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. 2026 Mar 8;46(11):3804–3813. doi: 10.1002/jat.70132

Health Biomarkers of Pesticide Exposure in Rural Populations of Santa Fe, Argentina: Oxidative Stress and Genotoxicity

María Priscila Dechiara 1, Carlina Leila Colussi 1,✉, Lucía Magdalena Odetti 1,2, Damián Marino 2,3, † , María Fernanda Simoniello 1
PMCID: PMC13628424  PMID: 41797357

ABSTRACT

The present study aimed to quantify pesticide residues in environmental matrices and plasma and to evaluate their potential effects on oxidative stress and DNA damage in rural populations of Santa Fe province. Soil and rainwater samples were collected, and biological samples and semistructured surveys were obtained from volunteers in three rural towns. Pesticide residues were analyzed using liquid and gas chromatography coupled with mass spectrometry. DNA damage was assessed by the comet assay (CA) and its modified version for oxidative lesions (ENDO sites), along with catalase (CAT) and superoxide dismutase (SOD) enzymatic activities and lipid peroxidation (TBARS). Results were compared with those from a control population in an urban setting. Pesticide residues were detected in 62% of blood samples, with significantly higher frequencies (p < 0.05) in rural participants compared to the control group, mirroring increases in oxidative and genotoxic biomarkers. Atrazine residues were found in 47% of rainwater samples from Santo Domingo, while glyphosate and its metabolite AMPA were present in 67% of soil samples from all towns studied. The detection of pesticide residues in both environmental and human samples supports the occurrence of concurrent exposure. The persistence of these compounds, their environmental mobility, and their potential to induce biological alterations highlight the need for preventive measures and health policies to reduce exposure risks in rural populations.

Keywords: environmental pollutants, public health, soil analysis, toxicology, water pollution

Short abstract

The study assessed pesticide residues in soil, rainwater, and plasma, and evaluated their effects on oxidative stress and DNA damage in rural populations of Santa Fe. Researchers detected pesticides in 62% of blood samples and observed higher frequencies as well as increased oxidative and genotoxic biomarkers compared to an urban control group. They found atrazine in rainwater and identified glyphosate and AMPA in soils from all towns. These findings indicate that the rural population faces simultaneous environmental and biological exposure, underscoring the need for preventive measures.

1. Introduction

Over the past 50 years, South America has become the dominant global producer of soybeans. In the 2019/2020 crop year, Brazil and Argentina produced 176 million tons, accounting for over half of the world's production. These two countries alone also contributed to 57% of all soybeans exported globally (Klein and Vidal Luna 2021). In Argentina's humid Pampas, the area dedicated to soybean cultivation has expanded significantly over recent decades, increasing overall grain production (Stølen 2023). The most notable land‐use changes occurred in large cattle estates, historically used for fattening livestock, which underwent rapid modernization during the 1990s. These estates converted pastures into soybean fields and adopted new technological packages (Stølen 2023). In terms of crop management, Argentina is known for its high annual consumption of pesticides, produced both domestically and through imports. Herbicides make up the largest proportion at 43%, followed by insecticides and fungicides, while acaricides, nematicides, molluscicides, growth regulators, and others account for less than 14% (Ferraro et al. 2020; Montoya et al. 2022).

Santa Fe province was the birthplace of the first organized agricultural colony in the country. The vast majority of the territory is rural, although there are heavily urbanized areas. Approximately 53% of the population is concentrated in two cities, Santa Fe and Rosario, where industrial, commercial, and service complexes are located. The province contributes approximately 8.3% to the national gross domestic product (GDP) and generates 23.9% of the total value of national exportable production. It is the leading province for oilseed production and the second‐largest producer of cereals. Notably, 75% of Argentina's cereal exports and 58% of its oilseeds are shipped from Santa Fe ports. Cereal and oilseed production accounts for more than 80% of the area planted in the province. Among primary activities, soybeans constitute 60% of grain production, followed by wheat, corn, sunflowers, and sorghum (INTA 2025). In this context, Candioti, Santo Domingo, and La Pelada—towns in the counties of La Capital and Las Colonias—have seen their planted areas increase over the past 25 years (INTA 2025).

In response to growing concern about the environmental and health consequences of intensive agriculture, an increasing number of studies in Argentina have adopted integrated monitoring strategies that include both environmental sampling and human biomonitoring (Mac Loughlin et al. 2022; Urseler et al. 2022). Human biomonitoring involves the direct measurement of chemical substances, their metabolites, or biological markers in human specimens (such as blood, urine, or hair) and provides a reliable estimate of internal exposure (Ladeira and Smajdova 2017). Combined with environmental sampling—such as pesticide detection in soil, water, or air—this approach offers a more comprehensive understanding of exposure routes and potential risks to both ecosystems and human populations.

Given the significant socio‐environmental impacts of agriculture in this region, recent studies in Argentina have investigated herbicides and fungicides levels (for instance, glyphosate (GLY)—and its metabolite aminomethylphosphonic acid (AMPA)—and atrazine (ATZ), among others), in various environmental matrices, including surface water (Mac Loughlin et al. 2022), groundwater (Urseler et al. 2022), soil (Bernasconi et al. 2021), and even fruits and vegetables for human consumption (Mac Loughlin et al. 2018). Furthermore, the detrimental effects of pesticide exposure on nontarget organisms have been explored in the same region, focusing on zebrafish (Bianchi et al. 2024), caimans (Odetti et al. 2023), turtles (Boccioni et al. 2024), and adult and tadpole amphibians (Martinuzzi et al. 2020). Research on pesticide residues in human blood samples and their effects on health has also been conducted. For instance, Simoniello et al. (2008, 2010) and Porcel de Peralta et al. (2011) have demonstrated the importance of blood genotoxic biomarkers in rural workers from central‐northern Santa Fe. More recently, Colussi et al. (2024) detected organochlorine (OC) and atrazine residues in postpartum women from the same province.

In this context, along with the environmental conditions and the potential health risks associated with pesticide use, there is a need to generate updated data on both environmental contamination and human exposure in rural populations of the region. Therefore, the objective of this study was to evaluate pesticide concentrations in different environmental matrices (specifically soil and rainwater) and to assess human exposure by measuring these compounds in plasma samples, as well as by analyzing oxidative stress and genotoxic biomarkers in residents of three rural towns in the Pampa region of Santa Fe province.

2. Materials and Methods

2.1. Study Population

A cross‐sectional study was carried out in Santa Fe province, Argentina, involving residents of three rural towns (Candioti, La Pelada, and Santo Domingo) located in agricultural areas dominated by soybean, livestock, and dairy production. Urban residents from Santa Fe city served as the control group. Eligible individuals were adults (≥ 18 years) living in the study area. Exclusion criteria included pregnancy, breastfeeding, or inability to consent. A face‐to‐face questionnaire was administered to gather demographic, lifestyle, occupational, health, and pesticide‐related risk awareness information, using a tool already developed in the laboratory.

All participants signed informed consent, following the Declaration of Helsinki. Introductory meetings were held in each town to explain the study, eligibility criteria, and how results would be communicated. Participants received an information sheet with contact details, and sample collection appointments were arranged at local health centers.

2.2. Human Biological Sampling

Peripheral blood samples (10 mL) were obtained by certified healthcare professionals at local health centers. Blood was collected in heparinized tubes and divided into aliquots for multiple analyses. One aliquot was used for genotoxicity assays, including the standard and enzyme‐modified comet assay (ENDO Sites). Another aliquot was used to isolate erythrocytes, which were washed three times in 0.9% NaCl solution and stored at −80°C for oxidative stress biomarker analysis: catalase (CAT), superoxide dismutase (SOD), and lipid peroxidation (LPO). Additional plasma aliquots were reserved for pesticide residue analysis.

2.2.1. Oxidative and Genotoxic Biomarkers

2.2.1.1. Alkaline Comet Assay

The alkaline comet assay (CA) was performed based on the protocol by Singh et al. (1988), with minor modifications following Simoniello et al. (2008) cell viability was assessed using acridine orange and ethidium bromide. Each assay included negative and positive internal controls (50 μM H2O2). Briefly, 50 μL of heparinized blood was mixed with 200 μL of 1% low‐melting‐point agarose and layered on two precoated microscope slides (1% normal‐melting‐point agarose). Coverslips were placed on the slide, and cooled for 10 min. Slides were then immersed overnight in a lysis buffer (2.5 M NaCl, 100 mM EDTA, 10 mM Tris–HCl, 1% Triton X‐100, 10% dimethyl sulfoxide, pH 10) at 4°C in the dark. DNA unwinding was performed in alkaline buffer (300 mM NaOH, 1 mM EDTA, pH > 13) for 20 min, followed by electrophoresis under the same buffer at 0.7 V/cm for 20 min. Slides were neutralized in 0.4 M Tris–HCl (pH 7.5) and stained with 25 μL of acridine orange (2 μg/μL). DNA damage was visually scored in 100 randomly selected nucleoids per slide using a four‐class scale (10 no damage; 4 = severe damage). The Damage Index Comet Assay (DICA) was calculated as: DICA = n 1 + 2n 2 + 3n 3 + 4n 4, where n 1–n 4 correspond to the number of cells in each damage class. Total DICA score ranged from 100 to 400 arbitrary units.

2.2.1.2. Comet Assay Modified for the Detection of Oxidized Bases

After lysis, slides were rinsed with enzyme buffer (40 mM HEPES, 0.1 M KCl, 0.5 mM EDTA, 0.2 mg/mL BSA, pH 8.0). Then, 50 μL of endonuclease III solution or buffer alone (for control slides) was applied, and covered with a coverslip. Slides were incubated at 37°C for 30 min, after which CA procedures were repeated as described above. The presence of oxidized pyrimidines was estimated by subtracting the DICA values of untreated slides from those incubated with the enzyme, yielding the number of ENDO Sites (arbitrary units).

2.2.1.3. Oxidative Stress Biomarkers: Catalase Activity in Erythrocytes, Superoxide Dismutase, and Lipid Peroxidation in Erythrocytes (TBARS)

Erythrocytes were lysed (1:100 dilution) in ice‐cold ultrapure water. CAT activity was assessed spectrophotometrically by monitoring the decrease in H2O2 absorbance at 240 nm every 15 s for 3 min (Beutler 1975). One CAT unit was defined as the amount of enzyme that degrades 1 mol of H2O2 per minute per gram of hemoglobin, with results expressed in kU/g Hb. SOD activity (% inhibition) was measured using a commercial kit (Sigma, 191‐160‐1 KT), and reported as % inhibition. Readings were taken at 440 nm using a Rayto plate reader. Lipid peroxidation was evaluated by TBARS assay, which measures malondialdehyde (MDA) through its reaction with thiobarbituric acid (TBA), following the method of Buege and Aust (1978) with modifications. Lysed erythrocytes (1:4 dilution) were incubated with reaction solution (15% w/v TCA, 0.375% w/v TBA, 0.25 M HCl), and 4% BHT to prevent iron‐induced peroxidation (Paravani et al. 2019). Samples were heated at 95°C for 45 min, cooled, and centrifuged at 12,000 g for 10 min at 4°C. Absorbance was measured at 535 nm, and MDA concentration was calculated using an extinction coefficient of 1.56 × 105 M−1 cm−1. Results were expressed as nmol MDA/g Hb. Iron‐free tubes and deionized water were used to minimize contamination.

2.2.2. Exposure Biomarkers

2.2.2.1. Determination of Pesticides in Plasma

For the plasma samples, the following compounds were analyzed: OC insecticides: DDT metabolites [1,1‐dichloro‐2,2‐bis(4‐chlorophenyl)‐ethylene (pp‐DDE), 1‐chloro‐4‐(2,2‐dichloro‐1‐(2‐chlorophenyl)vinyl)‐benzene (op‐DDE), 1,1‐dichloro‐2,2‐bis(4‐chlorophenyl)‐ethane (pp‐DDD), 1,1,1‐trichloro‐2,2‐bis(4‐chlorophenyl)‐ethane (pp‐DDT), 1‐chloro‐2‐(2,2,2‐trichloro‐1‐(4‐chlorophenyl)ethyl)‐benzene (op‐DDT)], heptachlor (HEP), heptachlor epoxide (HEPTE), methoxychlor (MET), γ‐Lindane (ϒ‐HCH), dieldrin (DIE), and endosulfan (END); organophosphate (OP) insecticide: methyl parathion (METP); pyrethroid insecticides: cypermethrin (CYP), λ‐cyhalothrin (LAMB), permethrin (PER), and bifenthrin (BIF); organic compound, adjuvant‐synergist: piperonyl butoxide (BUTOX); fungicides: epoxiconazole (EPOX), tebuconazole (TEB), and azoxystrobin (AZOX) (Supplementary Table S1 and Supplementary Table S2).

2.2.2.2. Analytical Procedure and Instrumental Analysis

Sample preparation was adapted according to matrix type. For human plasma, a liquid–liquid extraction with hexane at acidic pH was performed, using D5‐ATZ as an internal standard (Liu and Pleil 2002). For rainwater, derivatization with FMOC‐Cl was applied for glyphosate and AMPA analysis, followed by purification and filtration (Goodwin et al. 2003), for atrazine, direct injection was used. Finally, for soil, glyphosate was extracted using alkaline buffer and sonication, followed by FMOC‐Cl derivatization.

All analytes were quantified using chromatography coupled to mass spectrometry. For plasma and rainwater atrazine, gas chromatography–mass spectrometry (GC–MS) was used (Perkin Elmer Clarus 580 with Clarus SQ 8S mass detector), applying splitless injection at 250°C, helium as carrier gas at 1 mL/min, and a temperature ramp from 80°C to 300°C. Ionization was carried out by electron impact (70 eV), detection in SIM mode, and quantification by calibration curves using internal standards.

For glyphosate and AMPA in rainwater and soil, liquid chromatography coupled to mass spectrometry (HPLC‐MS) was employed using the ChemStation software. Chromatographic conditions and ion monitoring were optimized according to analyte properties and matrix type, following external calibration with treated standards and internal quality controls with isotopically labeled tracers (15C‐15N‐GLY and D5‐ATZ) (Feng and Thompson 1990).

2.3. Rainwater and Soil Samples

2.3.1. Sampling

Rainwater was collected during spring–summer in Santo Domingo and in summer in La Pelada and Candioti. Residents, with support from local health units, gathered 100‐mL samples in sterile containers from the start to the end of each rain event. A total of 157 samples were obtained: 96 from Candioti, 30 from La Pelada, and 31 from Santo Domingo. All samples followed APHA (2007) guidelines for pesticide analysis and were stored at −20°C.

Soil samples were taken from the top 5 cm (without vegetation) over a 30 × 30‐cm area at four cardinal points of each town, the main square, and nearby crop fields. Samples were homogenized, and 500‐g subsamples were analyzed.

2.4. Statistical Methods

Data set normality was evaluated using the Kolmogorov Smirnov test, and parametric (t‐test, Dunnet test, or ANOVA) or nonparametric (Kruskal–Wallis or Mann–Whitney U test) tests were used to compare different groups based on the parameters analyzed and confounding factors (sex, age, habits, residence time, distance from homes to the crops fields, work activity, consumption of medications, and illness). Categorical variables were summarized as frequencies and percentages, while continuous ones were presented as the mean and standard error or dichotomized. Considering pesticide quantification, median, interquartile range (IQR), and frequency of appearance of each compound were reported. The SPSS 17.0 for Windows was used, with a significance level of 0.05.

3. Results

3.1. Participant Characteristics

In this study, 145 adults (≥ 18 years), from three rural towns and from Santa Fe City (as a control group) participated. Their sociodemographic characteristics, lifestyle habits, work activities, and health parameters are shown in Table 1.

TABLE 1.

Sociodemographic, lifestyle habits, work activities, and health parameters data in participants from Santa Fe Province, Argentina.

Variables Santa Fe, n = 30 (control group) Candioti, n = 35 La Pelada, n = 37 Santo Domingo, n = 43
Sociodemographic
• Age (years), mean ± SD 38 ± 14 45 ± 13 42 ± 16 48 ± 15
• Sex, n (%)
○ Female 14 (47) 26 (74) 24 (65) 22 (51)
○ Male 16 (53) 9 (26) 13 (35) 21 (49)
• Educational level, n (%)
○ Analphabet 0 (0) 8 (23) 4 (11) 0 (0)
○ Primary school 8 (27) 18 (52) 18 (49) 24 (56)
○ High school 16 (53) 5 (14) 11 (29) 11 (25)
○ College/university school 6 (20) 4 (11) 4 (11) 8 (19)
• Living at 0–200 m from crop fields, % 0 71 82 91
Lifestyle habits, n (%)
• Smoking 7 (23) 6 (17) 8 (22) 8 (19)
• Alcohol consumption 5 (17) 4 (11) 5 (14) 4 (9)
• Medicament consumption 12 (40)

20 (57)

 17 (46) 20 (47)
Work activity, n (%)
• Rural 0 (0) 6 (17) 15 (34) 7 (19)
• Non rural 30 (100) 29 (83) 28 (66) 30 (81)
Health parameters
• Health control in health system, n (%)
○ Public health 5 (17) 15 (43) 7 (19) 20 (46)
○ Private health 18 (60) 3 (8) 10 (27) 8 (19)
○ Both 1 (3) 2 (6) 1 (3) 0 (0)
○ None 6 (20) 15 (43) 19 (51) 15 (35)
• Previous pathologies, n (%) 14 (47) 26 (74) 20 (54) 22 (51)
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Regarding proximity to cultivated fields, 68% of the surveyed population in Santo Domingo and 82% in La Pelada live within 500 m of agricultural land, while in Candioti, 71% reside between 0 and 200 m from these fields.

3.2. Oxidative and Genotoxic Biomarkers

A comparative analysis across the three rural locations showed significant differences in DICA values compared to the control group (p ≤ 0.002). Similarly, for ENDO sites, significant differences were observed in all three localities compared to the control group (p ≤ 0.002; Figure 1). Regarding oxidative parameters, participants from rural localities showed significantly higher values of CAT and SOD, compared to the control group. For TBARS, significant differences were detected in Santo Domingo and La Pelada compared to the control group. Additionally, CAT values were significantly higher in La Pelada compared to Santo Domingo (p = 0.001) and Candioti (p = 0.002). For TBARS and CA, significant differences were observed between La Pelada and Santo Domingo (p = 0.0001) and between Candioti and Santo Domingo (p ≤ 0.0004), while no significant differences were found between Candioti and La Pelada (p ≥ 0.15). See Figure 1. Smoking habits, alcohol consumption, age, and medication use were analyzed as potential confounding factors, but no significant differences were found for any of these variables in relation to the biomarkers analyzed (p > 0.05). Regarding the residence time, modified CA (ENDO Sites) showed significant differences in La Pelada town (p = 0.02), with higher values observed in participants with longer residence times. In the other localities, no statistically conclusive differences were found related to residence time. For work activity related to agricultural tasks, statistically significant differences in SOD values were observed in Santo Domingo (p = 0.03) and Candioti (p = 0.04), while no significant differences were found in La Pelada (p = 0.24). No significant differences were observed for CAT in any of the towns analyzed (p > 0.05 in all cases).

FIGURE 1.

FIGURE 1

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Genotoxic and oxidative stress biomarkers measured in the control group and in populations from Candioti, La Pelada, and Santo Domingo. (A) DNA damage index assessed by the comet assay (DICA and ENDO parameters). (B) Catalase activity (CAT, kU·g⁻¹ Hb). (C) Superoxide dismutase activity (SOD, % inhibition). (D) Lipid peroxidation measured as thiobarbituric acid reactive substances (TBARS, nmol·g⁻¹ Hb). Bars represent mean values ± standard error of the mean (SEM). Sample sizes for each group are indicated below the bars. Statistical comparisons were performed against the control group using appropriate parametric or nonparametric tests according to data distribution. *p < 0.05 and **p ≤ 0.002 versus control group.

3.3. Pesticides in Blood Samples

A total of 77 blood samples from the three rural populations were analyzed, of which 48 (62%) contained at least one detectable pesticide residue. Figure 2 provides an overview of the detection patterns and concentration levels of the most frequently identified pesticides in plasma samples, whereas compounds detected only one or not all are not presented.

FIGURE 2.

FIGURE 2

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Pesticide residues detected in human blood samples. (A) Number of serum samples with detectable pesticide residues (n) for each compound. (B) Mean concentrations (± SD) detected in serum samples for the most frequently detected pesticides.

Particularly, in Candioti, 76.5% of the analyzed blood samples (26 out of 34) exhibited detectable pesticide residues. The most frequently detected pesticide was λ‐cyhalothrin (32.4%), followed by cypermethrin, pp‐DDD, and γ‐Lindane (8.8% each). In Santo Domingo, 77.8% of the samples (14 out of 18) tested positive for pesticides, with pp‐DDD detected in 44.4% of positive samples, azoxystrobin in 27.8%, and permethrin in 11.1%. In La Pelada, 32% of the analyzed samples (8 out of 25) were positive for pesticides; the most frequently detected compounds were pp‐DDD, pp‐DDE, and bifenthrin (12% each). In the control group, pesticide residues were detected in 21 out of 30 participants. The most frequently detected compound was pp‐DDE, present in 33.3% of these individuals.

3.4. Oxidative, Genotoxic, and Exposure Biomarkers and Distance From Crops

The quantification of pesticide residues in blood was compared with CA and modified CA values. No statistically significant differences were found (p > 0.05). Among the participants with pesticide residues detected in blood plasma, 94% lived within 0–500 m of cultivated fields. In Candioti, 88% of individuals with pesticide residues lived within 0–200 m from cultivated fields; 54% of these individuals had DICA values above the median of the data (DICA > 183). In La Pelada, all individuals with detectable pesticide residues (100%) lived within 0–500 m from agricultural fields. Among them, 25% had DICA values above the median (DICA > 171). In Santo Domingo, 78% of individuals with pesticide residues lived within 0–500 m of cultivated fields; 43% of these individuals had DICA values above the median (DICA > 200). When examining distance from homes to cultivated fields, statistically significant differences were found for TBARS values in Santo Domingo (p = 0.03), with higher values observed in individuals living closer to cultivated areas.

3.5. Environmental Analysis

A total of 157 rainwater samples were collected, with no detectable glyphosate or AMPA (LOD = 0.50 μg/L). Atrazine was present in 47% of samples, with a median of 0.02 μg/L (IQR < LOD = 0.34).

Thirty‐one soil samples were analyzed from the three towns. Glyphosate and AMPA were detected in 67% of them, with median concentrations of 18.0 μg/kg (IQR = 9.7–20.1) and 40.9 μg/kg (IQR = 6.6–105.8), respectively. No significant differences were found between locations. However, local hotspots were identified. Candioti: Highest levels near the urban perimeter in a livestock field (20.0 μg/kg glyphosate; 144.0 μg/kg AMPA). Other high values occurred in the cemetery (18.8 μg/kg) and main square (17.8 μg/kg). Santo Domingo: The highest glyphosate level (27.3 μg/kg) occurred in an undeveloped lot of the Sports Club; AMPA peaked near a cornfield (132.2 μg/kg). La Pelada: The highest glyphosate concentration was at the Rural Hospital yard (21.3 μg/kg), and AMPA peaked in the main square (236.9 μg/kg).

4. Discussion

Participants showed a broad age range and had long‐term residence in their communities, consistent with the population structure of both departments (IPEC 2010). This stability in residency enhances the relevance of biomonitoring data, as long‐term environmental exposure can be more accurately inferred.

Genotoxicity biomarkers are essential tools in cancer epidemiology because they enable early detection of environmentally induced effects and are widely applied in human biomonitoring (Ladeira and Smajdova 2017). Because DNA damage and insufficient repair mechanisms contribute to the development of cancer and other chronic diseases, the CA provides valuable information on early genetic alterations that may indicate future risk (Milić et al. 2021).

In our study, both the CA and modified CA test revealed significant differences between the three rural towns and the urban control group. Santo Domingo exhibited the highest levels of genetic damage, likely reflecting oxidative DNA impairment. Comparable findings were reported by Verzeñassi et al. (2023) in San Salvador (Entre Ríos) and by Avila‐Vazquez et al. (2018) in Monte Maíz (Córdoba), where elevated tumor incidence was linked to compromised oxidative damage repair. Our results align with previous studies documenting similar patterns of genotoxicity in agricultural environments (Colussi et al. 2024).

Oxidative stress alterations are a well‐recognized mechanism of pesticide toxicity (Ighodaro and Akinloye 2018), and biomarkers of effect play a critical role in identifying populations at increased risk and guiding preventive actions (Halliwell 2002). In this study, antioxidant responses and lipid peroxidation levels varied by locality: La Pelada exhibited higher CAT activity accompanied by lower TBARS and modified CA values, suggesting more effective antioxidant compensation, whereas Santo Domingo revealed the greatest oxidative damage.

No significant associations emerged between biomarkers and individual factors such as smoking, alcohol consumption, age, or medication use. This supports the interpretation that the observed biological alterations may be more closely related to pesticide exposure than to personal characteristics. These findings align with previous research from the same region (Simoniello et al. 2008; Simoniello et al. 2010) and with reports of increased TBARS and antioxidant enzyme activity in pesticide‐exposed populations (Kisby et al. 2009; Ledda et al. 2021). Pesticide residues have previously been detected in multiple human biological matrices, including blood (Colussi et al. 2024), urine (Chen et al. 2022), breast milk (Figueiredo et al. 2024), and umbilical cord (Zhang et al. 2024). These compounds act as endocrine disruptors, capable of inhibiting enzymes, altering immune function, and promoting carcinogenic processes (Zhang et al. 2024).

In our study, λ‐cyhalothrin and the DDT metabolite pp‐DDD were the most frequently identified analytes in blood. The persistence of DDT—despite its ban in the 1990s—reflects its chemical stability and bioaccumulative nature, consistent with reports in Argentina (Stroia et al. 2019).

λ‐Cyhalothrin is commonly used in soybean production (Pautasso et al. 2023) and vector control programs (Kambou et al. 2024). Multiple analytes were detected in blood samples, suggesting potential health implications. Prenatal exposure to pyrethroids has been associated with language delays in children (Chen et al. 2022), while other studies report adverse effects on sperm parameters (Akhigbe et al. 2024). Sex‐related biological differences may further modulate vulnerability through distinct occupational and domestic exposure patterns (Mergler 2012). Recent research, including Medley et al. (2024), highlights sex‐specific effects of pesticide exposure on fetal growth and biomarker profile (Macheka et al. 2024). Considering that health impacts may emerge years after exposure, biomonitoring is essential to assess long‐term risks (Choi et al. 2015).

Most participants with detectable residues lived within 0–500 m of cultivated fields, and genetic damage was notably higher in Candioti and Santo Domingo. These observations parallel findings from Córdoba province, where residues were documented near storage areas and among horticultural workers (Eandi et al. 2021; Lucero et al. 2008).

Our results highlight the need for larger studies and for investigating additional mechanisms associated with chronic pesticide exposure. Biomarkers remain indispensable tools for epidemiological surveillance, and the detection of pesticides in both biological samples and environmental matrices underscores the importance of continued monitoring.

Given their mobility, pesticides can contaminate natural resources through processes such as runoff and leaching, contributing to long‐term health risks.

In this study, atrazine was detected in rainwater, consistent with seasonal corn cultivation (Pautasso et al. 2023). Its mobility explains its presence across diverse matrices (Urseler et al. 2022; Gagneten et al. 2023; Vera‐Candioti et al. 2021), and concentrations observed exceeded those previously reported by Alonso et al. (2018). Although atrazine use is restricted in Córdoba, it remains unregulated in other regions of Argentina. Glyphosate, the most widely used herbicide in the country, is recognized for its environmental persistence (Aparicio et al. 2018). Glyphosate and its metabolite AMPA were detected in soil samples, consistent with findings by Aparicio et al. (2018) and Avila‐Vazquez et al. (2021). Their absence in rainwater may be related to rapid degradation or strong soil adsorption (Maqueda et al. 2017), a pattern also observed internationally (Ore et al. 2023). The spatial distribution in our study suggests contamination from both direct application in public spaces and drift from nearby agricultural fields.

Finally, residues of OC pesticides have been reported in multiple regions of Argentina, including Buenos Aires province (Tombesi et al. 2018) and Patagonia (Miglioranza et al. 2013; Miglioranza et al. 2021). Vera‐Candioti et al. (2021) also detected similar compounds in groundwater from southern Santa Fe, geographically aligned with our study area.

This study has several limitations. Its cross‐sectional design prevents establishing causal relationships between pesticide exposure and oxidative or genotoxic outcomes. The sample size—particularly when stratified by locality or exposure—may have limited the statistical power to detect associations. Accordingly, the findings should be interpreted as exploratory and hypothesis‐generating, highlighting the need for larger‐scale studies to confirm and extend these results.

For certain pesticide groups (dieldrin, endosulfan, pyrethroids), only parent compounds were measured because validated methods and certified standards for their metabolites were not available in our laboratory. In addition, complete recovery data for all analytes and matrices (blood, rainwater, soil) could not be obtained. Although internal standards and quality controls were applied, full recovery validation was constrained by limited reference materials and laboratory resources.

Despite these limitations, the results raise important public health concerns and reinforce the need for surveillance programs monitoring pesticide residues in environmental and human samples, as well as preventive policies to reduce exposure in agricultural communities.

5. Conclusions

This biomonitoring study represents an interdisciplinary effort combining environmental and biological sampling in populations potentially exposed to pesticides in Santa Fe province. It also highlights the collaboration between various institutions and the collective construction of knowledge. Herbicides were detected in environmental matrices, such as rainwater and soil, likely as a result of agricultural and/or domestic use. These compounds may serve as indicators (or tracer molecules) of the development, expansion, and impact of the prevailing agricultural production model.

Given the risk associated with pesticide exposure, training and awareness campaigns for individuals involved in agricultural activities are essential to promote health and environmental protection.

The observed increase in genetic damage across the three studied populations suggests the need to implement surveillance systems to identify rural populations at risk and apply preventive or corrective measures accordingly.

Some of the analytes detected in the biological samples—such as DDT, banned in Argentina in the 1990s—persist in human tissues due to their high environmental stability. Moreover, λ‐cyhalothrin is primarily used in agricultural applications and is not commonly employed for domestic or sanitary purposes. Therefore, its high concentrations detected in human samples may be considered an indicator of environmental exposure related to agricultural practices, raising concerns about potential health effects considering chemical mixtures.

It is therefore important to initiate studies focused on the effects of such mixtures, using the compound profiles and concentrations identified in this study as a reference.

Author Contributions

Conceptualization: María Priscila Dechiara, María Fernanda Simoniello and Damián Marino. Data curation: María Priscila Dechiara, María Fernanda Simoniello and Damián Marino. Formal analysis: María Priscila Dechiara, Lucía Magdalena Odetti, María Fernanda Simoniello and Damián Marino. Funding acquisition: María Fernanda Simoniello and Damián Marino. Investigation: María Fernanda Simoniello, Carlina Leila Colussi and María Fernanda Simoniello. Methodology: María Priscila Dechiara and Lucía Magdalena Odetti. Project administration: María Fernanda Simoniello and Damián Marino. Resources: María Fernanda Simoniello and Damián Marino. Software: María Priscila Dechiara, María Fernanda Simoniello and Damián Marino. Supervision: María Fernanda Simoniello and Damián Marino. Validation: María Fernanda Simoniello and Damián Marino. Visualization: María Priscila Dechiara, Carlina Leila Colussi, Lucía Magdalena Odetti and María Fernanda Simoniello. Writing – original draft: María Priscila Dechiara and Carlina Leila Colussi. Writing – review and editing: María Priscila Dechiara, Carlina Leila Colussi, Lucía Magdalena Odetti and María Fernanda Simoniello.

Funding

This work was supported by the Universidad Nacional del Litoral and CAI+D (50120110100196, 50120150100161LI, and 50320220100078LI).

Ethics Statement

The objectives of the research were explained to each of the volunteers; in all cases, informed consent was obtained according to the regulations of the Research Ethics and Safety Committee of the Faculty of Biochemistry and Biological Sciences of the National University of the Littoral (Act 13/11).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1 Limit of detection and limit of quantification for compounds analyzed in blood samples.

Table S2 Limit of detection and limit of quantification for compounds analyzed in soil and rainwater.

JAT-46-3804-s001.docx (22.9KB, docx)

Acknowledgements

We are deeply grateful to the staff of the health centers and the local communities for their support, which made this work possible, especially to Dr. Arturo Serrano. We also extend our sincere thanks to the participants of this study. We thanks to Fabio Claude for his assistance with field and laboratory logistics, and to the fellows at the Centro de Investigaciones del Medio Ambiente, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, for their invaluable support and willingness to help throughout the research process.

Data Availability Statement

The data that has been used is confidential.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1 Limit of detection and limit of quantification for compounds analyzed in blood samples.

Table S2 Limit of detection and limit of quantification for compounds analyzed in soil and rainwater.

JAT-46-3804-s001.docx (22.9KB, docx)

Data Availability Statement

The data that has been used is confidential.

Articles from Journal of Applied Toxicology are provided here courtesy of Wiley

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