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Article

Small-Scale Farming, Pesticide Exposure, and Respiratory Health: A Cross-Sectional Study in Bolivia

by
Maria Teresa Solís-Soto
1,2,*,
Jonas Walber
3,
Armando Basagoitia
4,
Ondine S. von Ehrenstein
5,6 and
Katja Radon
2,3
1
OH TARGET Competence Center, Universidad San Francisco Xavier de Chuquisaca, Estudiantes 96, Sucre P.O. Box 359, Bolivia
2
Center for International Health, University Hospital Munich (LMU), Ziemssenstr. 1, 80336 Munich, Germany
3
Environmental Epidemiology & Net Teaching Unit, Institute for Occupational, Social and Environmental Medicine, University Hospital Munich (LMU), Munich. Ziemssenstr. 1, 80336 Munich, Germany
4
Consultora Salud Global, Urriolagoitia 354, Sucre, Bolivia
5
Department of Community Health Sciences, Fielding, School of Public Health, University of California, P.O. Box 951772, Los Angeles, CA 90095-1772, USA
6
Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095-6900, USA
*
Author to whom correspondence should be addressed.
Environments 2025, 12(8), 290; https://doi.org/10.3390/environments12080290
Submission received: 16 July 2025 / Revised: 18 August 2025 / Accepted: 19 August 2025 / Published: 21 August 2025
(This article belongs to the Special Issue Healthy and Safe Environments Across Occupational and Environmental Contexts, 2nd Edition)
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Abstract

This study analyzed the relationship between pesticide exposure with respiratory symptoms and lung function among small-scale farm workers in rural communities of Sucre, Bolivia. A cross-sectional study was conducted including 277 farmers and 214 non-farmers ≥ 16 years. Pesticide exposure and respiratory symptoms were assessed by questionnaire, and lung function was assessed by spirometry. Logistic regression models were used to estimate odds ratios and 95% confidence intervals for associations between pesticide exposure and respiratory symptoms, while multiple linear regression was employed to estimate associations with lung function. The adjusted regression models indicated a positive association between pesticide exposure and chronic cough or phlegm (aOR 1.22; 95% CI 1.0 to 1.5), chest tightness (1.14; 1.0 to 1.3), and nasal allergies (1.21; 1.0 to 1.4). Also, pesticide exposure showed a slight positive association with FVC (β = 0.04; 95% CI = 0.01 to 0.07). Agricultural work (vs. non-agricultural work) showed a dual effect; on the one hand, it showed a negative association with lung function (FEV1/FVC (%): −1.57; 95% CI = −3.25 to −0.11); on the other hand, it seemed to be a protective factor for nasal allergies (aOR 0.31; 95% CI 0.1–0.8). Our study suggests an association between pesticide exposure and respiratory symptoms and farm work with lung function parameters. The results underscore the need to enhance programs that regulate and train farmers on the use of pesticides, thereby reducing health effects on workers and agricultural and neighboring communities.

Graphical Abstract

1. Introduction

Agriculture is one of the primary productive sectors in the economies of many countries in Latin America, accounting for an important portion of each country’s GDP. Globally, an increase in agricultural production has been reported, primarily through the intensive use of agrochemicals, such as pesticides, to control pests and protect crops [1]. In this sense, pesticide use also has increased, particularly in low- and middle-income countries, where its use is estimated to have risen by 153% over the last two decades [2]. As a result, pesticide contamination has significantly polluted the environment and caused adverse impacts on human health and ecosystems [3,4]. Depending on the type of pesticide and its mechanism of action, it can have various effects on human health. Exposure through direct contact, handling of pesticides, or ingestion of pesticide residues in food has been associated with a number of health problems, including cancer, diabetes mellitus, neurological disorders, adverse reproductive outcomes, and oxidative stress [5]. Several studies have also suggested a link between pesticide exposure and respiratory health, including chronic bronchitis, chronic obstructive pulmonary disease [6], and asthma [7]. These adverse respiratory health effects may particularly occur in individuals with pre-existing respiratory diseases or increase susceptibility in healthy individuals due to repeated exposures [8]. Several factors can influence these associations, including the type of pesticide, the duration and route of exposure (skin contact, ingestion, or inhalation), the use of personal protective equipment, hygienic practices after pesticide handling, and the individual’s health status, among others [9]. However, the evidence to date is inconclusive [10,11,12].
Some studies have found that certain farm-related factors may contribute to protection against rhinitis, asthma, and atopy in farmers and communities near farms [13]; nevertheless, this finding appears to be inconsistent [14]. It was reported that farmers can be exposed to several occupational risks, including high pesticide exposure during the sowing, cultivation, and harvesting seasons [15,16]. Additionally, people in agricultural communities may be more exposed to pesticides due to direct work in agriculture, proximity to croplands treated with pesticides, and the transfer of chemicals on their clothes and equipment, which contributes to para-occupational exposure [17,18]. Some studies of small-scale farmers in Bolivia have found frequent use of pesticides with a high degree of toxicity, as well as symptoms of poisoning [19]. Additionally, a lack of knowledge about hygiene and protection measures was reported, particularly in the handling and storage of these products [20], which can cause increased pesticide exposure. Few studies have evaluated pesticide exposure in Bolivia, and even fewer have associated this exposure with health problems such as respiratory health in small-scale farming in Bolivia [21]. This study aimed to investigate the relationship between pesticide exposure and respiratory symptoms, as well as lung function impairments, among small-scale farm workers in Sucre, Bolivia. The results can help better understand pesticide exposure in this working population and contribute evidence to inform public policies that improve working conditions, occupational safety culture, and respiratory health.

2. Materials and Methods

2.1. Design and Setting of the Study

A cross-sectional study was conducted in rural areas of Districts 6 and 7 in Sucre, Bolivia (Figure 1). Although people in both areas engage in agricultural activities, these activities are more pronounced in District 7 due to its favorable geographic and climatic conditions. In this area, primary production focuses on vegetables, including tomatoes, potatoes, guava, avocados, lemons, and papayas, and it is the primary source of these products for the capital city. In District 6, the main economic activities are construction and commerce. A total of 13,429 inhabitants (D6: 4678; D7: 8751) reside in the two areas combined, and the most common languages spoken in Sucre are Spanish (68%) and Quechua (26%) [22].

2.2. Study Population and Sampling

Due to the high dispersity of the houses and communities, especially in District 7, the lack of official registers, and limited geographic accessibility, we included nine communities in the study (District 6: Alegria; District 7: Chaco, Chuqui-Chuqui, La compuerta, Surima, Tapial) in coordination with the farmers union, vicinal joins, and primary health services. The communities were mapped, and a random sample was implemented, selecting 215 households (group of people living in the same house), distributed proportionally to the size of each community. All family members aged 16 years or older were invited to participate in the study. Approximately 645 persons were invited, resulting in a participation of 76%. Farmers were defined as people who reported currently working in agriculture.

2.3. Data Collection and Variable Definition

Two trained interviewers, one of whom was fluent in Quechua, conducted face-to-face visits to each household between October 2016 and January 2017. During the visits, two structured questionnaires were administered. The first one was directed at the head of the family or other representative and included closed questions regarding household characteristics. Subsequently, an individual questionnaire was administered to each family member to assess pesticide exposure and respiratory symptoms. Additionally, spirometry was performed. Each visit took approximately 2 h on average for each family.
Prior to the fieldwork, both the questionnaire and spirometry procedures were piloted with five families from different communities with similar backgrounds. Based on this pilot, certain technical terms were adapted to better align with the local context.

2.3.1. Assessment of Pesticide Exposure

Pesticide exposure was assessed using an adapted version of the instrument developed by Erik Jørs [19], which has been previously employed in Bolivia to explore knowledge, attitudes, and practices related to pesticide use.
As reported in other studies [11], an Individual Exposure Burden (IEB) score was calculated considering a simple sum of six variables related to exposure with a possible total score ranging from 0 to 10. It included the following questions and ratings:
(a)
Do you use pesticides (insecticides, fungicides, herbicides, acaricides, etc.) in agriculture? (no = 0; yes = 2);
(b)
Do you use pesticides for purposes other than agricultural exposure? (e.g., treatment of contaminated clothes and domestic use for pest control (no = 0; yes = 1);
(c)
Presence of previous signs or symptoms after pesticide exposure (including nausea, headache, vomiting, dizziness, muscle weakness, salivation, blurred vision, extreme tiredness, loss of appetite, slurred speech, skin irritation, tremor, lack of coordination, dry mouth, shortness of breath, abdominal pain, excessive perspiration) (no = 0; yes = 1);
(d)
Frequency of pesticide handling (no contact= 0; rarely (mostly diluted pesticides) = 1; sometimes = 2; frequently = 3);
(e)
Use of personal protective equipment when handling pesticides (handling pesticides yes = 0; no = 1);
(f)
Distance from home to crop areas (˃400 m = 0; 61 to 400 m = 1; or ≤60 m = 2).
For further analysis, high and low exposure to pesticides were categorized using the distribution of the data as a criterion, defining individuals with high pesticide exposure as those with an IEB score greater than the median (2 points). Additionally, sociodemographic information, including age (1 ≤ 30; 2 = 30–49; 3 ≥50 years), gender (1 = male; 2 = female), educational level (1 = none; 2 = primary; 3 = secondary or higher), smoking status (1 = never; 2 = former; 3 = current), fuel for cooking or heating (1 = gas, 2 = wood and coal), and height (cm) were considered as potential confounders.

2.3.2. Assessment of Respiratory Health

Respiratory symptoms were assessed using the Spanish version of the European Community Respiratory Health Survey (ECRHS), which evaluates respiratory symptoms over the previous 12 months through 14 closed questions [23]. For this study, we included the following:
(a)
Chronic cough or phlegm was considered present if the individual reported coughing on most days for at least three months per year or if sputum production occurred on most days for at least three months per year.
(b)
Presence of wheeze was defined as the occurrence of any whistling in the chest at any time during the last 12 months.
(c)
Nasal allergy was considered present if the individual reported having any nasal allergies, including rhinitis.
(d)
Chest tightness was defined as present if the individual reported a sensation of chest oppression or whistling.
All recommendations for administering the questionnaire were followed.

2.3.3. Assessment of the Lung Function

Lung function was evaluated using spirometry with an EasyOne™ portable spirometer (ndd Medizintechnik, Zurich, Switzerland), which was calibrated daily. Forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and the FEV1/FVC ratio were analyzed following a standard procedure, including quality control [23]. Usable spirometry was defined as two or more acceptable trials (Grade A quality) with repeatability of FEV1 and FVC [24]. This means that the back-extrapolated volume must be <5% of the FVC or 0.100 L, whichever is greater, a maneuver performed with maximal inhalation and exhalation and no coughing, inhalations during the trace, or evidence of leaks. For a test to achieve repeatability, the difference between the largest and second largest values for FVC and FEV1 should be within 0.15 L (150 mL) [25]. The spirometry was performed by a health professional previously trained in lung function, spirometry, and equipment management.
Since no specific reference table for Bolivia was available to compare lung function parameters with a proper reference population, considering age, sex, height, and ancestral background [26], we used the quantitative values obtained by spirometry for the entire study population.

2.4. Data Analysis

The questionnaires were completed on paper and digitized twice by independent individuals using the EpiInfo v.7 statistical software. After error checking, further data analyses were conducted using SPSS v. 29. Pesticide exposure, sociodemographic data, and respiratory symptoms were analyzed as categorical variables, and absolute and relative frequencies were reported. Lung function variables were analyzed as numerical, and the mean and standard deviation were reported. Missing values were excluded from further analysis.
Intraclass correlation coefficient (ICC) was computed to analyze the relationship of cases within a cluster (household) for each of the main outcomes. ICC ranged from 0.005 for FEV1 and 0.016 for FEV1/FVC%). Considering the low correlation between observations, no adjustments by cluster sampling were performed [27].
Comparisons between groups were performed using a T-test, and comparison between categorical variables was performed using the chi-squared test. To assess the associations of the independent variables and respiratory symptoms, unadjusted and adjusted logistic regression models were computed. A one-way ANCOVA was conducted to compare lung function parameters (FVC, FEV1, and FEV1/FVC%) between farmers and non-farmers, as well as between those with high and low pesticide exposure, while controlling for age, sex, and height. Levene’s test and normality checks were carried out, and the assumptions were met. A sensitivity analysis was performed considering different cut-off points for IEB (more than one and more than three points in the IEB score) to analyze the consistency of the results.
Finally, to predict factors associated with lung function, linear regression models were computed. All models considered 95% confidence intervals.

2.5. Ethics Considerations

Ethical guidelines according to the Helsinki declaration [28] and recommendations for good epidemiological practice [29] were followed in each step of the research. The study protocol has received ethical approval from the Bioethics Committee of the Medical Faculty of the Universidad San Simón in Cochabamba, Bolivia (08.2016). Additionally, the authorization of the local authorities in the study communities was requested.
The families received an informative letter, and the objectives and procedures of the study were explained during the first contact with the participants. Written informed consent was required for all participants. The questionnaire and all other data were anonymized; only a code was assigned to link all the information. Participation was voluntary, and it was ensured that non-participation would have no adverse consequences on the individuals or the community.

3. Results

A total of 491 individuals participated in the study, comprising 277 farmers (56.4%) and 214 non-farmers (43.6%). Compared to non-farmers, more farmers were 50 years or older (50% vs. 33%), male (56% vs. 36%;), current smokers (19% vs. 8%), used wood or coal for cooking or heating (13% vs. 7%), and had a lower percentage of secondary education (26% vs. 44%). More than half of the farmers (57%) reported using pesticides in agriculture, with 40% of them using them frequently. Additionally, more than 90% had experienced signs or symptoms after pesticide application, despite 76% reporting the use of at least three personal protective equipment items, including a face mask. Among the personal protection elements most used by farmers when handling pesticides were a hat (88%), boots (51%), overalls (44%), a facial mask (38%), and gloves (30%).
The IEB Index was higher in farmers compared to the group of non-farmers ( x ¯ = 4.3; SD = 0.8 vs. 0.9; 0.8) (Table 1).

3.1. Respiratory Symptoms and Pesticide Exposure

Approximately 35% of participants (n = 166) reported experiencing symptoms of chest tightness, and 13% (n = 63) reported symptoms of chronic phlegm or cough. The adjusted models indicated a positive association between pesticide exposure (as measured by the IEB score) and chest tightness (aOR 1.14; 95% IC 1.0–1.3) and chronic cough or phlegm (aOR 1.22; 95% IC 1.0–1.5) (Table 2).
On the other hand, 38% (n = 183) and 16% (n = 76) reported symptoms of wheezing and nasal allergies, respectively. Farmers (2.10; 1.1–3.7), compared to non-farmers, were significantly more likely to report wheezing. Additionally, agricultural work was shown to be protective (0.31; 0.1–0.8) for nasal allergies compared to non-agricultural work, while pesticide exposure (1.21; 1.0–1.4) was shown to be a risk factor for nasal allergies (Table 3).

3.2. Lung Function and Pesticide Exposure

A total of 375 of 435 spirometry (86.2%) were considered of sufficient quality (Quality A) and included in the subsequent analyses. Among the main reasons attributed to low-quality spirometries were difficulties in understanding the test, especially in older people or those with language difficulties, as well as some cases where the recommended number of attempts was exceeded without being able to exhale with the necessary force.
Of the included spirometries, 348 (93%) and 213 (57%) participants reported an FEV1/FVC% ratio above 70 and 80%, respectively. Farmers presented significantly higher values in FVC (L) [F = 6.340, p = 0.012] but lower values in FEV1/FVC (%) ratio [F = 7.094, p = 0.008] compared to non-farmers. However, people reporting high pesticide exposure showed significantly higher means of FVC (L) [F = 7.037, p = 0.008] and FEV1 (L) [F = 3.899, p = 0.049] compared to those reporting low pesticide exposure (Table 4). Sensitivity analysis with IEB cut-off points of 1 and 3 maintained the same trend (Supplementary Material)
Adjusted for height, age, gender, smoking status, and fuel for cooking or heating, exposure to pesticides (β = 0.033; 95% CI = 0.001 to 0.066) showed a significant positive association only with FVC, accounting for 72% of the variance in this model, while farmers showed a negative association only with FEV1/FVC (%) ratio (β = −1.568; 95% CI = −3.249 to −0.112), with an R squared of 31%. (Table 5).

4. Discussion

This study found an association between pesticide exposure and the presence of chronic cough or phlegm, chest tightness, and nasal allergy symptoms. Farmers had a slightly lower percentage of total lung volume exhaled in the first second of forced expiration (FEV1/FVC%) compared to non-farmers. However, this difference was not apparent concerning pesticide exposure.
The characteristics of the people involved in small-scale agriculture in the rural communities we studied are consistent with those reported in other contexts related to family-run agriculture. Most farmers were males, older, and had lower educational levels than non-farmers, with limited land areas for cultivation located close to their homes [30]. Our study also reports that nearly 60% of farmers frequently used pesticides in their agricultural practices. More than 90% of them reported some symptoms of poisoning after contact with pesticides, which could be explained by the low percentage of farmers reporting the use of a facial mask (38%) or gloves (30%) when handling pesticides. In this sense, the characteristics of our study population are very similar to other contexts in Latin America, where a high percentage of family farming (72%) has been reported, mainly small-scale working in the informal sector, with a common low educational level, low income, and a lack of social and healthcare security for the families [31], which may be related to low availability of occupational training. Other studies have also found inadequate pesticide handling practices, and an equally high percentage of farmers reported symptoms of acute pesticide poisoning after spraying [20].
The analysis revealed a relationship between pesticide exposure, measured using an Individual Exposure Burden (IEB) score, and respiratory symptoms, including chest tightness, chronic phlegm, and nasal allergy, consistent with other studies. However, no association was found with wheeze. In agriculture, one of the main routes of entry of pesticides is the respiratory tract during fumigation, preparation of mixtures, or application in closed environments [32]. Depending on the type of pesticide, potential mechanisms of action affecting the airways have been identified. Many pesticides can directly alter the bronchial lining through irritation, inflammation, immunosuppression, and increased susceptibility to allergens or other stimuli [12,33]. Furthermore, the development of acute and chronic respiratory disorders may be attributed to an oxidative stress reaction. This reaction is implicated in many of the pathogenic processes underlying chronic obstructive pulmonary disease, including direct tissue destruction, blockage of the antiprotease pathway, promotion of mucus hypersecretion, and disruption of vascular barrier function, resulting in bronchial wall edema, bronchoconstriction, and inflammation [8,34]. This mechanism could explain the higher risk found for wheeze in farmers compared to non-farmers, as well as a lower FEV1/FVC ratio, and its negative association with this indicator of lung function, suggesting a more obstructive pattern in this group, as reported previously [10,35]. Studies in Latin America have reported a high and increasing prevalence of herbicide use [36], which has been linked to respiratory problems [37]. However, previous studies in Bolivia report that pesticide mixing is common, which could enhance the toxic effect of pesticides [19]. In addition to this, Bolivia, as well as other Latin American countries, faces severe difficulties posed by lax or permissible regulatory systems that allow the use of pesticides prohibited in the European Union [36] and by deficiencies in marketing that facilitate access to pesticides without adequate conditions [38]. No relationship was observed between pesticide exposure and lung function parameters. This finding may be partially explained by a potential exposure misclassification [39]. Individuals who reported no current direct exposure to pesticides may have experienced past exposures or may still be indirectly exposed, as nearly a third of non-farmers report living within 400 m of a crop field.
On the other hand, our study found that, regardless of pesticide exposure, farmers were less likely to experience nasal allergy compared to non-farmers (aOR 0.31; 95% CI 0.1–0.8). Consistent with this, several studies have reported that farm-related exposures could induce an anti-inflammatory response of innate immunity, as well as increased biodiversity of the gut microbiota, which could play a key role in allergic diseases. This protective effect could be partially explained by high exposure to lipopolysaccharide, a cell wall component of Gram-negative bacteria, and bacterial DNA (CpG), which are very common in farm environments. However, a complex interaction between the microbiome, immunomodulatory effects of microbial components, timing of exposure, and individual factors such as lifestyle has been reported [40,41]. In this sense, in our study area, it is very possible that farmers living in rural areas were exposed to the farm environment from the intrauterine environment and throughout their lives, since this activity is often inherited from the family. This exposure from early ages may have regulated microbiome and immune maturation and decreased the risk for developing allergic disease.
To explore the relationship between pesticide exposure and respiratory function, two approaches were considered. Validated surveys were used in the Spanish version, allowing us to compare our results with those from other contexts [23]. Although this survey has not been validated in Bolivia, its application in various contexts in Latin America has shown good performance [42]. Likewise, the questionnaire assessment was carried out by trained interviewers instead of self-completion, as approximately one-third of our study population had only completed primary education. Our study achieved a high response rate (76%), which may have been due to the coordination meetings with leaders and health authorities that facilitated the approach and dissemination of the study in the communities, as well as the use of home visits and face-to-face interviews in the participants’ own language.
This study is subject to several limitations. Since this is a cross-sectional study, it is not possible to assume causality, mainly due to the difficulty of assuming the temporality criterion. Also, considering self-reported symptoms may lead to a potential recall bias among people with a current respiratory problem. It is also possible that there may be potential exposure misclassification in the study, especially among non-farmers living near crops, whose exposure to pesticides may be high even without being involved in farm activities. Given the restricted resources and laboratories in our local context, it was not possible to determine the presence of pesticide metabolites or other more specific and objective exposure indicators. However, our study considered the calculation of an Individual Exposure Burden (IEB), which included variables related to exposure to pesticide use in and outside of agriculture, as well as the distance to crop fields and the use of personal protective equipment in the score, considering that this practice can mitigate pesticide exposure [11]. Future studies can complement exposure measurement by evaluating the IEB and some biological measurements that will strengthen a more comprehensive exposure assessment. In terms of assessing lung function, we did not consider a post-bronchodilator spirometry test, thus limiting a more accurate estimation of the reversibility issues associated with the obstruction [23]. Given the limited availability of population reference parameters for the general population, particularly in Bolivia, we were unable to calculate the predictive value for FEV1 and FVC, which limits the comparability of our results. However, we adjusted the values by age, gender, and height as recommended, which allows for estimating adjusted values [26]. Future studies could also consider more advanced statistical analyses that would allow for a more precise analysis of the relationship between exposure and outcome, taking into account potentially mediating factors and other confounding factors. More population-based studies are needed that consider the assessment of pesticide and farming or residence-related exposure in a more holistic manner, including the type of pesticides, intensity, and timing of exposure in farmers and non-farmers, as well as the amount of pesticides absorbed and accumulated by the body. Furthermore, it is crucial to consider follow-up population studies to identify respiratory problems in the short and long term. In this way, more solid evidence can be provided to support stricter regulation and control, as well as the promotion of adequate education and training programs tailored to the needs of agricultural communities.
This study suggests an association between pesticide exposure and respiratory and allergic symptoms, although farmers appear to have a lower odds of developing nasal allergies. In addition, farmers appear to have a lower FVC/FEV1 ratio than non-farmers, suggesting the presence of obstructive patterns. The results emphasize the need to implement and monitor the use of pesticides, especially those with high toxicity, which can affect all members of farming communities. It is also necessary to strengthen training programs for farmers on pesticide management and the use of personal protective equipment, as well as on alternatives for their use, to reduce and mitigate pesticide exposure and the effects on the health of farmers and neighboring communities.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/environments12080290/s1, Table S1: Adjusted means and standard deviation (SD) of spirometry values in farmers and non-farmers (N = 375); Table S2: Adjusted means and standard deviation (SD) of spirometry values in farmers and non-farmers (N = 375).

Author Contributions

Conceptualization, M.T.S.-S., O.S.v.E. and K.R.; methodology, M.T.S.-S., O.S.v.E., A.B. and K.R.; software, M.T.S.-S., J.W. and K.R.; validation, M.T.S.-S., J.W. and K.R.; formal analysis, M.T.S.-S. and K.R.; investigation, M.T.S.-S., J.W., A.B. and K.R.; resources, M.T.S.-S. and K.R.; data curation, M.T.S.-S. and J.W.; writing—original draft preparation, M.T.S.-S.; writing—review and editing, M.T.S.-S., J.W., A.B., O.S.v.E. and K.R.; visualization, M.T.S.-S.; supervision, K.R.; project administration, M.T.S.-S. and K.R.; funding acquisition, M.T.S.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Center for International Health of the Ludwig Maximilians Universität in München, Germany (CIHLMU). These funds were provided through the Network Funds 2016 call by the German Academic Exchange Service (DAAD), Centers of Excellence for Exchange and Development (EXCEED), and the German Federal Ministry for Economic Development and Cooperation (BMZ).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Universidad Mayor de San Andrés (UMSS 06.09.2016).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We would like to thank all the study participants, as well as the local authorities who facilitated the fieldwork.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GDPGross Domestic Product
IEBIndividual Exposure Burden
FVC (L)Forced Vital Capacity (FVC), which is the total volume of air exhaled in a forced expiratory maneuver.
FEV1 (L)The amount of air that a person exhales during the first second of a forced expiratory maneuver.
FEV1/FVC (%)The ratio of FEV1 to FVC is obtained by dividing the FEV1 by the FVC and is expressed as a percentage (100 × FEV1/FVC).

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Environments 12 00290 g001
Figure 1. Study areas in Districts 6 and 7 of Sucre, Bolivia.
Figure 1. Study areas in Districts 6 and 7 of Sucre, Bolivia.
Environments 12 00290 g001
Table 1. Sociodemographic and pesticide exposure characteristics among farmers and non-farmers (N = 491).
Table 1. Sociodemographic and pesticide exposure characteristics among farmers and non-farmers (N = 491).
VariablesCategoriesn MissingTotalFarmers (N = 277)Non-Farmers (N = 214)p-Value
n%n%
Age (years)˂300138 (28.1)5519.98338.8˂0.001
30–49143 (29.1)8330.06028.0
≥50210 (42.8)13950.27133.2
GenderMale0232 (47.3)15455.67836.4˂0.001
Female259 (52.7)12344.413663.6
Educational levelNone1107 (21.8)5319.25425.2˂0.001
Primary217 (44.3)15255.16530.4
Secondary or higher166 (33.9)7125.79544.4
Smoking status Never3375 (76.8)19369.918285.8˂0.001
Former44 (9.0)3111.2136.1
Current69 (14.1)5218.8178.0
Fuel for cooking or heating Gas4437 (89.724087.019793.40.021
Wood or coal50 (10.3)3613.0146.6
Height (cm; mean and SD)57156 (9.0)1588.61538.8˂0.001 ***
BMI (mean and SD)5726.6 (5.2)25.95.127.45.30.003 ***
Use of pesticides in agricultureYes0157 (32.0)15756.700-
Use of pesticides for other purposesYes9236 (48.0)15054.58641.50.005
Signs or symptoms after pesticide exposureYes0251 (51.1)25190.600.0-
Frequency of pesticide handlingNo contact0339 (69.0)12545.1214100.0
Rarely 10 (2.0)103.600.0
Sometimes 31 (6.3)3111.200.0˂0.001
Frequently 111 (22.6)11140.100.0
Use of PPE when handling pesticides *Yes 0424 (86.4)21075.8214100.0˂0.001
Distance to crop areas (m)˃4000308 (62.7)16659.914266.40.34
61 to 400 126 (25.7)7727.84922.9
≤60 57 (11.6)3412.32310.7
IEB (Mean; SD) **92.79 (2.5)4.250.80.860.8˂0.001 ***
* It includes the use of at least three personal protective elements, at least one of which was a face mask. ** Individual Exposure Burden (IEB) score considering the use of pesticides in agriculture, use of pesticides for other purposes, signs or symptoms after pesticide exposure, frequency of pesticide handling, use of PPE when handling pesticides, and distance to crop areas. *** T-test.
Table 2. Unadjusted and adjusted logistic regression models to predict chest tightness and chronic phlegm or cough (N = 482).
Table 2. Unadjusted and adjusted logistic regression models to predict chest tightness and chronic phlegm or cough (N = 482).
Chest Tightness (n = 166)Chronic Phlegm/Cough (n = 63)
n (%)OR (95% CI)aOR (95% CI) *n (%)OR (95% CI)aOR (95% CI) *
FarmerNo52 (25.2)1124 (11.4)11
Yes114 (41.6)2.11 (1.4–3.1)1.29 (0.2.4)41 (14.9)1.37 (0.8–2.3)0.95 (0.4–2.2)
IEB ** (mean; SD)3.39 (2.6)1.15 (1.1–1.2)1.14 (1.0–1.3)3.57 (2.6)1.14 (1.0–1.3)1.22 (1.0–1.5)
* Models adjusted by age, gender, educational level, smoking status, fuel for cooking or heating, and Body Mass Index. ** Individual Exposure Burden is a score considering the use of pesticides in agriculture, use of pesticides for other purposes, signs or symptoms after pesticide exposure, frequency of pesticide handling, use of PPE when handling pesticides, and distance to crop areas. Nine missing values in the IBE variable were excluded from this analysis.
Table 3. Unadjusted and adjusted logistic regression models to predict wheeze and nasal allergies (N = 491).
Table 3. Unadjusted and adjusted logistic regression models to predict wheeze and nasal allergies (N = 491).
Wheeze (n = 183)Nasal Allergies (n = 76)
n (%)OR (95% CI)aOR (95% CI) *n (%)OR (95% CI)aOR (95% CI) *
FarmerNo60 (28.3)1137 (17.5)11
Yes129 (46.6)2.21 (1.5–3.2)2.1 (1.1–3.7)40 (14.5)0.80 (0.5–1.3)0.31 (0.1–0.8)
IEB ** (mean; SD)3.39 (2.6)1.04 (0.9–1.1)1.03 (0.9–1.2)3.04 (2.7)1.04 (0.9–1.1)1.21 (1.0–1.4)
* Models adjusted by age, gender, educational level, smoking status, fuel for cooking or heating, and Body Mass Index. ** Individual Exposure Burden is a score considering the use of pesticides in agriculture, use of pesticides for other purposes, signs or symptoms after pesticide exposure, frequency of pesticide handling, use of PPE when handling pesticides, and distance to crop areas. Nine missing values in the IEB variable were excluded from this analysis.
Table 4. Adjusted means and standard deviation (SD) of spirometry values in farmers and non-farmers (N = 375).
Table 4. Adjusted means and standard deviation (SD) of spirometry values in farmers and non-farmers (N = 375).
Farmers Pesticide Exposure *
Yes
Mean (SE)		No
Mean (SE)		p Values **High
Mean (SE)		Low
Mean (SE)		p Values **
FVC (L) 3.95 (0.04)3.79 (0.04)0.0123.98 (0.04)3.82 (0.04)0.008
FEV1 (L)3.15 (0.03)3.10 (0.04)0.3063.19 (0.04)3.10 (0.03)0.049
FEV1/FVC (%)79.80 (0.41)81.52 (0.41)0.00880.44 (0.46)80.72 (0.43)0.666
* Pesticide exposure is defined as high with ˃2 at the Individual Exposure Burden (IEB); ** ANCOVA.
Table 5. Multiple linear regression models for lung function (N = 375).
Table 5. Multiple linear regression models for lung function (N = 375).
FVC *FEV1 *FEV1/FVC (%) *
β-Coefficient95% CIβ-Coefficient95% CIβ-Coefficient95% CI
IEB **0.0330.001; 0.0660.020−0.007; 0.0470.006−0.350; 0.361
Farmer−0.011−0.163; 0.142−0.052−0.180; 0.075−1.568−3.249; −0.112
R20.72 0.72 0.31
* Model adjusted by height, age, gender, smoking status, and fuel for cooking or heating. ** Individual Exposure Burden is a score considering the use of pesticides in agriculture, use of pesticides for other purposes, signs or symptoms after pesticide exposure, frequency of pesticide handling, use of PPE when handling pesticides, and distance to crop areas.
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Solís-Soto, M.T.; Walber, J.; Basagoitia, A.; Ehrenstein, O.S.v.; Radon, K. Small-Scale Farming, Pesticide Exposure, and Respiratory Health: A Cross-Sectional Study in Bolivia. Environments 2025, 12, 290. https://doi.org/10.3390/environments12080290

AMA Style

Solís-Soto MT, Walber J, Basagoitia A, Ehrenstein OSv, Radon K. Small-Scale Farming, Pesticide Exposure, and Respiratory Health: A Cross-Sectional Study in Bolivia. Environments. 2025; 12(8):290. https://doi.org/10.3390/environments12080290

Chicago/Turabian Style

Solís-Soto, Maria Teresa, Jonas Walber, Armando Basagoitia, Ondine S. von Ehrenstein, and Katja Radon. 2025. "Small-Scale Farming, Pesticide Exposure, and Respiratory Health: A Cross-Sectional Study in Bolivia" Environments 12, no. 8: 290. https://doi.org/10.3390/environments12080290

APA Style

Solís-Soto, M. T., Walber, J., Basagoitia, A., Ehrenstein, O. S. v., & Radon, K. (2025). Small-Scale Farming, Pesticide Exposure, and Respiratory Health: A Cross-Sectional Study in Bolivia. Environments, 12(8), 290. https://doi.org/10.3390/environments12080290

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