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Original Article
16 (
2
); 264-270
doi:
10.25259/JNRP_360_2024

Cognitive functional screening with the Indonesian Montreal Cognitive Assessment of farmers exposed to pesticides: A cross-sectional study

Faculty of Medicine, Faculty of Medicine, Universitas Islam Indonesia, Yogyakarta, Indonesia.
Department of Public Health, Faculty of Medicine, Universitas Islam Indonesia, Yogyakarta, Indonesia.
Department of Neurology, Faculty of Medicine, Universitas Islam Indonesia, Yogyakarta, Indonesia.

*Corresponding author: Sani Rachman Soleman, Department of Public Health, Faculty of Medicine, Universitas Islam Indonesia, Yogyakarta, Indonesia. sani.rachman@uii.ac.id

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Khoiriyah M, Ilhamsyah N, Putri AA, Soleman SR, Prasasti GD. Cognitive functional screening with the Indonesian Montreal Cognitive Assessment of farmers exposed to pesticides: A cross-sectional study. J Neurosci Rural Pract. 2025:16:264-70. doi: 10.25259/JNRP_360_2024

Abstract

Objectives:

Cognitive assessment with the Indonesian Montreal Cognitive Assessment (MoCA Ina) is essential to detect mild cognitive impairment in farmers in Indonesia. This study aims to observe cognitive function with the MoCa Ina in high-exposed and low-exposed areas in Magelang Regency, Central Java, Indonesia.

Materials and Methods:

A cross-sectional study is proposed to collect 101 respondents from Pakis District, high-exposed pesticides, and 100 respondents from Mertoyudan District, low-exposed ones. Covariates are baseline demographic and pesticide-use behavior, and dependent variables are exposure level and MoCA Ina components. Statistical analysis uses chi-square and Binary Logistic for categorical data. Independent t-tests, analysis variance, and covariance analysis are used to analyze continuous data. All data are set at <0.05 significance with the Statistical Package for the Social Sciences version 25.

Results:

Elementary school (adjusted odd ratio [AOR] = 0.43; confidence interval [CI] 95% = 0.07, 0.27; P = 0.00) and junior high school (AOR = 0.11; CI 95% = 0.01, 0.74; P = 0.02) are associated with exposure status, as well as MoCA Ina components exclusively visuospatial (P < 0.001), naming (P < 0.001), abstraction (P = 0.00), delayed recall (P = 0.02), and total MoCA (P = 0.00). However, after controlling for confounding, only orientation finds its significance (mean difference 0.20, P = 0.04). The mean difference proves that the high-exposed area has a worse score MoCA than the low-exposed pesticide one. Specifically, in highly exposed one, pesticide use behavior, broflanilide pesticide application (P = 0.02), length of used pesticide (P = 0.01), and spraying time (P = 0.00) get their significance. Wearing glass protection contributes to cognitive scoring MoCA Ina components such as naming (P < 0.001), language (P = 0.02), abstraction (P = 0.02), orientation (P = 0.00), and total MoCA (P = 0.01).

Conclusion:

Pesticide exposure contributes to cognitive function. Additional precautions regarding educational background, pesticide-use behavior, and personal protective equipment compliance should be handled.

Keywords

Cognitive function
Magelang regency
MoCA Ina
Pesticide exposure

INTRODUCTION

The utilization of pesticides globally has reached two million tons, comprising 51% herbicide, 20% fungicide, 19% insecticide, and the remaining other pesticides.[1] The most utilized pesticides are in China, the United States of America, Argentina, Thailand, Brazil, and India.[2] The global trend of pesticide application from 1990 to 2022 sharply increased and is estimated to double from the baseline trend.[2] This condition will persist due to the increasing pesticide export in low-middle-income countries and the exacerbating agricultural land.[3]

Driven by the utilization of pesticides, environmental contamination drives ecosystem imbalance and thus potentially induces health problems. The highest environmental risk in Benin was caused by carbofuran, chlorpyrifos, and endosulfan polluted water and lake.[4] Recently, the European Union banned the importation of fish from the Winam Gulf due to its contamination with endosulfan.[5] Leaching pesticides in the groundwater and contaminated drinking water caused by malathion and dieldrin in Ganger Rivers, India, imposed human health.[6] A report from Australia showed that triazine herbicide was detected in water streams with median concentrations of 2.85 ug/L.[7] Potential hazards from this contamination seriously affect marine biota and human life.

Pesticide poisoning in humans has become a concern recently. An adverse effect that occurred in the exposed population was cognitive impairment. Most pesticides, such as organophosphate and carbamate classes, work in neuromuscular junctions in the synaptic cleft to inhibit substantial enzyme cholinesterase to produce acetylcholine.[8] Other pesticide classes, endosulfan and chlordane, belong to the organochlorine, inhibit the GABA-gate chloride channel and the pyrethroid class to block sodium channel modulators.[8] These cumulative actions of pesticides cause mild to severe cognitive function among farmers. A complete and comprehensive assessment is beneficial for screening cognitive function through the specific instrument, the Montreal Cognitive Assessment (MoCA). Studies were published on the sensitivity MoCA to detect mild cognitive impairment in even less educated persons, with a sensitivity of 86% and specificity of 75% for an illiterate person.[9,10] Similarly, the Indonesian Montreal Cognitive Assessment (MoCA Ina) has been verified to detect mild cognitive impairment in post-stroke patients[11] and schizophrenia.[12] Since pesticides have proven to cause substance-induced cognitive decline, the MoCA Ina instrument is used to screen farmers for cognitive problems exposed to those harmful substances.

Driven concern about the effect on cognitive function, Magelang Regency in Central Java Province, Indonesia, is an agricultural region where most of the population works as farmers. Pesticide exposure to health outcomes such as neurological disorders,[13] nail problems,[14] and cumulative exposure to chlorpyrifos[15] is commonly evaluated among farmers. However, specific assessment using MoCA Ina is limited. Since the spreading of pesticides in agricultural and household areas is continuing globally, potential cognitive impairments could be minimized by MoCA Instruments. This study aims to examine pesticide exposure to cognitive functions by the MoCA Ina in farmers in Indonesia. This regional data in Magelang Regency, Indonesia, could be insightful to provide a contribution globally in the assessment of pesticide exposure with cognitive dysfunction in farmers.

MATERIALS AND METHODS

Study population

This cross-sectional study selected respondents in high and low-exposed areas of Magelang Regency, Central Java Province, Indonesia. High exposure was defined as a high-exposed community to pesticides in Pakis District, and low exposure was verified as a low-exposed one in Mertoyudan District. Both districts were selected due to occupational status in Pakis District being dominated by farmers and Mertoyudan District being private sectors.[16,17] A convenience sampling method was used to collect the respondents based on the formula below:[18]

Zα22P1P+ZβP11P1+P21P22P1P22

P: Proportion in population, P1: Proportion in exposed group, P2: Proportion in non-exposed group, Zα: Z-score for significance level, Zβ: Z-score for power.

Where P1 = 0.55, P2 = 0.36, P = 0.73, Zα = 1.96, and Zβ = 0.84. The prevalence of cognitive decline due to pesticide exposure was taken from Tiwari et al., study.[19] According to sample size calculations, 92 respondents for each high and low exposure to pesticides were obtained in this study. However, we added 100 samples in high-exposed and 101 samples in low-exposed pesticide to anticipate drop-out participants. Thus, the total number of participants for high and low-exposed pesticides was 201. The inclusion criteria in high exposed were primary occupation as farmers who lived in Pakis district for at least 1 year, and the low-exposed area included non-farmers workers. We used farmers’ occupation as the primary parameter exposure to omit sampling bias in exposure assessment. Informed consent was obtained by signing a form witnessed by a family member. Ethical clearance was proposed to the Ethical Committee, Faculty of Medicine Universitas Islam Indonesia, number 9/Ka.Kom.Et/70/KE/VII/2023.

Covariates

Baseline demographics such as age, gender, education, occupation, length of work, work duration, and smoking status were covariates. In addition, pesticide use behavior was stated by type, length of use pesticide, mixing, spraying, farming frequency, personal protective equipment (PPE) wearing, and type of PPE. Both data were obtained from the questionnaire. Age variables were stratified into three categories: 18–30, 31–40, and 41–55. In addition, educational background was stratified into no education, elementary, junior high school, senior high school, and university. Occupation status was ordered by farmers, the private sector, civil servants, and no occupation included household wives.

Cognitive assessment

Three trained assistants were assigned to perform MoCA Ina, supervised by a neurologist. The MoCA Ina consists of 13 test items covering five domains, namely visuospatial and executive function consisting of three parts; attention consisting of three parts; language consisting of two parts; and naming, memory, abstraction, delayed recall, and orientation, consisting of one part. The maximum examination score is 30 points, where 26–30 is normal, and below 26 is denoted cognitive dysfunction. The adjustment for individuals with low education, below 12 years of education, is by adding a point. We analyzed every component and total MoCA Ina score to obtain which specific cognitive test components were affected by pesticide exposure. This instrument is widely used in Indonesia to evaluate cognitive function.[11,12] The validity and reliability of MoCA Ina for detecting mild cognitive impairment have a sensitivity of 90–96% and a specificity of 87–95%.[11]

Statistical analysis

Descriptive analysis was visualized using a distribution and frequency table. Categorical data were presented by number and percentage and continuous data by mean and standard deviation (SD). Chi-square and binary logistics conducted an association between covariates and level of exposure for categorical and independent t-tests or analysis of variance (ANOVA) for continuous scale with two groups and more than two groups if data were normally distributed with Kolmogorov–Smirnov test. Bonferroni post hoc analysis was selected to capture the significant difference between the groups in ANOVA analysis.[20] Analysis covariance (ANCOVA) was also performed to find which MoCA Ina components were related to exposure level (high and low-exposed) by controlling covariates including age, gender, educational background, occupational status, and smoking status. All statistical data were presented in P-value, odd ratio, and adjusted odd ratio (AOR) to control confounding as well as age stratification,[21] with 95% confidence interval (CI) and setting up at <0.05 was statistically significance. Statistical analysis was conducted using the Statistical Package for the Social Sciences version 25.

RESULT

Our study finds that most respondents in both areas are female, approximately 50%. The high-exposed areas are dominated by 31–40 year old, which is equal to 43% and the low-exposed areas are mostly 18–30 year old or 37%. Educational background in high-exposed areas is mostly graduated from elementary school at 60%, and 46% in low-exposed areas are graduated from senior high school. Occupational status is 99% for farmers and the private sector in high-exposed versus low-exposed areas, respectively. Length of work is 73% over 10 years, and 41% is below 10 years in high-exposed versus low-exposed. We obtain that missing data in the low-exposed are 29% in the length of work variable and 53% in the work duration variable due to the household wife as a primary occupation. Working duration <7 h in high-exposed is 77%. Smoking status is also more than 60% in both areas. A detailed description of baseline characteristics is reported in Table 1.

According to pesticide-use behavior, profenofos, abamectin, and mancozeb are the most applied pesticides in high-exposed, as presented in Figure 1. Length of used pesticide is more than 5 years (69.3%); mixing pesticide every 1–2 days in a week (82.2%); spraying pesticide every 1–2 days in a week (83.2%); everyday farming frequency (87.1%); constantly wearing PPE (50.5%); and long sleeve, hat, and mask are the most wore PPE in farmers (93.1%, 91.1%, and 87.1%, respectively) (data were not shown). Overall, MoCA Ina components in the high-exposed areas are lower than those in the low-exposed areas (the mean difference ranged from 0.20 for orientation to 2.40 for total MoCA Ina). A detailed MoCA Ina comparison of high and low-exposed pesticides has been shown in Table 1.

Table 1: Baseline characteristics of respondents in high-exposed and low-exposed pesticide.
Variables High-exposed (n=101) Low-exposed (n=100)
n(%) n(%)
Gender
  Male 49 (49.49) 44 (44)
  Female 52 (52.52) 56 (56)
Age
  18–30 years old 34 (34.34) 37 (37)
  31–40 years old 43 (43.43) 35 (35)
  41–55 years old 24 (24.24) 28 (28)
Education
  No education 2 (2.2) 1 (1)
  Elementary 59 (59.59) 16 (16)
  Junior high school 30 (30.30) 24 (24)
  Senior high school 8 (8.8) 46 (46)
  University 2 (2.2) 13 (13)
Occupation
  Farmers 99 (99.99) 0 (0)
  Civil servant 2 (2.2) 4 (4)
  Private sector 0 (0) 65 (65)
  No occupation 0 (0) 31 (31)
Length of work
  <10 years 28 (28.28) 41 (41)
  ≥10 years 73 (73.73) 30 (30)
  Missing data 29 (29)
Work duration
  <7 h 77 (77.77) 24 (24)
  ≥7 h 24 (24.24) 23 (23)
  Missing data 53 (53)
Smoking
  Yes 38 (38.38) 33 (33)
  No 63 (63.63) 67 (67)
Mean±SD Mean±SD
Visuospatial 1.96±1.17 2.74±1.32
Naming 2.58±0.86 2.91±0.32
Attention 4.07±1.35 4.40±1.59
Language 1.63±0.90 1.90±1.03
Abstraction 0.63±0.77 0.97±0.78
Delayed recall 1.50±1.82 2.11±1.90
Orientation 5.34±0.92 5.54±0.83
MoCA 18.6±4.87 21.0±5.00

MoCA: Montreal Cognitive Assessment, SD: Standard deviation

The association between covariates and exposure status is evaluated in Table S1. This finding summarizes that elementary school, junior high school, and work duration < 7 years are associated with exposure level (AOR = 0.43; CI 95% = 0.07, 0.27; AOR = 0.11, CI 95% = 0.01, 0.74; AOR = 2.72, CI 95%=1.11, 6.66, respectively). In addition, MoCA Ina components are only visuospatial, naming abstraction, delayed recall, and total MoCA obtained their significance.

Supplementary Material

Association between MoCA Ina components with status exposure by controlling age, gender, educational background, occupational status, and smoking status is found that only the orientation component obtained its significance (mean difference 0.20, P = 0.04), as presented in Table 2.

We evaluate pesticide use behavior in the high-exposed areas and obtain that the abstraction component is associated with broflanilide pesticide (P = 0.02), length of used pesticide (P = 0.01), wearing gloves (P = 0.04), and protection glass (P = 0.02). Length of use pesticide >5 years and <1 year provides significant differences between groups (P = 0.01; CI 95% = 0.17, 1.61). Delayed recall correlates with spraying pesticide (P = 0.00), where spraying 1–2 days a week and 3–4 days a week provide significant differences between groups (P = 0.004; CI 95% = 0.69, 3.60). The naming component obtains its significance by wearing protection glass (P < 0.001) and long-sleeved (P = 0.00); other components, such as language (P = 0.02), orientation (P = 0.00), and total MoCA (P = 0.01), correlate with wearing protection glass. A detailed of this finding is illustrated in Table S2.

DISCUSSION

Studies of pesticide exposure to cognitive function using MoCA were limited. Two studies were performed in Thailand and South Korea using translated MoCA. In the Thailand study, pre-application versus post-application pesticides significantly affected MoCA score, 21.25 ± 4.02 versus 17.51 ± 3.90, respectively.[22] Another study in South Korea examined cognitive decline (MoCA score <23) in farmers (AOR = 1.49; CI 95% = 0.59, 3.78) and pesticide application (AOR = 1.51; CI 95% = 0.62, 3.68).[23] The present study compared high-exposed and low-exposed cognitive functions with MoCA Ina components in Magelang Regency, Central Java, Indonesia.

Among covariates, elementary and junior high school were associated with level of exposure for several reasons. In high-exposed areas, most respondents had an educational level at elementary that was considered low-educated compared to low-exposed areas where most respondents graduated from senior high school. The association between education background and exposure level was statistically significant. Educational background, however, is an important component for cognitive function through MoCA Ina examination, where low-educated people are more challenging to recognize the procedure, as well as low compliance with wearing PPE compared to knowledgeable ones. The Statistic Bureau Magelang Regency reported that most population in Pakis District were farmers with low-level education. Most people in Mertoyudan District were private sector workers with medium and higher-level education.[17] Gaber and Abdel-Latif ’ study claimed that higher education among farmers was more knowledgeable and compliant with the adverse effects of pesticide precautions, taking precautions after contacting pesticides, and reading label containers for safety.[24] Another covariate was work duration <7 h, which proved a robust correlation with exposure level. We assumed that almost 80% of respondents in Pakis were farmers who work around 7–8 h every day while most respondents in low-exposed were household wives.

The number of pesticides (percentage) used in high-exposed areas (n = 101), n: Sample size.
Figure 1:
The number of pesticides (percentage) used in high-exposed areas (n = 101), n: Sample size.
Table 2: Association between MoCA components on exposure level.
MoCA components High-exposed (n=101) Low-exposed (n=100) Mean difference P-value
Mean±SD Mean±SD
Visuospatial 1.96±1.17 2.74±1.32 0.78 0.50
Naming 2.58±0.86 2.91±0.32 0.33 0.24
Attention 4.07±1.35 4.40±1.59 0.33 0.84
Language 1.63±0.90 1.90±1.03 0.27 0.62
Abstraction 0.63±0.77 0.97±0.78 0.34 0.34
Delayed recall 1.50±1.82 2.11±1.90 0.61 0.74
Orientation 5.34±0.92 5.54±0.83 0.20 0.04*
MoCA 18.6±4.87 21.0±5.00 2.40 0.59

Analysis covariance (ANCOVA) adjusted with age, gender, occupation, educational background, and smoking status. The mean difference indicated that low-exposed preferred higher MoCA results compared to high-exposed. Asterisk indicated statistically significant at <0.05. MoCA: Montreal Cognitive Assessment, SD: Standard deviation

We obtained data that no MoCA Ina components, except for orientation, were associated with exposure level after controlling potential confoundings. Orientation is managed by a specific brain system of cortical activity inside the precuneus and inferior parietal lobe, with space orientation activating the posterior region, followed anteriorly by person and time orientation.[25] The pesticide most commonly applied in this study was profenofos, which affects cortical activity in the parietal lobe, as reported by Sagiv et al.[26] Their study examined 95 respondents’ proximity to pesticide application, and two points were found there. First, organophosphate exposure was associated with cortical activation during executive functioning and language comprehension assignments. Second, the maternal lived 1 km from pesticide application; there was bilateral decreasing brain activation in the prefrontal cortex in both hemispheres.[26] However, our finding was not only concerning profenofos but also other pesticides such as abamectin, broflanilide, and fungicide mancozeb, which frequently existed in agricultural land. Thus, this scenario would be worse due to cumulative poisoning in the real setting in a high-exposed area.

We assessed specific MoCA Ina related to pesticide application behavior in high-exposed areas where abstraction and delayed recall got their significance. This finding suggested that broflanilide pesticide, as a GABA-gated chloride channel allosteric modulator,[8] was working almost similar mechanism like profenofos in the cortical region. We also noticed that more often spraying pesticides and the length of application could be more cumulative in the neuron system and was posing farmers with cognitive problems. Another finding in this study was concerned with PPE applications. Protection glass correlated with some MoCA Ina components, followed by wearing long sleeves and gloves. However, we could not verify the interaction between two variables, whether application PPE protects from cognitive function and vice versa. A similar but different result was noticed in Chittrakul et al., study that wearing PPE offered increasing levels of urinary metabolite pesticide, particularly wearing gloves and masks.[22] It is imperative to note that wearing PPE was accompanied by training appropriately to wear them, and compliance with wearing PPE during farming, mixing, and spraying was warranted to minimize exposure.[27]

Limitations

This study has several limitations. First, we could not examine the causal relationship between variables due to study design bias.[28] Further evaluation should be performed using a robust method such as a cohort study.[29] Second, the interaction between the two variables was unlikely to be verified. This essential analysis captures which one variable affects another one. Third, we argued that the mean and SD in the low-exposed area (21 ± 5.0) were below the scoring value of MoCA Ina at 26.[30] We assumed that several factors contributed to this phenomenon. Occupational or environmental factors in the low-exposed area should have been proven for further evaluation. MoCA Ina assessment required a tranquil environment and respondents’ preparedness for tiredness, sickness, emotional condition, and occupational tasks.[31] Respondents should focus on the instructions given by examiners. We used low-exposed groups to compare exposure levels of pesticides. Thus, healthy control individuals overestimated the specificity of the MoCA test.[32]

CONCLUSION

Low education background and work duration above 7 years are demographic factors in pesticide exposure. The MoCA Ina components in high-exposed areas are slightly lower than in low-exposed ones. However, only visuospatial, naming, abstraction, delayed recall, and total MoCA are linked to exposure status. After controlling for potential confounding, only orientation finds its significance; the remaining MoCA Ina components are none. Specifically in a high-exposed area, few pesticide applications, such as broflanilide, length of pesticide used, and spraying time, correspond to declining abstraction and delayed recall tests. In addition, wearing protective glasses is significant in the association with cognitive function in farmers, including naming, language, abstraction, orientation, and total MoCA. This study proves that pesticide exposure exists to cause cognitive impairment. Proposing a multi-sectoral tie to control pesticide application is essential to protect the environment and humans.

Authors’ contributions:

MK: Funding acquisition, collecting data, writing manuscript. NI: Collecting data, writing manuscript. AABP: Collecting data, writing manuscript. SRS: Conceptualization, formal analysis, review. GDP: Review, formal analysis.

Ethical approval:

The research/study was approved by the Institutional Review Board at the Ethical Committee, Faculty of Medicine Universitas Islam Indonesia, number 9/Ka.Kom.Et/70/ KE/VII/2023, dated July 2, 2023.

Declaration of patient consent:

The authors certify that they have obtained all appropriate patient consent.

Conflicts of interest:

There are no conflicts of interest.

Use of artificial intelligence-assisted technology for manuscript preparation:

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Financial support: This study was funded by Program Kreativitas Mahasiswa (PKM) from the Ministry of Higher Education, Republic of Indonesia.

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