Pesticides play a key role in rural agriculture, but their excessive or misuse can negatively impact malaria vector control policies; This study was conducted among farming communities in southern Côte d’Ivoire to determine which pesticides are used by local farmers and how this relates to farmers’ perceptions of malaria. Understanding pesticide use can help develop awareness programs about mosquito control and pesticide use.
The survey was conducted among 1,399 households in 10 villages. Farmers were surveyed about their education, farming practices (e.g., crop production, pesticide use), perceptions of malaria, and the various household mosquito control strategies they use. The socioeconomic status (SES) of each household is assessed based on some predetermined household assets. Statistical relationships between various variables are calculated, showing significant risk factors.
Farmers’ educational level is significantly associated with their socioeconomic status (p < 0.0001). Most households (88.82%) believed that mosquitoes are the main cause of malaria and knowledge of malaria was positively associated with higher education level (OR = 2.04; 95% CI: 1.35, 3.10). Indoor chemical use was significantly associated with household socioeconomic status, education level, use of insecticide-treated bed nets and agricultural insecticides (p < 0.0001). Farmers have been found to use pyrethroid insecticides indoors and use these insecticides to protect crops.
Our study shows that educational level remains a key factor influencing farmers’ awareness of pesticide use and malaria control. We recommend that improved communication targeting educational attainment, including socioeconomic status, availability, and access to controlled chemical products be considered when developing pesticide management and vector-borne disease management interventions for local communities.
Agriculture is the main economic driver for many West African countries. In 2018 and 2019, Côte d’Ivoire was the world’s leading producer of cocoa and cashew nuts and the third largest coffee producer in Africa [1], with agricultural services and products accounting for 22% of gross domestic product (GDP) [2] . As the owners of most agricultural land, smallholders in rural areas are the main contributors to the economic development of the sector [3]. The country has enormous agricultural potential, with 17 million hectares of farmland and seasonal variations favoring crop diversification and the cultivation of coffee, cocoa, cashew nuts, rubber, cotton, yams, palm, cassava, rice and vegetables [2]. Intensive agriculture contributes to the spread of pests, mainly through increased use of pesticides for pest control [4], especially among rural farmers, to protect crops and increase crop yields [5], and to control mosquitoes [6]. However, inappropriate use of insecticides is one of the main causes of insecticide resistance in disease vectors, especially in agricultural areas where mosquitoes and crop pests may be subject to selection pressure from the same insecticides [7,8,9,10]. Pesticide use can cause pollution that impacts vector control strategies and the environment and therefore requires attention [ 11 , 12 , 13 , 14 , 15 ].
Pesticide use by farmers has been studied in the past [5, 16]. Level of education has been shown to be a key factor in the correct use of pesticides [17, 18], although pesticide use by farmers is often influenced by empirical experience or recommendations from retailers [5, 19, 20]. Financial constraints are one of the most common barriers limiting access to pesticides or insecticides, leading farmers to purchase illegal or obsolete products, which are often less expensive than legal products [21, 22]. Similar trends are observed in other West African countries, where low income is a reason for purchasing and using inappropriate pesticides [23, 24].
In Côte d’Ivoire, pesticides are widely used on crops [ 25 , 26 ], which impacts agricultural practices and malaria vector populations [ 27 , 28 , 29 , 30 ]. Studies in malaria-endemic areas have shown an association between socioeconomic status and perceptions of malaria and infection risks, and the use of insecticide-treated bed nets (ITN) [31,32,33,34,35,36,37] . Despite these studies, efforts to develop specific mosquito control policies are undermined by a lack of information about pesticide use in rural areas and the factors that contribute to proper pesticide use. This study examined malaria beliefs and mosquito control strategies among agricultural households in Abeauville, southern Côte d’Ivoire.
The study was carried out in 10 villages in the Abeauville department in southern Côte d’Ivoire (Fig. 1). Agbowell Province has 292,109 inhabitants in an area of 3,850 square kilometers and is the most populous province in the Anyebi-Tiasa region [38]. It has a tropical climate with two rainy seasons (April to July and October to November) [39, 40]. Agriculture is the main activity in the region and is carried out by small farmers and large agro-industrial companies. These 10 locations include Aboude Boa Vincent (323,729.62 E, 651,821.62 N), Aboude Kuassikro (326,413.09 E, 651,573.06 N), Aboude Mandek (326,413.09 E , 651573.06N) Abude) (330633.05E, 652372.90N), Amengbeu (348477.76E, 664971.70N), Damojiang (374,039.75 E, 661,579.59 N), Casigue 1 (363,140.15 E, 634,256.47 N), Lovezzi 1 (351,545.32 E ., 642.06 2.37 N), Ofa (350 924.31 E, 654 607.17 N), Ofonbo (338 578.5) 1 E, 657 302.17 north latitude) and Uji (363,990.74 east longitude, 648,587.44 north latitude).
The study was conducted between August 2018 and March 2019 with the participation of farming households. The total number of residents in each village was obtained from the local service department, and 1,500 people were randomly selected from this list. Participants recruited represented between 6% and 16% of the village population. Households included in the study were those farming households that agreed to participate. A preliminary survey was conducted among 20 farmers to assess whether some questions needed to be rewritten. The questionnaires were then completed by trained and paid data collectors in each village, at least one of whom was recruited from the village itself. This choice ensured that each village had at least one data collector who was familiar with the environment and spoke the local language. In each household, a face-to-face interview was conducted with the head of the household (father or mother) or, if the head of the household was absent, another adult over 18 years of age. The questionnaire contained 36 questions divided into three sections: (1) Demographic and socio-economic status of the household (2) Agricultural practices and use of pesticides (3) Knowledge of malaria and the use of insecticides for mosquito control [see Annex 1].
Pesticides mentioned by farmers were coded by trade name and classified by active ingredients and chemical groups using the Ivory Coast Phytosanitary Index [41]. The socioeconomic status of each household was assessed by calculating an asset index [42]. Household assets were converted into dichotomous variables [43]. Negative factor ratings are associated with lower socioeconomic status (SES), whereas positive factor ratings are associated with higher SES. Asset scores are summed to produce a total score for each household [35]. Based on the total score, households were divided into five quintiles of socioeconomic status, from the poorest to the richest [see Additional file 4].
To determine whether a variable differs significantly by socioeconomic status, village, or educational level of household heads, the chi-square test or Fisher’s exact test can be used, as appropriate. Logistic regression models were fitted with the following predictor variables: education level, socioeconomic status (all transformed into dichotomous variables), village (included as categorical variables), high level of knowledge about malaria and pesticide use in agriculture, and pesticide use indoors (output via aerosol). or coil); educational level, socio-economic status and village, resulting in high awareness of malaria. A logistic mixed regression model was performed using the R package lme4 (Glmer function). Statistical analyzes were performed in R 4.1.3 (https://www.r-project.org) and Stata 16.0 (StataCorp, College Station, TX).
Of the 1,500 interviews conducted, 101 were excluded from analysis because the questionnaire was not completed. The highest proportion of households surveyed was in Grande Maury (18.87%) and the lowest in Ouanghi (2.29%). The 1,399 surveyed households included in the analysis represent a population of 9,023 people. As shown in Table 1, 91.71% of household heads are male and 8.29% are female.
About 8.86% of household heads came from neighboring countries such as Benin, Mali, Burkina Faso and Ghana. The most represented ethnic groups are Abi (60.26%), Malinke (10.01%), Krobu (5.29%) and Baulai (4.72%). As expected from the sample of farmers, agriculture is the only source of income for the majority of farmers (89.35%), with cocoa being grown most frequently in the sample households; Vegetables, food crops, rice, rubber and plantain are also grown on a relatively small area of land. The remaining heads of households are businessmen, artists and fishermen (Table 1). A summary of household characteristics by village is presented in the Supplementary file [see Additional file 3].
Education category did not differ by gender (p = 0.4672). Most of the respondents had primary school education (40.80%), followed by secondary education (33.41%) and illiteracy (17.97%). Only 4.64% entered university (Table 1). Of the 116 women surveyed, more than 75% had at least a primary education, and the rest had never attended school. The educational level of farmers varies significantly across villages (Fisher’s exact test, p < 0.0001), and the educational level of household heads is significantly positively correlated with their socioeconomic status (Fisher’s exact test, p < 0.0001). In fact, the higher socioeconomic status quintiles mostly consist of more educated farmers, and conversely, the lowest socioeconomic status quintiles consist of illiterate farmers; Based on total assets, sample households are divided into five wealth quintiles: from the poorest (Q1) to the richest (Q5) [see Additional file 4].
There are significant differences in the marital status of heads of households of different wealth classes (p < 0.0001): 83.62% are monogamous, 16.38% are polygamous (up to 3 spouses). No significant differences were found between wealth class and number of spouses.
The majority of respondents (88.82%) believed that mosquitoes are one of the causes of malaria. Only 1.65% responded that they did not know what causes malaria. Other identified causes include drinking dirty water, exposure to sunlight, poor diet and fatigue (Table 2). At the village level in Grande Maury, the majority of households considered drinking dirty water to be the main cause of malaria (statistical difference between villages, p < 0.0001). The two main symptoms of malaria are high body temperature (78.38%) and yellowing of the eyes (72.07%). Farmers also mentioned vomiting, anemia and pallor (see Table 2 below).
Among the malaria prevention strategies, respondents mentioned the use of traditional medicines; however, when sick, both biomedical and traditional malaria treatments were considered viable options (80.01%), with preferences related to socioeconomic status. Significant correlation (p < 0.0001). ): Farmers with higher socioeconomic status preferred and could afford biomedical treatments, farmers with lower socioeconomic status preferred more traditional herbal treatments; Almost half of households spend on average more than 30,000 XOF per year on malaria treatment (negatively associated with SES; p < 0.0001). Based on self-reported direct cost estimates, households with the lowest socioeconomic status were more likely to spend XOF 30,000 (approximately US$50) more on malaria treatment than households with the highest socioeconomic status. In addition, the majority of respondents believed that children (49.11%) are more susceptible to malaria than adults (6.55%) (Table 2), with this view being more common among households in the poorest quintile (p < 0.01) .
For mosquito bites, the majority of participants (85.20%) reported using insecticide-treated bed nets, which they mostly received during the 2017 national distribution. Adults and children were reported to sleep under insecticide-treated mosquito nets in 90.99% of households. The frequency of household use of insecticide-treated bed nets was above 70% in all villages except Gessigye village, where only 40% of households reported using insecticide-treated bed nets. The average number of insecticide-treated bed nets owned by a household was significantly and positively correlated with household size (Pearson’s correlation coefficient r = 0.41, p < 0.0001). Our results also showed that households with children under 1 year of age were more likely to use insecticide-treated bed nets at home compared with households without children or with older children (odds ratio (OR) = 2.08, 95% CI : 1.25–3.47).
In addition to using insecticide-treated bed nets, farmers were also asked about other mosquito control methods in their homes and on agricultural products used to control crop pests. Only 36.24% of participants mentioned spraying pesticides in their homes (significant and positive correlation with SES p < 0.0001). The chemical ingredients reported were from nine commercial brands and were mainly supplied to local markets and some retailers in the form of fumigating coils (16.10%) and insecticide sprays (83.90%). Farmers’ ability to name the names of pesticides sprayed on their houses increased with their level of education (12.43%; p < 0.05). The agrochemical products used were initially purchased in canisters and diluted in sprayers prior to use, with the largest proportion typically destined for crops (78.84%) (Table 2). Amangbeu village has the lowest proportion of farmers using pesticides in their homes (0.93%) and crops (16.67%).
The maximum number of insecticidal products (sprays or coils) claimed per household was 3, and SES was positively correlated with the number of products used (Fisher’s exact test p < 0.0001, however in some cases these products were found to contain the same); active ingredients under different trade names. Table 2 shows the weekly frequency of pesticide use among farmers according to their socioeconomic status.
Pyrethroids are the most represented chemical family in household (48.74%) and agricultural (54.74%) insecticide sprays. Products are made from each pesticide or in combination with other pesticides. Common combinations of household insecticides are carbamates, organophosphates and pyrethroids, while neonicotinoids and pyrethroids are common among agricultural insecticides (Appendix 5). Figure 2 shows the proportion of different families of pesticides used by farmers, all of which are classified as Class II (moderate hazard) or Class III (slight hazard) according to the World Health Organization classification of pesticides [44]. At some point, it turned out that the country was using the insecticide deltamethrin, intended for agricultural purposes.
In terms of active ingredients, propoxur and deltamethrin are the most common products used domestically and in the field, respectively. Additional file 5 contains detailed information on chemical products used by farmers at home and on their crops.
Farmers mentioned other mosquito control methods, including leaf fans (pêpê in the local Abbey language), burning leaves, cleaning the area, removing standing water, using mosquito repellents, or simply using sheets to repel mosquitoes.
Factors associated with farmers’ knowledge of malaria and indoor insecticide spraying (logistic regression analysis).
Data showed a significant association between household insecticide use and five predictors: educational level, SES, knowledge of mosquitoes as a major cause of malaria, ITN use, and agrochemical insecticide use. Figure 3 shows the different ORs for each predictor variable. When grouped by village, all predictors showed a positive association with the use of insecticide sprays in households (except knowledge of the main causes of malaria, which was inversely associated with insecticide use (OR = 0.07, 95% CI: 0.03, 0.13) . )) (Figure 3). Among these positive predictors, an interesting one is the use of pesticides in agriculture. Farmers who used pesticides on crops were 188% more likely to use pesticides at home (95% CI: 1.12, 8.26). However, households with higher levels of knowledge about malaria transmission were less likely to use pesticides in the home. People with higher levels of education were more likely to know that mosquitoes are the main cause of malaria (OR = 2.04; 95% CI: 1.35, 3.10), but there was no statistical association with high SES (OR = 1.51; 95% CI: 0.93, 2.46).
According to the head of the household, the mosquito population peaks during the rainy season and night time is the time of the most frequent mosquito bites (85.79%). When farmers were asked about their perception of the impact of insecticide spraying on malaria-carrying mosquito populations, 86.59% confirmed that mosquitoes appear to be developing resistance to insecticides. The inability to use adequate chemical products due to their unavailability is considered the main reason for the ineffectiveness or misuse of products, which are considered to be other determining factors. In particular, the latter was associated with lower educational status (p < 0.01), even when controlling for SES (p < 0.0001). Only 12.41% of respondents considered mosquito resistance as one of the possible causes of insecticide resistance.
There was a positive correlation between the frequency of insecticide use at home and the perception of mosquito resistance to insecticides (p < 0.0001): reports of mosquito resistance to insecticides were mainly based on the use of insecticides at home by farmers 3–4 times a week (90.34%) . In addition to frequency, the amount of pesticides used was also positively correlated with farmers’ perceptions of pesticide resistance (p < 0.0001).
This study focused on farmers’ perceptions of malaria and pesticide use. Our results indicate that education and socioeconomic status play a key role in behavioral habits and knowledge about malaria. Although most household heads attended primary school, as elsewhere, the proportion of uneducated farmers is significant [35, 45]. This phenomenon can be explained by the fact that even if many farmers begin to receive education, most of them have to drop out of school to support their families through agricultural activities [26]. Rather, this phenomenon highlights that the relationship between socioeconomic status and education is critical to explaining the relationship between socioeconomic status and the ability to act on information.
In many malaria-endemic regions, participants are familiar with the causes and symptoms of malaria [33,46,47,48,49]. It is generally accepted that children are susceptible to malaria [31, 34]. This recognition may be related to the susceptibility of children and the severity of malaria symptoms [50, 51].
Participants reported spending an average of $30,000, not including transportation and other factors.
A comparison of farmers’ socioeconomic status shows that farmers with the lowest socioeconomic status spend more money than the richest farmers. This may be because households with the lowest socioeconomic status perceive costs to be higher (due to their greater weight in overall household finances) or because of the associated benefits of public and private sector employment (as is the case with more rich households). ): Due to the availability of health insurance, funding for malaria treatment (relative to total costs) may be significantly lower than costs for households that do not benefit from insurance [52]. In fact, it was reported that the richest households predominantly used biomedical treatments compared to the poorest households.
Although most farmers consider mosquitoes to be the main cause of malaria, only a minority use pesticides (through spraying and fumigation) in their homes, similar to findings in Cameroon and Equatorial Guinea [48, 53]. The lack of concern for mosquitoes compared to crop pests is due to the economic value of crops. To limit costs, low-cost methods such as burning leaves at home or simply repelling mosquitoes by hand are preferred. Perceived toxicity may also be a factor: the odor of some chemical products and the discomfort after use cause some users to avoid their use [54]. The high use of insecticides in households (85.20% of households reported using them) also contributes to the low use of insecticides against mosquitoes. The presence of insecticide-treated bed nets in the household is also strongly associated with the presence of children under 1 year of age, possibly due to antenatal clinic support for pregnant women receiving insecticide-treated bed nets during antenatal consultations [6].
Pyrethroids are the main insecticides used in insecticide-treated bed nets [55] and used by farmers to control pests and mosquitoes, raising concerns about the surge in insecticide resistance [55, 56, 57,58,59]. This scenario may explain the decreased sensitivity of mosquitoes to insecticides observed by farmers.
Higher socioeconomic status was not associated with better knowledge of malaria and mosquitoes as its cause. In contrast to previous findings by Ouattara and colleagues in 2011, wealthier people tend to be better able to identify the causes of malaria because they have easy access to information through television and radio [35]. Our analysis shows that level of higher education predicts better understanding of malaria. This observation confirms that education remains a key element of farmers’ knowledge about malaria. The reason socioeconomic status has less of an impact is that villages often share television and radio. However, socioeconomic status should be taken into account when applying knowledge about domestic malaria prevention strategies.
Higher socioeconomic status and higher education level were positively associated with household pesticide use (spray or spray). Surprisingly, the ability of farmers to identify mosquitoes as the main cause of malaria negatively impacted the model. This predictor was positively associated with pesticide use when grouped across the entire population, but negatively associated with pesticide use when grouped by village. This result demonstrates the importance of the influence of cannibalism on human behavior and the need to include random effects in the analysis. Our study shows for the first time that farmers with experience using pesticides in agriculture are more likely than others to use pesticide sprays and coils as internal strategies to control malaria.
Echoing previous studies on the influence of socioeconomic status on farmers’ attitudes toward pesticides [ 16 , 60 , 61 , 62 , 63 ], wealthier households reported higher variability and frequency of pesticide use. Respondents believed that spraying large amounts of insecticide was the best way to avoid the development of resistance in mosquitoes, which is consistent with concerns expressed elsewhere [64]. Thus, domestic products used by farmers have the same chemical composition under different commercial names, which means that farmers should prioritize technical knowledge of the product and its active ingredients. Attention should also be paid to the awareness of retailers, as they are one of the main reference points for pesticide buyers [17, 24, 65, 66, 67].
To have a positive impact on pesticide use in rural communities, policies and interventions should focus on improving communication strategies, taking into account educational levels and behavioral practices in the context of cultural and environmental adaptation, as well as providing safe pesticides. People will buy based on cost (how much they can afford) and quality of the product. Once quality becomes available at an affordable price, the demand for behavior change in purchasing good products is expected to increase significantly. Educate farmers about pesticide substitution to break the chains of insecticide resistance, making it clear that substitution does not mean a change in product branding; (since different brands contain the same active compound), but rather differences in the active ingredients. This education can also be supported by better product labeling through simple, clear representations.
Since pesticides are widely used by rural farmers in Abbotville Province, understanding farmers’ knowledge gaps and attitudes toward pesticide use in the environment appears to be a prerequisite for developing successful awareness programs. Our study confirms that education remains a major factor in the correct use of pesticides and knowledge about malaria. Family socioeconomic status was also considered an important tool to consider. In addition to the socioeconomic status and educational level of the household head, other factors such as knowledge about malaria, use of insecticides to control pests, and perceptions of mosquito resistance to insecticides influence farmers’ attitudes toward insecticide use.
Respondent-dependent methods such as questionnaires are subject to recall and social desirability biases. It is relatively easy to use household characteristics to assess socioeconomic status, although these measures may be specific to the time and geographic context in which they were developed and may not uniformly reflect the contemporary reality of specific items of cultural value, making comparisons between studies difficult. Indeed, there may be significant changes in household ownership of index components that will not necessarily lead to a reduction in material poverty.
Some farmers do not remember the names of pesticide products, so the amount of pesticides farmers use may be underestimated or overestimated. Our study did not consider farmers’ attitudes toward pesticide spraying and their perceptions of the consequences of their actions on their health and the environment. Retailers were also not included in the study. Both points could be explored in future studies.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Post time: Apr-28-2024