% CI 1.22–1.39)
Lee et al. 200737	CS –population; USA	GC/MS	Prevalent self-reported RA	LR	RA was not significantly associated with OCP insecticides
Li et al. 200838	Co – population; Sweden	Occupational status from census data	RA via hospital register	SIRs	Farmers showed a slight risk of RA (SIR= 1.1, 95% CI 1.0–1.1)
Parks et al. 201139	Co – post-menopausal women; USA	Quest.	Incident self-reported RA/SLE confirmed by DMARDs use	Cox	Personal insecticide use was associated with ↑ RA/SLE risk, with higher frequency (HR= 2.0, 95% CI 1.2–3.6) and longer duration (HR= 1.9, 95% CI 1.2–3.2)
Parks et al. 201640	Co – women; USA	Quest.	Incident self-reported RA confirmed by DMARDs use	LR	Women with RA had ↑ associations for maneb/mancozeb (OR= 3.3, 95% CI 1.5–7.1) and glyphosate (OR= 1.4, 95% CI 1.0–2.1)
Koureas et al. 201741	CS – pesticide sprayers; Greece	Quest., OPP via GC-MS	Prevalent self-reported RA	LR	RA was associated with ↑ exposure to OPP (OR= 6.5, 95% CI 1.0–45.4) and guanidines (OR= 16.2, 95% CI 1.6–165.9)
Meyer et al. 20178	Co – farmers; USA	Quest.	Incident RA self-reported, confirmed by validation or DMARD use	LR	Incident RA was associated with ever use of fonofos (OR= 1.7, 95% CI 1.2–2.4), carbaryl (OR= 1.5, 95% CI 1.0–2.2), and chlorimuron ethyl (OR 1.4, 95% CI 1.0–2.1)
Parks et al. 201742	Co – women; USA	Quest.	Prevalent self-reported RA confirmed by DMARDs use	LR	RA risk ↑ with childhood-only farm residence and personal pesticide exposure on crops (OR= 1.8, 95% CI 1.1–2.9) or livestock (OR= 2.0, 95% CI 1.2–3.3)
Guo et al. 202343	CS – population; USA	3-PBA levels (method not reported)	Prevalent self-reported RA	LR, RCS	Significant association of RA with highest vs. lowest 3-PBA levels in subgroups such as low education (OR 2.2, 95% CI 1.1–4.9)
Parks et al. 20249	Co – farmers >65 years; USA	Quest.	Incident RA based on Medicare claims	LB models	RA was associated with the use of 9 pesticides, with the strongest associations for malathion (RR 1.8, 95% CI 1.1–2.7) and metolachlor (RR 1.6, 95% CI 1.1–2.2)
Ly et al. 202444	CS – population; USA	DCBA, (DEET metabolite) via HPLC-MS/MS	Prevalent self-reported arthritis, RA, OA	LR, RCS	Higher DCBA levels associated with ↓ RA (OR= 0.6, 95% CI 0.5–0.9)

Abbreviation: Co, Cohort; PM, Proportional mortality; CC, Case-control; CS, Cross-sectional; RA, rheumatoid arthritis; OA, osteoarthritis; OCP, Organochlorine Pesticides; DMARD, disease modifying anti-rheumatic drugs; DCBA, 3-(diethylcarbamoyl)benzoic acid; DEET, N,N-diethyl-meta-toluamide; OPP, Organophosphate pesticides; M-H, Mantel-Haenszel; HRR, Hospitalization Relative Risk; LR, Logistic regression; SIR, Standardized Incidence Ratio; Cox, Cox proportional hazards model; LB, Log-binomial models; RCS, Restricted cubic spline; HPLC-MS/MS, high-performance liquid chromatography-tandem mass spectrometry; GC-MS, Gas Chromatography-Mass Spectrometry. ↑ Increased; ↓Decreased.

^*RA and other polyarthropathies

Table 2 presents epidemiological evidence linking SLE to pesticides and agricultural exposures. Of the 10 studies, four were CC, three were Co, and three were CS studies. Exposure to pesticides was primarily assessed through questionnaires. A smaller number of studies employed biomonitoring techniques such as GC-MS/MS or gas chromatography-electron capture detection (GC-ECD) to measure specific OCP levels. Outcome assessment varied, including self-reported physician diagnoses, clinical evaluations confirmed by rheumatologists, confirmation of self-report based on DMARD use, biomarker analyses (e.g., ANA, anti-dsDNA, oxidative stress markers), and death certificate data. Logistic regression was the most used statistical method, often combined with other approaches such as Cox proportional hazards models, ROC curve analysis, and trend tests like the Cochran-Armitage. SLE was associated with pesticide use during childhood, personal insecticide use, and rural or farming-related exposures. Specific chemicals like hexachlorobenzene (HCB) and lindane were linked to increased disease activity and hematologic abnormalities.⁵⁰ However, a few studies reported no significant associations or identified protective associations with carbaryl exposure and childhood farm residence.⁵²

Table 2.

Epidemiological evidence linking systemic lupus erythematosus (SLE) to pesticide and agricultural exposures

Author	Study design; Country	Exposure Assessment	Outcome Assessment	Statistical Methods	Clinical Associations
Balluz et al. 200145	CC – community; USA	Quest.; OPP via GC-MS/MS; OCP via GC-ECD	Prevalent SLE confirmed by physicians	LR	No associations of SLE with OC and OPP metabolites
Cooper et al. 200446	CC – population; USA	In-person interview	SLE recently diagnosed by rheumatologists	LR	+ association of SLE with mixing pesticides (OR= 7.4, 95% CI 1.4, 40.0)
Gold et al. 200736	CC – population; USA	Death Certificates	ICD-9 code, underlying or contributing	LR	Non-significant + association between farming occupation and SLE mortality
Parks et al. 201139	Co – post-menopausal women; USA	Quest.	Self-reported incident RA and SLE cases via self-report	Cox	Personal insecticide use was associated with ↑ RA/SLE risk, with higher frequency (HR= 2.0, 95% CI 1.2–3.6) and longer duration (HR= 1.9, 95% CI 1.2–3.2)
Parks et al. 201647	Co – women; USA	Quest.	Self-reported prevalent SLE confirmed by DMARD use	LR	+ association of pesticide use during childhood farm residence with prevalent SLE (OR = 1.8; 95% CI 1.1–3.0 vs. neither)
Simoniello et al. 201748	CS – community; Argentina	Quest.	Prevalent SLE, hospital-based; Oxidative stress biomarkers	LR, ROC curve	SLE patients from rural areas exposed to pesticide mixtures had ↑ oxidative DNA damage compared to SLE urban residents (p = 0.011)
Gergianaki et al. 201849	CS - community; Greece	Self-report and history	Prevalent SLE diagnosed by rheumatologists; symptoms; severity	LR	Rural patients had more prevalent cutaneous/joint symptoms and greater disease severity (OR= 2.3, 95% CI 1.2–4.3)
Helmy et al. 202150	CS – community; Egypt	OCP via GC-MS/MS	Clinical diagnosed SLE; severity; ANA, anti-dsDNA	LR, linear regression	HCB linked to ↑ polycythemia. Lindane linked to cardiac issues (OR= 5.8, 1.1–29.9), ↓C (β= −0.29, −0.4 to −0.1), anemia (β= −0.3, −0.1 to −0.0), leukopenia (β= −0.2, −0.3 to 0.0)
Williams et al. 201951	CC – community; USA	Quest.	SLE cases via hospital; ANA-negative controls	LR, CA test	+ association of pesticide exposure with SLE, mostly urban African American women (OR= 2.2, 95% CI 1.3–3.9).
Parks et al. 202252	Co – farmers; USA	Quest.	Self-reported incident SLE/SS confirmed by medical records or DMARD use	LR, Cox	+ association metribuzin use with SLE/SS (HR= 5.3, 95%CI 2.2–12.9); - associations with carbaryl (HR= 0.6, 0.4–0.9), petroleum distillates (HR= 0.4, 0.2, 0.9)

Abbreviations: Co, Cohort; PM, Proportional mortality; CC, Case-control; CS. Cross-sectional; Quest., Questionnaire; SLE, Systemic Lupus Erythematosus; RA, Rheumatoid Arthritis; SS, Sjögren’s Syndrome; ANA, Antinuclear Antibodies; anti-dsDNA, Anti-double-stranded DNA antibodies; SLEDAI-2K, Systemic Lupus Erythematosus Disease Activity Index 2000; HCB, Hexachlorobenzene; OCP, Organochlorine Pesticides; GC-MS/MS, Gas Chromatography–Tandem Mass Spectrometry; GC-ECD, Gas Chromatography with Electron Capture Detector; C, complement; LR, Logistic regression; Cox, Cox proportional hazards model; CA test, Cochran-Armitage test; HR, Hazard ratio; positive association, +association; negative association, -association; ↑ Increased; ↓Decreased.

Few epidemiological studies have assessed the link between pesticide exposure or agricultural work and other autoimmune and inflammatory rheumatic diseases (Table 3), including systemic sclerosis (SSc), Sjogren’s syndrome (SjS), and ankylosing spondylitis (AS), and osteoarthritis (OA). Among the four studies focused on systemic sclerosis (SSc), two were case control, and one was cross-sectional. Exposure assessment commonly involved pesticide metabolites measures and questionnaires.^53,55 Outcome assessment ranged from medical records and clinical classifications (diffuse cutaneous Systemic Sclerosis = dcSSc; limited cutaneous Systemic Sclerosis = lcSSc) to detailed laboratory methods, including ELISA, immunofluorescence, immunoblotting, and cytokine profiling. Nailfold capillaroscopy and creatine kinase levels were also used to capture clinical features of SSc. Logistic regression was the statistical method that was most used. The results regarding the association between pesticide exposure and SSc were mixed. Some studies highlighted methodological limitations such as underreporting of pesticide exposure or lack of analysis on specific pesticide effects. Studies investigating pesticides and OA used cross-sectional designs, self-report diagnoses, and logistic regression. Different pesticide biomarkers were assessed, and higher exposure levels were consistently associated with increased odds or prevalence of OA.^57–59 Similarly, Lee et al. (2007)³⁷ found that OC pesticide levels were positively associated with arthritis in women. Very few studies have assessed the relationship between pesticide exposure and less common rheumatic diseases such as AS and SjS and these studies have resulted in inconsistent results (see Table 3).

Table 3.

Epidemiological evidence linking SSc, OA, AS, SjS to pesticide and agricultural exposures

Study	Study design; country	Outcomes	Exposure Assessment	Outcome Assessment	Statistical Methods	Clinical Associations
Lee et al. 200737	CS – population; USA	OA	OCP metabolites via GC/MS	Prevalent self-reported OA	LR	+ association with arthritis, but not OA with OCP
Gold et al. 200736	CC – population; USA	SSc	Death Certificates	ICD-9 code, underlying or contributing	LR	Farm occupation was not significantly associated with ↑ SSc mortality
Marie et al. 201453	CC – hospital patients; France	dcSSc; lcSSc; ANA, ACA, anti-Scl70	Quest.	Prevalent SSc diagnosed in 3 medical units, ELISA	-	No associations of SSc with general use pesticides
Shiue et al. 201554	CS – population; USA	AS	Pesticides metabolites (method not reported)	Abnormal AS by physical examination	Weighted LR, linear regression	There were no associations between AS and pesticides
Aguila et al. 202155	Co – hospital patients; Brazil	SSc subtypes, ANA, Anti-Scl70, ACA, anti-RNA	Quest.	IF, IB, CK, nailfold capillaroscopy	LR	Exposure to pesticides alone was not evaluated
Parks et al. 202252	Co – farmers; USA	SjS	Quest.	Incident cases via medical records or medication use	LR; Cox	Metribuzin was associated with ↑SLE/SS; Carbaryl and child farm residence associated with ↓risk
Galli et al. 202456	CS – hospital patients; France	SSc forms	JEM	Medical records, and antibody status	LR	No significant associations were found between pesticide exposure above or below the 50th percentile and no pesticide exposure
Liang et al. 202357	CS – population; USA	OA	3-PBA levels (method not reported)	OA self-reported	LR	Higher 3-PBA levels associated with ↑odds of OA
Liang et al. 202458	CS – population; USA	OA	Glyphosate via 2D-IC-MS/MS	OA self-reported physician diagnosis	LR; RCS	Higher glyphosate levels associated with ↑OA odds
Zhu et al. 202459	CS – population; USA	OA	OPP levels via GC-MS/MS	OA self-reported diagnosis	LR; RCS; BKMR regression	In ASCVD patients, DMP, DEP, OPP mixture exposures were linked to higher OA prevalence

Abbreviations: SSc, Systemic Sclerosis; dcSSc, Diffuse cutaneous Systemic Sclerosis; lcSSc, Limited cutaneous Systemic Sclerosis; SjS, Sjögren’s Syndrome; SLE, Systemic Lupus Erythematosus; RA, Rheumatoid Arthritis; OA, Osteoarthritis; AS, Ankylosing Spondylitis; ANA, Antinuclear Antibodies; ACA, Anti-centromere Antibodies; Anti-Scl70, Anti-topoisomerase I Antibodies; Anti-RNA pol III, Anti-RNA polymerase III Antibodies; IF, immunofluorescence; IB, immunoblotting; PBMCs, Peripheral Blood Mononuclear Cells; CK, creatine kinase; 3-PBA, 3-Phenoxybenzoic acid; HCH, Hexachlorocyclohexane; DDT, Dichlorodiphenyltrichloroethane; DMP, Dimethyl phosphate; DEP, Diethyl phosphate; OPP, Organophosphate pesticides; OCP, Organochlorine Pesticides; GC/MS, GC-MS/MS, Gas Chromatography coupled with (tandem) Mass Spectrometry; HPLC-MS/MS, High-Performance Liquid Chromatography coupled with tandem Mass Spectrometry; 2D-IC-MS/MS, two-dimensional ion chromatography, tandem mass spectrometry; RCS, Restricted cubic spline. ↑ Increased; ↓Decreased.

Nine studies evaluated associations between pesticide exposure or agricultural work and autoantibodies linked to rheumatic diseases (Table 4). Most studies focused on antinuclear antibodies (ANA), with a few assessing other markers such as anti-dsDNA, anti-CCP, anti-TPO. Exposure assessment varied, including questionnaires, interviews, and biomarker analysis (e.g., GC/MS, fat biopsy). Outcome assessments varied across studies and included laboratory-based techniques such as indirect immunofluorescence (primarily for ANA detection), ELISA, flow cytometry, and electrochemiluminescence assays. Some studies also used composite clinical indices (e.g., DAS28, MDHAQ) and self-reported survey or registry data for disease severity and symptoms. Most studies focused on serological autoantibodies relevant to rheumatic diseases, including ANA, anti-dsDNA, anti-CCP, anti-TPO. While some studies found positive associations between pesticide classes (e.g., OCP, carbamates, phenoxyacetic acids) and increased autoantibody levels, others reported no significant associations. A few studies noted compound-specific effects, such as ANA being inversely associated with bromoxynil and 2,4-D, and positively associated with trifluralin, fungicides, and certain farming tasks.

Table 4.

Epidemiological evidence linking pesticide exposure to autoantibodies

Study	Outcomes	Exposure Assessment	Outcome Assessment	Statistical Methods	Clinical Associations
McConnachie et al. 199260	ANA, anti-DNA, ASM	History, fat biopsy, chlordane levels	Flow cytometry	Student’s t test	Few individuals exposed to chlordane had autoantibodies. One showed high ANA and anti-DNA titers, and another had elevated ASM. There was no comparison between groups
Rosemberg et al. 199961	ANA	Quest.	IF	LR; Chi-square test	+ associations between carbamate, OCP, phenoxyacetic acid, 2,4D and ANA levels
Cooper et al. 200662	ANA	Structured interview	IF	LR	No significant associations between ANA and pesticides
Semchuk et al. 200763	ANA	Quest.; Bromoxynil via GC/MS	Indirect IF	LR; GEE	ANA was (−) associated with bromoxynil and 2,4D and + associated with trifluralin and fungicide
Cebecauer et al. 200964	ANA, TPO ab	DDE, DDT, HCB, HCH via GC/MS	IF, ECL	Yates’ chi-square test	ANA only or with TPO associated with high OCP levels
Dinse et al. 201665	ANA	Pesticide metabolites (method not reported)	IF	Lognormal regression models	No significant associations between ANA and pesticides
Parks et al. 201966	ANA, ENA, anti-dsDNA, anti-CCP, anti-TPO	Quest.	IF, ELISA, EIA	LR	+ associations of autoantibodies with methyl bromide, aldicarb, and OCP
Ebel et al. 202267	Anti-CCP, RF, RA severity in RA patients	Quest.	ELISA, NEPH, DAS28, MDHAQ scores, ILD	LR; linear regression	Pesticide was not associated with anti-CCP and RA severity
Santos et al. 202268	Anti-CCP, ANA levels	Quest.	ELISA	Linear regression	+ association of anti-CCP with mancozeb, paraquat, methomyl, and farming tasks; + associations of ANA with azoxystrobin and (−) with linuron

Abbreviations: ANA, antinuclear antibodies; anti-dsDNA, anti–double-stranded DNA antibodies; ASM, anti–smooth muscle antibodies; TPOab, anti–thyroid peroxidase antibodies; ENA, extractable nuclear antigens; anti-CCP, anti–cyclic citrullinated peptide antibodies; OCP, organochlorine pesticides; 2,4-D, 2,4-dichlorophenoxyacetic acid; GC/MS, gas chromatography–mass spectrometry; ELISA, enzyme-linked immunosorbent assay; EIA, enzyme immunoassay; IF, immunofluorescence; ECL, electrochemiluminescence; NEPH, nephelometry; DAS28, Disease Activity Score in 28 joints; MDHAQ, Multidimensional Health Assessment Questionnaire; ILD, interstitial lung disease; Quest., questionnaire; GEE, generalized estimating equations; LR, Logistic regression.

Experimental in vivo and in vitro studies are presented in Table 5. A series of experimental studies in lupus-prone (NZBxNZW) F1 mice suggest that chronic exposure to OCP can accelerate the onset and progression of SLE-like disease. Sobel et al. (2006)⁶⁹ showed that Chlordecone (Chlord.) exposure accelerated disease onset in genetically susceptible mice, as evidenced by increased levels of anti-ds-DNA and anti-chromatin antibodies. Wang et al. (2007)⁷⁰ found that Chlord. partially mimics estrogen’s immune effects by promoting germinal center B-cell survival, suggesting this as a key mechanism in SLE acceleration. In 2008, Wang and colleagues⁷¹ further suggested that Chlord. elevated proinflammatory cytokines and altered T-cell responses even after ovariectomy, indicating that its immunomodulatory effects extend beyond classical estrogenic pathways. Li et al. (2008)⁷² reported that chronic DDT exposure may exacerbate renal involvement in lupus without broadly activating the immune system, suggesting tissue-specific toxicity. Sobel (2005)¹⁴ showed that prolonged exposure to OCP combination led to accelerated lupus nephritis, characterized by increased proteinuria, elevated anti-dsDNA antibodies, and immune complex deposition in the kidneys. Finally, two ex-vivo studies investigated the immunological effects of OCP in patients with autoimmune diseases. Dar et al. (2012)⁷¹ found that chronic exposure to HCH and DDT in SLE patients was associated with altered T-cell subset distribution and cytokine profiles, suggesting a potential role in disease progression through immunomodulation. Alsulimani et al. (2025)⁷² observed that in vitro stimulation of PBMCs from SSc patients with HCH and DDT led to reduced immune regulation and increased pro-fibrotic cytokines, indicating possible involvement in disease activity and infection susceptibility. Collectively, these findings provide strong experimental evidence that long-term exposure to certain OCP may promote or worsen autoimmune processes characteristic of SLE, acting through distinct immunotoxic mechanisms that are not limited to estrogen mimicry.

Table 5.

Pesticides Accelerate Lupus-like Disease in Murine Models: Immunotoxic and Pathological Evidence

Study	Outcomes	Exposure Assessment	Outcome Assessment	Statistical Methods	Clinical Associations
Sobel et al. 200516	Anti-dsDNA, kidney immune complex - (NZBxNZW) F1 mice	Chronic Chlord., methoxychlor, DDT exposure	Proteinuria, BUN levels, ELISA, IHF	Kaplan-Meier, ANOVA, Kruskal-Wallis	OCP accelerates SLE-like disease in mice independent of classic estrogenic activity
Sobel et al. 200669	SLE accelerated onset in (NZBxNZW) F1 mice	Chronic Chlord. exposure via subcutaneous	Anti-dsDNA, anti-chromatin via ELISA	Kaplan-Meier, Logrank test for curve differences	Chlord. accelerates SLE only in lupus-prone strain
Wang et al. 200770	SLE accelerated onset in (NZBxNZW) F1 mice	Chronic Chlord. exposure via subcutaneous	B-cell markers, Apoptosis and proliferation assays, Splenic HS	ANOVA, Kruskal-Wallis test for histological scores	Chlord. mimics some but not all E2 immune effects; GC B-cell survival may be a shared key step in SLE acceleration
Wang et al. 200871	Accelerated onset of SLE in (NZBxNZW) F1 mice	Subcutaneous implantation post-ovariectomy	Flow cytometry, Luminex, apoptosis assay, T-cell proliferation	ANOVA, Gabriel’s comparison intervals, Levene’s test	Chlord. ↑ inflammatory cytokines and may promote autoimmunity via distinct T-cell pathways
Li et al. 200972	SLE activity, anti-DNA, IgG, cytokines	Chronic DDT exposure via subcutaneous	ELISA, Flow cytometry	ANOVA, Chi-square test, Kaplan-Meier	DDT may exacerbate renal involvement in lupus without immune activation
Dar et al. 201273	T-cell subsets, cytokines in SLE patients	Chronic HCH, SST measured by GLC	ELISA, Flow cytometry	Student’s T-test, ANOVA	HCH, DDT may alter T-cell subsets, cytokines that could lead SLE development or flare
Alsulimani et al. 20274	T cells response in vitro to OCP in blood of SSc patients	HCH, DDT via chrom.	Flow cytometry, ELISA, PBMCs stimulated HCH/DDT in vitro	ANOVA with Tukey’s post hoc test	OCP associated with ↓ immune regulation and ↑pro-fibrotic cytokines, suggesting a role in disease activity and infections

Abbreviation: SLE, Systemic lupus erythematosus; SSc, Systemic sclerosis; OCP, Organochlorine Pesticides; Chlord., Chlordecone; HCH, Hexachlorocyclohexane; DDT, Dichlorodiphenyltrichloroethane; SST, ΣDDT + ΣHCH (sum of selected OCPs); ELISA, Enzyme-linked immunosorbent assay; BUN, Blood urea nitrogen; GC, Germinal center; PBMCs, Peripheral blood mononuclear cells; GLC, Gas-liquid chromatography; Chrom., Chromatography; E2, Estradiol; ANOVA, Analysis of variance. IHF, immunohistofluorescence; Splenic HS, histological scoring of spleen morphology

Summary and Recommendations

Changes in rainfall patterns, the increase in heatwaves, and severe cold spells may affect agricultural productivity due to their varying impacts on agricultural pests, as well as urban pests that spread diseases to humans, both of which are managed through pesticide use.^75,16 These increasingly frequent events may alter pesticide use patterns, consequently changing both occupational and environmental human exposure. Given that pesticide exposure has been linked to chronic diseases and, in recent years, to autoimmune rheumatic diseases, this scoping review gathered existing literature on the role of pesticides in rheumatic diseases more broadly, including both epidemiological and experimental evidence. Literature on pesticides and rheumatic diseases is limited, with evidence mainly centered on RA and SLE, where studies commonly report positive associations with pesticide exposure or agricultural work. Some of these associations (reported in two studies) were related to disease severity, severity markers, and comorbidities in patients with SLE. Considering the limited number of studies and the heterogeneity in their epidemiological designs, caution is needed when interpreting these findings.⁷⁶ However, these findings reinforce the potential association between pesticide exposure, RA, and SLE.

Despite the inherent limitations of the studies, clinicians should remain attentive to the context of environmental or occupational exposure to these substances and consider precautionary recommendations, especially for patients or individuals with additional associated risk factors (e.g., affected family members, pre-existing autoantibodies or other known genetic or environmental risk factors). Taken together, under the precautionary principle, actions may be recommended to reduce exposures. Patients may be advised to find alternatives to residential use of chemical insecticides, such as essential oils and repellent plants, physical traps, and biodegradable, DEET-free products. For farmers or farm workers, this may include greater use of personal protective equipment, using filtered or bottled water, and in the general population, also consuming organic foods when possible (i.e., avoiding the ‘Dirty Dozen,’, the twelve most pesticide laden fruits and vegetable items as reported by the Environmental Working Group⁷⁷ and/or properly washing produce, especially if unable to purchase organic). In addition, limiting animal product consumption is key. A substantial proportion of pesticides are used on corn and soy to feed animals, which leads to soil and water pollution, bioaccumulation in animal products, and loss of biodiversity.^78,79 Notably, lower levels of pesticides were found in vegetarians compared to omnivores, which may have been partly attributable to the greater propensity of vegetarians to consume organic foods.⁸⁰

Research on other rheumatic diseases has been limited, so more studies are needed to evaluate potential effects on non-autoimmune arthritis, for example. More data are needed on pesticide effects on disease activity among existing patients, with detailed exposure histories on modifiable risk factors, and potential intervention studies (e.g., investigating the effects of reduced exposures). Longitudinal clinical cohorts should consider using both questionnaire-based assessments of current and past use in the context of a broader exposome approach, including biomarkers of current exposures (e.g., pesticides with short half-lives) or persistent pesticides such as the OCP. Additionally, considering that pesticide toxicity can be modulated by metabolic pathways and that genes such as CYP1A1 and PON1 may confer differential susceptibility,^81,82 along with the known genetic component of certain rheumatic diseases,^83,84 future studies should address gene-environment interactions (GxE) to better understand how pesticides may contribute to these diseases, either as risk factors or environmental triggers.

KEY POINTS.

• Epidemiological studies have focused on the role of pesticides in the development of autoimmune rheumatic diseases (e.g., rheumatoid arthritis, lupus), with limited research addressing other inflammatory rheumatic diseases.

• Mechanistic studies have predominantly explored autoimmune pathways, while key processes in non-autoimmune rheumatic diseases remain poorly examined.

• The roles of pesticides in exacerbation, progression or symptoms of rheumatic diseases remain largely unexplored.

• Shifts in weather patterns, such as extended growing seasons, or increasing frequency of storms and flooding, may influence pesticide use patterns, leading to potential increases in exposure level risks for pesticide-driven diseases.

Synopsis.

This article synthesizes epidemiological and mechanistic evidence linking pesticides to increased risk of rheumatic diseases and potential disease activity modulation. The critique also explores how climate-related changes in pesticide use may amplify health risks and needs for adaptation to emerging environmental threats, and summarizes unmet research needs and how to best address them.

Clinics Care Points.

• Recommend the use of personal protective equipment (PPE) for farmers and farm workers, especially those with additional risk factors (for example, family history of rheumatic diseases).

• Advise consumption of filtered or bottled water to reduce potential ingestion of environmental contaminants, such as pesticides residues.

• Encourage patients to consume organic foods, when possible, especially limiting non-organic produce listed in the “Dirty Dozen.”

• Promote proper washing of fruits and vegetables to reduce pesticide residues, such as soaking them in a solution containing two teaspoons of baking soda per quart of water.

• Encourage patients to minimize consumption of animal products, given that a substantial proportion of pesticides are used on crops for animal feed.

• Suggest non-chemical alternatives for residential pest control (e.g., essential oils, repellent plants, physical traps, biodegradable and DEET-free products).