Abstract
This study explored the potential association between chronic exposure to pesticide mixtures including paraquat and respiratory outcomes among Colombian farmers. Sociodemographic and occupational data, respiratory symptoms and spirometric data were collected. Paraquat in spot urine samples were quantified with solid-phase extraction high-performance liquid chromatography. Multiple Poisson regressions with robust variance were used to determine factors associated with respiratory outcomes. Profiles of pesticide mixtures used were identified among 217 farmworkers, but profenofos and methamidophos-based mixtures were more frequent. Chronic paraquat exposure was slightly associated with self-reported asthma (PR: 1.06; 95% CI 1.00 to 1.13). Different pesticide mixtures were associated with flu, thoracic pain, allergic rhinitis, and obstructive pattern in spirometry. Although acute exposure to paraquat is low among Colombian farmers participating in the study, associations between respiratory outcomes and chronic pesticide mixtures exposure including profenofos, methamidophos or glyphosate require further specific studies.
Keywords: Occupational epidemiology, Toxicology, Pesticide, Paraquat, Chemical mixtures
Introduction
Paraquat (1,1’-dimethyl-4–4’-bipyridinium dichloride) is a quaternary ammonium compound widely used as a contact herbicide and crop desiccant. Although it has been banned in several countries because it has been associated with poisoning, paraquat is widely used in developing countries1, 2). Among the harmful effects from paraquat, those involving the respiratory system have received much attention, having been observed since the first acute cases of poisoning were reported in the literature half a century ago3). Studies have approached this topic in different contexts since the year 1988, when a high occurrence of chronic obstructive pulmonary disease was reported in Colombia among exposed farmworkers, as compared to those not exposed to paraquat4).
Then several studies have been performed with farmworkers in Costa Rica. The first compared workers exposed to pesticides with those not exposed. Those with higher exposures to paraquat were found to present more episodes of dyspnea accompanied with wheezing, although no evidence of obstructive alterations were identified5). Another study, which included a group of farmworkers who handled paraquat and an unexposed group, also reported no alterations in spirometric results6). In a more recent study with indigenous workers exposed to paraquat pesticide mixtures on banana plantations, wheezing was associated with their returning to places where the chemical had been previously applied7).
In Greece, a study of grape farmers and workers for tourism companies showed a higher frequency of allergic rhinitis among those exposed to pesticides, including paraquat8). A similar occurrence was reported for chronic bronchitis among non-smoking women participating in a study about agricultural health9). In South Korea, research with farmworkers exposed to paraquat and those not exposed reported a dose-response relationship between exposure and a decrease in forced vital capacity and forced expiratory volume10). Considering the above inconsistent outcomes, it was decided to explore the possible respiratory effects from chronic exposure to paraquat and another pesticides among farm workers who work in three municipalities in the Department of Antioquia.
Methods
A cross-sectional study was conducted with a volunteer sample of 218 farmworkers, in the municipalities of Carmen de Viboral, Granada and La Unión, all in Antioquia, Colombia. One worker was excluded from the analysis due to lack of data required in the analysis, thus only 217 farmworkers were included in the study. These three municipalities are located in the Central Andes, an eastern sub-region of the Department of Antioquia. They have a variety of climatic zones corresponding to altitudes ranging from 800 to 3,000 masl, enabling the growth of many types of crops as beans, corn, potato, avocado, tree tomato (Solanum betaceum), berries, legumes, green vegetables and aromatic plants, which are treated with large amounts of pesticides. Most of the inhabitants from the region work in farming. The inclusion criteria for the present study was a report of having been periodically exposed to paraquat over the past two years and having applied or handled it one week to two days before collection of a urine sample.
Information from each worker was obtained with a survey administered by trained interviewers. It included different social and demographic factors (age, sex, schooling, enrollment in the General Social Security and Health System), occupation (type of office, exposure time at the office, use of personal protection equipment, hygiene practices, industrial safety measures, exposure outside of work) workplace habits, eating habits, clinical symptoms (respiratory signs and symptoms) and toxicological history (smoking and consumption of alcohol). Before administering the questionnaire, the objective of the study was explained to all participants, informed consent was obtained and the biological samples collected. The study was approved by the ethics committee of the Colombian National Institute of Health.
Pulmonary function and respiratory symptoms
Pulmonary functioning of the workers was evaluated with spirometry using a Sibilmed Micro® spirometer, calibrated at the beginning of each period in which spirometric evaluations were performed. No worker presented contraindications for undergoing the test. Forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) were recorded. The FEV1/FCV ratio was also evaluated to determine the presence of obstruction. National Health and Nutrition Examination Survey (NHAHES) III equations for male Caucasians were used as a reference to read and interpret these tests, since according to the National Institute for Occupational Safety and Health (NIOSH) spirometry results with this racial group are not significantly different than those obtained with American indigenous workers11). For analysis FEV1/FCV ratios less 80% were considered as obstructive pattern. There weren’t other spirometric results that suggest respiratory damage. Self-reports of certain clinical symptoms were obtained, including cough, rhonchi, dyspnea, wheezing, thoracic pain, fatigue and some illnesses such as flu, chronic bronchitis, asthma and allergic rhinitis.
Paraquat measurements and variables related to workplace exposure
Urine samples (25 ml) were obtained from each participant and analyzed in the Occupational and Environmental Health Group laboratory of the Colombian National Institute of Health, where paraquat levels in urine were determined using high performance liquid chromatography with solid-phase extraction (SPE-HPLC)12), with limit of detection of 0.45 ng/ml. An external calibration curve was constructed using a certified pattern to differentiate paraquat from the rest of the bipyridinium herbicides. Since the respiratory effects were expected to be chronic, exposure for each participant was calculated based on workplace exposure variables. Thus, the value obtained from the measurement was multiplied by the number of months of pesticide exposure at work, following the job exposure matrix methodology13). In addition, participants were asked open questions about whether or not they habitually use pesticides at home or at work, thus exposure of these pesticides was self-reported (yes/no).
Statistical methods
Given that these farmworkers use complex mixtures of these substances, the most commonly reported pesticides were identified with a truth table14). Variables were then described using percentages or measurements of central tendency and dispersion, depending on the distribution observed. Additionally glyphosate concentrations were described using kernel density estimators, a non-parametric way of estimating the probability density function of a random variable15). The variables were compared among the municipalities using χ2, Fisher’s exact, one-way analysis of variance (ANOVA) or Kruskal-Wallis tests, according to the distribution observed. Lastly, adjusted prevalence ratios for respiratory outcomes were estimated based on chronic exposure to paraquat using Poisson regression models with robust variance16). The statistical program Stata 14 (Stata Corporation, College Station, USA) was used for these analyses.
Results
Data was collected from 217 farmworkers. Some of the characteristics of the participants are found in Table 2, most were from the municipality of Carmen de Viboral (55.76%) followed by La Unión (27.65%) and Granada (16.59%). When comparing the characteristics of the participants from the three municipalities, differences were observed in age, enrollment in social security and education. These results suggest that there is good access to education in Carmen de Viboral, and the social and labor conditions are better in La Unión. With respect to symptoms, differences were found for cough, dyspnea and fatigue, with a pattern in which the highest occurrences were always in Carmen de Viboral, followed by La Unión and Granada. No differences were found in the spirometry results nor in exposure to paraquat.
Table 2. Characteristics of Colombian farmers participating in the study (n=217).
Variable | Carmen de Viboral | La Unión | Granada | p value | |
---|---|---|---|---|---|
(n=121) | (n=60) | (n=36) | |||
Sex (male) (%) | 98.35 | 98.33 | 94.44 | 0.370a | |
Age (yr) | |||||
Median | 40 | 36 | 37 | 0.057b | |
Minimum and maximum | (18–67) | (16–66) | (17–64) | ||
Affiliation to social securityd (%) | |||||
Contributive | 19.83 | 61.67 | 16.67 | <0.001a | |
Subsidized | 77.69 | 26.67 | 80.56 | ||
No affiliated | 2.48 | 11.67 | 2.78 | ||
Education (%) | |||||
Analphabet | 4.96 | 1.67 | 0 | 0.029a | |
Incomplete elementary | 41.32 | 55.00 | 47.22 | ||
Complete elementary | 28.93 | 26.67 | 50.00 | ||
Incomplete secondary | 14.05 | 5.00 | 2.78 | ||
Complete secondary | 9.92 | 11.67 | 0 | ||
Technical | 0.83 | 0 | 0 | ||
Current smoker (%) | 38.02 | 35.00 | 25.00 | 0.356 | |
Former smoker (%) | 62.30 | 40.00 | 36.11 | 0.002 | |
Pesticide use in home (%) | 35.65 | 32.20 | 27.78 | 0.666 | |
Pesticide safety training (%) | 43.80 | 53.30 | 30.56 | 0.150a | |
Occupational exposure to pesticides (months) | |||||
Mean | 261.82 | 266.10 | 246.33 | 0.790c | |
Standard deviation | (139.67) | (151.02) | (124.66) | ||
Current paraquat exposure (self-reported) (%) | 7.44 | 1.67 | 0 | 0.111a | |
Current paraquat exposure (ng/ml) | |||||
Median | 1 | 1 | 1 | 0.345 | |
Mean | 9.61 | 13.22 | 10.95 | ||
Minimum and maximum | (1.00–54.4) | (1.00–57.1) | (1.00–52.2) | ||
Other pesticides (self-reported) (%) | |||||
Esbiothrin | 14.05 | 8.33 | 11.11 | 0.529 | |
Profenofos | 43.80 | 35.00 | 8.33 | <0.001 | |
Methomyl | 20.66 | 8.33 | 0 | 0.001a | |
Glyphosate | 15.70 | 1.67 | 16.67 | 0.005a | |
Methamidophos | 14.05 | 25.00 | 61.11 | <0.001 | |
Chlorpyrifos | 14.88 | 25.00 | 38.89 | 0.007 | |
Mancozeb | 6.61 | 8.33 | 36.11 | <0.001 | |
Chlorothalonil | 10.74 | 6.67 | 30.56 | 0.002 | |
Pesticide mixturese (self-reported) (%) | |||||
With profenofos and methomyl | 5.79 | 0 | 0 | 0.080a | |
With profenofos and methamidophos | 2.48 | 6.67 | 0 | 0.265a | |
With profenofos and chlorpyrifos | 4.13 | 3.33 | 0 | 0.675 | |
With profenofos | 14.05 | 8.33 | 0 | 0.024a | |
With methomyl | 5.79 | 1.67 | 0 | 0.276a | |
With glyphosate | 4.13 | 1.67 | 2.78 | 0.867a | |
With methamidophos | 2.48 | 6.67 | 11.11 | 0.094 | |
With chlorpyrifos | 2.48 | 8.33 | 2.78 | 0.188a | |
With mancozeb | 0.83 | 6.67 | 8.33 | 0.021a | |
Any other mixture | 57.85 | 56.67 | 75.00 | 0.143 | |
Self-reported respiratory outcomes (%) | |||||
Flu | 40.50 | 26.67 | 27.78 | 0.118 | |
Bronchitis | 4.96 | 3.33 | 2.78 | 1a | |
Asthma | 1.65 | 1.67 | 0 | 1a | |
Allergic rhinitis | 8.26 | 16.67 | 5.56 | 0.153a | |
Cough | 53.72 | 46.67 | 27.78 | 0.023 | |
Ronchi | 18.18 | 10.00 | 8.33 | 0.179 | |
Dyspnea | 25.62 | 15.00 | 8.33 | 0.040 | |
Wheezing | 4.13 | 3.33 | 2.78 | 1a | |
Thoracic pain | 21.49 | 21.67 | 22.22 | 1a | |
Fatigue | 40.50 | 38.33 | 13.89 | 0.012 | |
Obstruction pattern in spirometry (%) | 5.79 | 5.00 | 5.56 | 1a |
aFisher’s exact test; bKruskal-Wallis equality-of-populations rank test; cANOVA; other results are compared with χ2 test. dColombian health system classifies the individuals according to their payment capacity. People affiliate to contributive regime have labor relationships and/or ability to pay, such as hired or independent workers; people in the subsidized regime have not labor relationship or ability to pay, and no affiliated is a person not classified in the contributive or subsidized regimes. eMixtures including the more frequent pesticides: esbiothrin, profenofos, matabin, glyphosate, methamidophos, chlorpyrifos, mancozeb or chlorothalonil.
The participants reported using 62 different pesticides. Those most frequently reported were: profenofos (35.48%), methamidophos (24.88%), chlorpyrifos (21.66%), methomyl (13.82%), chlorothalonil (12.90%), mancozeb (11.98%), esbiothrin (11.98%), and glyphosate (11.98%). These pesticides were taken as the basis for the primary mixtures used, which are summarized in Table 1. Mixtures with these eight pesticides explained 46.32% of farmworkers participating in the study (n=101). The exploration of urine levels of paraquat using a Kernel density estimator identified a peak with individuals without exposure (n=147), and another peak towards 30 ng/ml that starts at 18 and ends close to 40 ng/ml among exposed farmworkers (n=70) ranged from 25 to 57.1 ng/ml (average: 32.06 ng/ml).
Table 1. Truth table of main pesticide mixtures reported by participants in the study.
More frequent pesticides in mixtures | n | % | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Paraquat | Esbiothrin | Profenofos | Methomyl | Glyphosate | Methamidophos | Chlorpyrifos | Mancozeb | Chlorothalonil | ||
M | M | 22 | 10.09 | |||||||
M | M | 11 | 5.05 | |||||||
M | M | 9 | 4.13 | |||||||
M | M | 8 | 3.67 | |||||||
M | M | 8 | 3.67 | |||||||
M | M | M | 7 | 3.21 | ||||||
M | M | M | 7 | 3.21 | ||||||
M | M | M | 7 | 3.21 | ||||||
M | M | 7 | 3.21 | |||||||
M | M | 6 | 2.75 | |||||||
M | M | 5 | 2.29 | |||||||
M | M | M | 4 | 1.83 | ||||||
Another pesticides | 116 | 53.68 |
Only main components of each mixture (M). Exposure to paraquat was based in results of urine concentrations, and exposure to other pesticide was self-reported.
There were more isolated reports of the use of profenofos and methomyl in Carmen de Viboral, and more of methamidophos, chlorpyrifos, mancozeb and chlorothalonil in Granada. There were fewer reports of the use of glyphosate in La Unión and fewer of profenofos in Granada. When exploring pesticide mixtures, a higher use of mixtures containing profenofos was reported in Carmen de Viboral and of those containing mancozeb in Granada.
In terms of an association between the pesticide mixtures (Table 3) and respiratory outcomes, the flu was observed to be associated with mixtures containing profenofos/methomyl, thoracic pain was associated with profenofos/methamidophos mixtures, allergic rhinitis with profenofos/glyphosate mixtures and obstructive pattern in spirometry with mixtures containing methamidophos. According to the job exposure matrix, paraquat was slightly associated with asthma.
Table 3. Adjusted prevalence ratios* (and 95% CI) of respiratory outcomes, chronic exposure to paraquat, and pesticide mixtures.
Respiratory outcomes | Paraquat (JEM)a | Municipalitiesb | Pesticide mixturesc | ||||||
---|---|---|---|---|---|---|---|---|---|
La Unión | Granada | 1 | 2 | 4 | 6 | 7 | 8 | ||
Cough | 1.00 (0.99–1.01) |
0.87 (0.63–1.19) |
0.52 (0.30–0.91) |
||||||
Fatigue | 1.00 (0.99–1.01) |
0.95 (0.65–1.39) |
0.36 (0.15–0.83) |
||||||
Flu | 0.99 (0.98–1.00) |
0.73 (0.45–1.18) |
0.74 (0.42–1.33) |
2.31 (1.60–3.34) |
|||||
Thoracic pain | 1.00 (0.98–1.02) |
0.93 (0.52–1.68) |
1.01 (0.49–2.08) |
4.07 (1.67–9.94) |
|||||
Dyspnea | 1.00 (0.99–1.02) |
0.58 (0.29–1.15) |
0.33 (0.11–1.01) |
||||||
Allergic rhinitis | 0.98 (0.95–1.01) |
2.48 (1.14–5.40) |
0.85 (0.19–3.80) |
2.70 (1.05–6.95) |
3.41 (1.19–9.72) |
||||
Obstructive pattern in spirometry | 1.02 (0.98–1.06) |
0.75 (0.19–2.99) |
0.85 (0.20–3.72) |
4.35 (1.08–17.52) |
|||||
Asthma | 1.06 (1.00–1.13) |
0.72 (0.08–6.62) |
0.00 (0.00–000) |
*Estimated with Poisson regressions with robust variance. aJEM: job exposure matrix [paraquat in urine concentrations (ng/ml) × months of exposure]; proxy of chronic exposure. bReference Carmen de Viboral, and adjusted by smoker status/former smoker. cMain pesticides in mixtures (always with paraquat): 1: with profenofos and methomyl; 2: with profenofos and methamidophos; 4: with profenofos; 6: with glyphosate; 7: with methamidophos, and 8: any other mixture.
Discussion
The findings from this study suggest that chronic exposure to paraquat is slightly associated with the occurrence of asthma. Associations were also observed between certain pesticide mixtures and the occurrence of respiratory disorders. It was interesting that chronic exposure to paraquat was slightly associated with asthma, and exposure to different pesticide mixtures were associated with flu, thoracic pain, allergic rhinitis, and obstructive pattern in spirometry. These findings demonstrate the importance of studying mixtures rather than individual pesticides, since exposure to a single pesticide is uncommon in agricultural work environments.
Although studies have reported an association between paraquat and asthma, the results have been contradictory. Toxicological studies have shown that different mechanisms could be associated with various adverse respiratory outcomes, including asthma. Respiratory absorption of paraquat is high in occupational exposure17). It destroys cell membranes and causes the formation of superoxide free radicals which are responsible for the pesticide’s toxicity. The free radicals generated during paraquat’s redox cycle can remove allylic hydrogen atoms from the polyunsaturated fatty acids in the membrane, damaging its structure and resulting in lipid peroxidation. Systemic toxicity is attributed to the destruction of the cellular membranes, with a selective action primarily in the lung at the level of type II pneumocytes18).
Studies about pesticide mixtures have used different methodological strategies, including multivariate statistical techniques such as principal components analysis19, 20), biplots21), risk indices based on accumulative exposure22) and qualitative comparative analyses based on set theory23). In general, these methods seem to be useful to explore the effect of short-term exposure. The experience from the present study is aimed at going beyond the use of job exposure matrices to study chronic exposure to paraquat and verbally reported pesticide mixtures. The association of chronic effects such as asthma with prolonged exposure to paraquat is of interest. In addition, moderate and serious poisoning results in the development of pulmonary fibrosis along with progressive dyspnea, decreased oxygen pressure and central cyanosis. For moderate and serious cases, pulmonary fibrosis typically results in the death of patients, and in a pattern of restrictive dysfunction for those who survive.
The interpretation of the findings should take into account the limitations inherent to the study design. As a cross-sectional study, the time period corresponding to the findings cannot be ensured. While attempting to simulate chronic exposure to paraquat using the job exposure matrix, this may not reflect actual exposure to the pesticide. Nevertheless, this study quantified biomarkers in urine, which was not often done in previous studies. It is important to remember that previous evidence has found that quantifying paraquat in a single micturition after exposure, as done by the present study, is highly correlated with quantifications using samples of 24-h urine24). Bias related to the health of the workers may also exist given the method used to recruit participants.
In conclusion, this study found a slightly association between chronic exposure to paraquat and asthma, and between several pesticide mixtures and particular spirometric symptoms and alterations. This suggests that workers exposed to mixtures containing paraquat should be closely monitored for respiratory disorders. In terms of the epidemiological methodology, future investigations that study pesticide mixtures using large sample sizes will make it possible to compare findings obtained from different statistical and mathematical methods in order to identify the most suitable method for measuring exposure.
Conflict of Interest
None declared.
Acknowledgments
The authors thank the workers who participated in the study and the environmental sanitation technicians at the Secretaries of Health in the municipalities of Carmen de Viboral, Granada and La Unión. The study was supported by the Colombian National Institute of Health and the Colombian Ministry of Health and Social Protection.
References
- 1.Wesseling C, van Wendel de Joode B, Ruepert C, León C, Monge P, Hermosillo H, Partanen TJ. (2001) Paraquat in developing countries. Int J Occup Environ Health 7, 275–86. [DOI] [PubMed] [Google Scholar]
- 2.Tsai WT. (2013) A review on environmental exposure and health risks of herbicide paraquat. Toxicol Environ Chem 95, 197–206. [Google Scholar]
- 3.Manktelow BW. (1967) The loss of pulmonary surfactant in paraquat poisoning: a model for the study of the respiratory distress syndrome. Br J Exp Pathol 48, 366–9. [PMC free article] [PubMed] [Google Scholar]
- 4.Arroyave ME .(1993) Pulmonary obstructive disease in a population using paraquat in Colombia. In: Forget G, Goodman T, de Villiers A (Eds.), Impact of pesticide use on health in developing countries. International Development Research Centre, Otawa. [Google Scholar]
- 5.Castro-Gutiérrez N, McConnell R, Andersson K, Pacheco-Antón F, Hogstedt C. (1997) Respiratory symptoms, spirometry and chronic occupational paraquat exposure. Scand J Work Environ Health 23, 421–7. [DOI] [PubMed] [Google Scholar]
- 6.Schenker MB, Stoecklin M, Lee K, Lupercio R, Zeballos RJ, Enright P, Hennessy T, Beckett LA. (2004) Pulmonary function and exercise-associated changes with chronic low-level paraquat exposure. Am J Respir Crit Care Med 170, 773–9. [DOI] [PubMed] [Google Scholar]
- 7.Fieten KB, Kromhout H, Heederik D, van Wendel de Joode B. (2009) Pesticide exposure and respiratory health of indigenous women in Costa Rica. Am J Epidemiol 169, 1500–6. [DOI] [PubMed] [Google Scholar]
- 8.Chatzi L, Alegakis A, Tzanakis N, Siafakas N, Kogevinas M, Lionis C. (2007) Association of allergic rhinitis with pesticide use among grape farmers in Crete, Greece. Occup Environ Med 64, 417–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Valcin M, Henneberger PK, Kullman GJ, Umbach DM, London SJ, Alavanja MC, Sandler DP, Hoppin JA. (2007) Chronic bronchitis among nonsmoking farm women in the agricultural health study. J Occup Environ Med 49, 574–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Cha ES, Lee YK, Moon EK, Kim YB, Lee YJ, Jeong WC, Cho EY, Lee IJ, Hur J, Ha M, Lee WJ. (2012) Paraquat application and respiratory health effects among South Korean farmers. Occup Environ Med 69, 398–403. [DOI] [PubMed] [Google Scholar]
- 11.Hankinson JL, Odencrantz JR, Fedan KB. (1999) Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med 159, 179–87. [DOI] [PubMed] [Google Scholar]
- 12.National Exposure Research Laboratory (1997) Office of Research and Development U.S. Environmental Protection Agency. Cincinnati, Ohio 45268. Method 549.2: Determination of diquat and paraquat in drinking water by liquid-solid extraction and high performance liquid chromatography with ultraviolet detection. Revision 1.0.
- 13.Hoar S. (1983) Job exposure matrix methodology. J Toxicol Clin Toxicol 21, 9–26. [DOI] [PubMed] [Google Scholar]
- 14.Anellis I. (2004) The genesis of the truth-table device. Russell J Bertrand Russell Stud 24, 55–70. [Google Scholar]
- 15.Parzen E. (2004) Quantile probability and statistical data modeling. Stat Sci 19, 652–62. [Google Scholar]
- 16.Barros AJ, Hirakata VN. (2003) Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol 3, 21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Baharuddin MR, Sahid IB, Noor MA, Sulaiman N, Othman F. (2011) Pesticide risk assessment: a study on inhalation and dermal exposure to 2,4-D and paraquat among Malaysian paddy farmers. J Environ Sci Health B 46, 600–7. [DOI] [PubMed] [Google Scholar]
- 18.Blanco-Ayala T, Andérica-Romero AC, Pedraza-Chaverri J. (2014) New insights into antioxidant strategies against paraquat toxicity. Free Radic Res 48, 623–40. [DOI] [PubMed] [Google Scholar]
- 19.Schilmann A, Lacasaña M, Blanco-Muñoz J, Aguilar-Garduño C, Salinas-Rodríguez A, Flores-Aldana M, Cebrián ME. (2010) Identifying pesticide use patterns among flower growers to assess occupational exposure to mixtures. Occup Environ Med 67, 323–9. [DOI] [PubMed] [Google Scholar]
- 20.Varona-Uribe ME, Torres-Rey CH, Díaz-Criollo S, Palma-Parra RM, Narváez DM, Carmona SP, Briceño L, Idrovo AJ. (2016) Exposure to pesticide mixtures and DNA damage among rice field workers. Arch Environ Occup Health 71, 3–9. [DOI] [PubMed] [Google Scholar]
- 21.Varona ME, Díaz-Criollo SM, Lancheros-Bernal AR, Murcia-Orjuela AM, Henao-Londoño GL, Idrovo AJ. (2010) Organochlorine pesticide exposure among agricultural workers in Colombian regions with illegal crops: an exploration in a hidden and dangerous world. Int J Environ Health Res 20, 407–14. [DOI] [PubMed] [Google Scholar]
- 22.Ragas AM, Oldenkamp R, Preeker NL, Wernicke J, Schlink U. (2011) Cumulative risk assessment of chemical exposures in urban environments. Environ Int 37, 872–81. [DOI] [PubMed] [Google Scholar]
- 23.Sánchez-Infante CI, Palma M, Carmona SP, Idrovo AJ, Ramírez JE. (2016) Un análisis comparativo cualitativo de signos y síntomas de intoxicación con mezclas a base de heptacloro. Acta Toxicol Argent 24, 2–9. [Google Scholar]
- 24.Park EK, Duarte Tagles H, Gee SJ, Hammock BD, Lee K, Schenker MB. (2008) Recruiting strategy and 24-hour biomonitoring of paraquat in agricultural workers. J Agromed 13, 207–17. [DOI] [PMC free article] [PubMed] [Google Scholar]