Pesticide Use Safety Practices and Knowledge Gaps Among Small-scale Farmers, Retailers and Healthcare Providers in Tanzania

Pesticide Use Safety Practices and Knowledge Gaps Among Small-scale Farmers, Retailers and Healthcare Providers in Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pesticide Use Safety Practices and Knowledge Gaps Among Small-scale Farmers, Retailers and Healthcare Providers in Tanzania Raphael Mwezi, Rosevera Kombo, Sarah Urasa, Marieke Dekker, William Howlett, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8540934/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Introduction: Agriculture is a cornerstone of Tanzania’s economy, with most production driven by small-scale farmers. In efforts to manage pest-related crop losses, pesticide use has increased significantly, heightening concerns related to human health, environmental sustainability, and regulatory compliance. This study examines the knowledge gaps, practices, and systemic factors influencing pesticide risk reduction among small-scale farmers, pesticide retailers, and healthcare providers in five agriculturally significant regions of Tanzania. Methodology: A cross-sectional study was conducted in Arusha, Iringa, Morogoro, Mwanza, and Shinyanga, purposively selected for their agricultural productivity and diversity. Data was collected via semi-structured questionnaires from 528 farmers, 102 pesticide retailers, and 64 healthcare providers, focusing on pesticide practices, risk reduction knowledge, training, and health outcomes. Multistage sampling ensured diverse representation, and data were analyzed using descriptive statistics with the R Statistical Package. Results and Discussion Findings revealed considerable regional and demographic variation in pesticide use and risk reduction practices. Most respondents were male (78.7%) and had primary-level education (69.7%), with limited access to pesticide risk reduction training—only 21.9% of farmers reported formal training. Pesticide sellers were more gender-balanced but had uneven training coverage, especially in Mwanza and Shinyanga. Most farmers sourced pesticides from licensed retailers (95%), yet unsafe disposal of empty containers (e.g., leaving on-site or burning) was common, posing environmental hazards. Technical information was mainly acquired from pesticide sellers (53.2%) and product labels (43.8%), while agricultural extension officers played a key but limited role in safety training. Insect pests and fungal diseases dominated as crop threats, driving high insecticide (50.7%) and fungicide (34.9%) use. Healthcare providers reported frequent pesticide exposure cases (58.8%), particularly in Iringa, but 93.5% lacked formal training in managing poisoning incidents. Most healthcare providers faced significant challenges in treating such cases. Conclusions The study reveals significant gaps in pesticide risk-reduction knowledge, training, and practice among smallholder farmers and related sectors in Tanzania. Key recommendations include expanding practical training for farmers and retailers, strengthening regulatory enforcement, improving pesticide waste disposal, and enhancing coordination among government, NGOs, and the private sector. Addressing gender and regional disparities is also essential to ensure inclusive progress. The findings highlight the urgent need for integrated actions to protect human health, the environment, and agricultural productivity. Pesticide risk reduction small-scale farmers pesticide retailers healthcare providers Tanzania agricultural practices training environmental health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Agriculture remains the cornerstone of Tanzania’s economy, employing over two-thirds of the nation’s workforce and contributing substantially to food security, rural livelihoods, and national GDP(Mwabulambo et al., 2018 ). The sector is predominantly characterized by small-scale farming, which forms the backbone of rural economies and sustains millions of households (Kariathi et al., 2016 ). However, agricultural productivity in Tanzania, as in many developing countries, is persistently threatened by biotic stresses such as pests, diseases, and weeds (A. V. F. Ngowi et al., 2007 ). To combat these challenges and achieve higher yields, smallholder farmers have increasingly turned to the use of pesticides. Pesticides, encompassing insecticides, herbicides, fungicides, and other agrochemicals, play a critical role in modern agricultural systems by protecting crops from pest infestations and minimizing yield losses (Jones A. Kapeleka et al., 2019 ). Their judicious use can significantly enhance agricultural productivity, food quality, and income for farming communities. Nevertheless, the intensification of pesticide use, especially among small-scale farmers in developing contexts, raises significant concerns regarding human health, environmental sustainability, and the resilience of rural production systems. In Tanzania, the expanding dependency on pesticides is a double-edged sword (Urasa et al., 2024 ). On one hand, it is a response to the increased incidence of pest outbreaks, changing climatic conditions, and the adoption of high-yield crop varieties that are often more susceptible to pests and diseases (Alexander Cogut, 2016 ; Nesheim et al., 2015 ). On the other, it exposes farmers, their families, consumers, and ecosystems to various risks (Aung & Chang, 2014 ; Commission & Directorate-general, 2007 ). These risks include acute and chronic health effects from exposure, contamination of soil and waterways, biodiversity loss, and the development of pesticide resistance among target pest populations. A growing body of evidence suggests that the safe and effective use of pesticides in Tanzania is hampered by several interrelated factors (Calista et al., 2022 ; Jones A. Kapeleka et al., 2020 ). These include limited farmer education, inadequate access to extension services, insufficient training on pesticide risk reduction, weak regulatory enforcement, and the prevalence of informal pesticide supply chains (Urasa et al., 2024 ). Many smallholder farmers lack formal education and rely on experiential knowledge or information from pesticide sellers, whose advice may be influenced by commercial interests rather than safety considerations (E. E. Lekei et al., 2014a ). Furthermore, the labeling and instructions on pesticide containers are often not tailored to the literacy levels of rural farmers, reducing the effectiveness of critical safety communications. Compounding these challenges is the issue of pesticide availability and distribution. While the majority of small-scale farmers obtain pesticides from licensed retailers, a notable fraction still accesses products through informal markets or unregulated vendors (Shao & Edward, 2014 ). These sources may sell counterfeit, expired, or improperly labeled products, exacerbating the risk of misuse and accidental poisoning (CENTRE FOR POLICY RESEARCH AND ADVOCACY, 2016 ). Additionally, the management of pesticide waste, particularly empty containers, remains a major concern. Unsafe disposal practices, such as burning, burying, or abandoning containers in the environment, are widespread and pose direct threats to human health and local ecosystems. Pesticide-related health risks extend beyond the immediate farming community (Jones Ackson Kapeleka et al., 2025 ; Mrema et al., 2017 ). Healthcare providers in rural Tanzania frequently encounter cases of pesticide exposure and poisoning, yet many report inadequate training and resources to manage such incidents effectively (E. Lekei et al., 2014 ). This gap highlights the critical intersection between the agricultural and health sectors and underscores the need for integrated approaches to pesticide risk reduction education, surveillance, and response. In response to these multifaceted challenges, a diverse array of actors has emerged to support safe pesticide use in Tanzania. Government agricultural extension officers remain central to disseminating information and training, but their reach is often limited by resource constraints (Manyilizu et al., 2017 ). NGOs, private sector companies, farmer associations, and international development partners also contribute to safety education, albeit on a smaller scale. Despite these efforts, coverage remains patchy, and significant gaps persist, especially in remote and underserved regions. The regulatory landscape for pesticides in Tanzania has evolved over recent decades, with the establishment of bodies such as the Tanzania Plant Health and Pesticides Authority (TPHPA, formerly TPRI), which oversees registration, training, and compliance (Plant Health act cap No. 133). However, enforcement of regulations on pesticide sales, usage, and waste management is challenged by limited capacity, logistical barriers, and the complexity of informal supply chains that operate parallel to formal distributors. Understanding the patterns of pesticide use and safety among small-scale farmers, retailers, and healthcare providers is fundamental to developing targeted interventions (Barraza et al., 2020 ; Chilipweli et al., 2021 ; Pedersen et al., 2017 ). Previous research in Tanzania and other sub-Saharan African countries has highlighted persistent knowledge gaps, risky behaviors, and systemic constraints, but region-specific insights are often lacking (E. E. Lekei et al., 2016 ; Ndosi et al., 2004 ; a Ngowi et al., 2001 ). Regional diversity in agro-ecological conditions, crop types, pest pressures, and socio-economic factors means that one-size-fits-all solutions are unlikely to be effective. Against this backdrop, the present study provides a comprehensive assessment of pesticide use and safety practices across five key regions of Tanzania: Mwanza, Shinyanga, Morogoro, Iringa, and Arusha (Chilipweli et al., 2021 ; Jones A. Kapeleka et al., 2019 , 2020 ; Jones Ackson Kapeleka et al., 2025 ). These regions were purposefully selected for their prominence in agricultural productivity, diversity in cropping systems, and known intensity of pesticide application. By drawing on the perspectives and experiences of small-scale farmers, pesticide retailers, and healthcare providers, the study seeks to illuminate the complexities of pesticide management in real-world settings. This study contributes to that understanding by offering detailed, regionally nuanced evidence from the perspectives of those most directly involved in the agricultural value chain. The ultimate goal is to support the transition toward safer, more sustainable farming systems that protect both human health and the environment, ensuring continued agricultural productivity and rural well-being for generations to come. 2. Methodology 2.1. Study Area The research was undertaken in five regions of Tanzania: Mwanza, Shinyanga, Morogoro, Iringa, and Arusha. These regions were specifically selected due to their prominence in agricultural productivity and the intensive use of pesticides attributed to high levels of crop cultivation. The diversity in agro-ecological conditions, crop types, and farming practices across these regions allowed for a comprehensive assessment of pesticide use and safety (Chilipweli et al., 2021 ; Jones A. Kapeleka et al., 2019 ; Jones Ackson Kapeleka et al., 2025 ). Study sites within each region were further stratified to encompass both peri-urban and rural settings, ensuring the inclusion of a wide array of small-scale farmers, pesticides retailers, and healthcare providers. This regional selection provided a representative overview of the pesticide risk reduction landscape in Tanzania’s key agricultural zones. 2.2. Study Design This research adopted a cross-sectional study design, which involved collecting data at a single point in time from a diverse sample of participants. The cross-sectional approach was chosen to capture a snapshot of pesticide use practices, knowledge, and safety measures among the target groups. By surveying farmers, retailers, and healthcare providers concurrently, the study was able to compare perspectives and experiences across the agricultural value chain. The design is advantageous for identifying prevalent behaviors, risk factors, and gaps in knowledge or resources related to pesticide risk reduction in the agricultural sector. 2.3. Data Collection Data were gathered using semi-structured questionnaires developed for three distinct respondent groups: pesticide sellers, small-scale farmers, and healthcare providers. The questionnaires were created through a rigorous process, including literature review, expert consultation, and pilot testing to ensure clarity and relevance. Each instrument was tailored to address the unique experiences, roles, and responsibilities of the respondent group: For pesticides sellers : questions focused on their knowledge and experience with pesticides, inventory and sales records (2020/2021), management practices for health and environmental safety, and regulatory compliance. For small-scale farmers : the survey assessed knowledge and experience with pesticide use, pest and disease challenges, types and quantities of pesticides used per cropping season, sources of pesticides, risk management practices, and awareness of environmental and health risks. For healthcare providers : the questionnaire examined their knowledge and experience with pesticide poisoning, capacity and training to treat poisoning cases, and their recommendations for improving pesticide risk reduction and health outcomes. Data collection was conducted through face-to-face interviews by trained research assistants, ensuring high response quality and the opportunity to clarify ambiguous responses. 2.4. Prior Information to Local Authorities Prior to commencing data collection, the research team conducted courtesy visits to relevant local authorities in each study area. The purpose was to inform and obtain formal permission from district-level officials, including District Agriculture, Irrigation and Cooperative Officers (DAICO), District Executive Directors (DED), Ward Executive Officers (WEO), Ward Agricultural Executive Officers (WAEO), and Village Executive Officers (VEO). During these visits, the objectives, scope, and methodology of the study were explained, and official letters of introduction and authorization were secured. This process facilitated cooperation, ensured community entry, and promoted transparency and trust with stakeholders. 2.5. Data Analysis Data were coded, entered, and analyzed using the R Statistical Package, Version 2025.09.2 + 418. Descriptive statistics (frequencies, percentages, means, and standard deviations) were generated to summarize participant demographics, knowledge levels, and reported practices. The analyses provided an overview of age, sex, educational attainment, occupation, and regional distribution, enabling the identification of trends and patterns relevant to pesticide use and safety. The robust use of descriptive statistics allowed for a clear presentation of findings that can inform policy and targeted interventions. 2.6. Inclusion and Exclusion criteria 2.6.1. Inclusion Criteria Small-scale farmers actively engaged in crop production within the selected regions and with direct experience in pesticide use. Licensed pesticides retailers operating within the study regions. Healthcare providers (doctors, nurses, clinical officers) employed in health facilities within the target areas and involved in treating pesticide poisoning or related health conditions. All participants had to be at least 18 years of age and willing to provide informed consent. 2.6.2. Exclusion Criteria Individuals are not directly involved in pesticide use, sale, or management. Respondents under the age of 18. Participants are unwilling or unable to provide informed consent. Large-scale commercial farmers, as the focus was on smallholder systems. 2.7. Sample Size and Sampling Procedure The sample size was determined based on the estimated population of small-scale farmers, pesticides retailers, and healthcare providers in the selected regions, using standard sample size calculation formulas to ensure representativeness and statistical power. Multistage sampling was employed: regions were purposively selected, followed by random selection of wards, villages, and respondents within each group. Proportional allocation was used to ensure adequate representation from each region. Replacement sampling was applied where initial respondents were unavailable or declined participation. 2.8. Quality Control To ensure data quality and reliability, research assistants were recruited from local hospitals and underwent comprehensive training led by subject matter experts. Training covered the study’s objectives, ethical considerations, and rigorous administration of the data collection instruments. Field supervisors conducted spot checks and regular debriefings to address challenges and maintain consistency in data collection. Pilot testing of the questionnaires was also performed to refine question clarity and instrument reliability prior to full-scale deployment. 3. Results 3.1. Results and Inferences for Farmers 3.1.1. Distribution of respondents per region The results from Table 1 provide valuable insights into the distribution of participants across various regions in Tanzania. A total of 528 respondents were surveyed, which allows for a diverse representation that is crucial for understanding pesticide use and safety. The region of Iringa has the highest number of respondents, totaling 191, which accounts for 36.2% of the overall sample. This significant representation suggests that findings from Iringa may substantially influence the overall conclusions and recommendations derived from the study. Following Iringa, Morogoro has 129 respondents (24.4%), contributing another notable proportion of the dataset. This region's presence further enriches the understanding of agricultural practices and challenges faced in pesticide management. In contrast, Arusha has the smallest representation, with 56 respondents (10.6%). While the insights from Arusha are valuable, the limited sample size may restrict the generalizability of findings from this area. Mwanza and Shinyanga present intermediate contributions to the dataset, with 72 (13.6%) and 80 (15.2%) respondents, respectively. Table 1 Number of respondents Variable Region n % Region of respondent Arusha 56 10.6 Iringa 191 36.2 Morogoro 129 24.4 Mwanza 72 13.6 Shinyanga 80 15.2 Total 528 100.0 3.1.2. Gender of farmers The results presented in Table 2 provide critical insights into the demographic composition of the survey participants regarding gender. Out of the total of 528 respondents , a significant majority are male , with 416 participants , representing 78.7% of the sample. In contrast, the female respondents total 112 , accounting for 21.3% of the total participants. Table 2 Gender distribution among respondents Variable N % Gender of respondent Male 416 78.7 Female 112 21.3 Total 528 100.0 3.1.3. Education Level of Farmers Figure 1 presents the distribution of education levels among small-scale farmers in the survey sample. The results indicate a clear predominance of farmers with lower formal education. Specifically, the majority of respondents, 69.7%, reported completing Standard VII, which corresponds to primary education. This is followed by 19.2% who completed Form IV, representing secondary education. Only a small fraction of farmers achieved higher levels of education: 1.9% reached Form VI, 1.1% attained certificates, 1.3% obtained diplomas, and 1.7% held degrees. Notably, 5.0% of the farmers surveyed had never attended formal school at all. 3.1.4. Farmers‟ Access to Pesticides Safe Use Training Table 3 provides an overview of farmers’ access to training on the safe use of pesticides across five regions in Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. The data reveals that a significant majority of farmers have not received any formal training on pesticide risk reduction. Overall, 78.1% (406 out of 520) of respondents indicated they had not received such training, while only 21.9% (114 respondents) reported having participated in training sessions. Regionally, Iringa demonstrates the highest proportion of trained farmers, with 29.9% having received training, followed by Morogoro at 23.4%. In contrast, Arusha, Mwanza, and Shinyanga lag behind, with only 16.1%, 12.5%, and 13.8% of respondents, respectively, reporting any form of pesticide risk reduction training. The data also shows that the majority of farmers in these regions, especially in Arusha (83.9%), Mwanza (87.5%), and Shinyanga (86.3%) lack essential training on safe pesticide handling. Table 3 details related to training on safe use of pesticides Any training in pesticides Region of respondent Total Arusha Iringa Morogoro Mwanza Shinyanga n % n % n 5 n 5 n % n % No 47 83.9% 129 70.1% 98 76.6% 63 87.5% 69 86.3% 406 78.1% Yes 9 16.1% 55 29.9% 30 23.4% 9 12.5% 11 13.8% 114 21.9% Total 56 100.0% 184 100.0% 128 100.0% 72 100.0% 80 100.0% 520 100.0% 3.1.5. Service Providers of Pesticides Safe Use Training to Farmers Figure 2 illustrates the various organizations and entities that provide training on the safe use of pesticides to farmers. The most significant contributor is the agricultural extension officers, who account for 35.5% of the training provided. This highlights the central role that government and public extension services play in disseminating critical safety information to small-scale farmers. The next most prominent provider is the Vegetable Seeds Company, responsible for 15.5% of the training, followed by "Feed the Future," an initiative or organization contributing 12.7%. Other sources of training include TAHA, SUA, Nafaka USAID, and Osho, each accounting for 3.6% or less, and a range of additional organizations such as Syngenta, Seedco, various private companies, and specific farmer training centers, each with smaller shares of the training landscape. Notably, a long tail of organizations—including NGOs, farmer associations, and commodity boards—provide marginal but nonetheless important support, often tailored to specific crops or local needs. 3.1.6. Farmers’ Source of Information on Pesticides Use Figure 3 demonstrates where farmers most commonly seek technical information and support regarding pesticide use. The data reveal that the majority of farmers rely on pesticide sellers as their primary source of technical guidance, with 53.2% of respondents identifying sellers as their main point of information. This underscores the influential role that pesticide retailers play in shaping farmers’ knowledge and practices with respect to pesticide application and safety. The second most utilized source is pesticide labels, referenced by 43.8% of farmers. This finding points to the importance of clear, comprehensible labeling on pesticide products, as many farmers turn directly to the product itself for guidance. Agricultural extension staff are the third most common source, cited by 24.1% of respondents. While extension officers are recognized as important trainers, their reach appears to be more limited compared to sellers and labels. Additionally, 23.5% of farmers report relying on their own knowledge, which may be based on personal experience or informal learning, while a small fraction (2.3%) turns to fellow farmers for advice. The relatively low reliance on peer-to-peer information sharing suggests that formal and commercial sources dominate the flow of technical support. 3.1.7. Information on Agriculture pests Figure 4 presents the types of agricultural pests most reported by small-scale farmers as affecting crop production. The data reveal that insect pests are overwhelmingly perceived as the primary challenge, with 96.2% of respondents identifying them as the main threat to their crops. This finding underscores the significant impact of insect infestations on agricultural productivity and the likely heavy reliance on insecticides in pest management strategies. Fungal diseases are the second most frequently reported issue, cited by 63.9% of respondents. This indicates that plant pathogens also represent a substantial threat to yields and may necessitate the use of fungicides as a common crop protection measure. Weeds are reported as a major concern by 20.7% of farmers, reflecting the ongoing battle with unwanted plants that compete for nutrients and resources. Nematodes are the least frequently mentioned, with only 1.3% of farmers identifying them as a significant problem. 3.1.8. Agriculture pests and regions Table 4 provides a detailed breakdown of the types of agricultural pests reported by farmers across five key regions in Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. Across all regions, insect pests emerge as the most pervasive problem, accounting for 53% of all pest issues reported (507 out of 960 cases). This trend is particularly pronounced in Shinyanga, where 68.4% of respondents identified insect pests as their primary challenge, as well as in Mwanza (57.6%) and Morogoro (52.4%). Iringa and Arusha also report high incidences of insect pests, at 47.2% and 51.8% respectively. Fungal diseases are the next most common pest type, making up 35% of reported cases. Iringa stands out with 42.9% of farmers reporting fungal problems, closely followed by Mwanza (40.8%) and Arusha (38.6%). In contrast, Morogoro reports a lower incidence of fungal diseases at 17.3%, suggesting regional variation in crop vulnerability or pathogen prevalence. Weeds are a significant concern in Morogoro, where 27.9% of farmers identified them as a primary pest, compared to less than 10% in most other regions. This suggests localized weed management challenges that may be tied to specific cropping systems or environmental factors. Nematode infestations are rare across all regions, comprising just 1% (7 cases) of the total reports, with occasional cases in Arusha, Morogoro, and Mwanza, and none in Iringa and Shinyanga. Table 4 Distribution of Regions and infestation of agricultural pests Variable Region of Respondent Total ARUSHA IRINGA MOROGORO MWANZA SHINYANGA n % n % n % n % n % n % Fungal 44 38.6% 170 42.9% 36 17.3% 51 40.8% 36 30.8% 337 35% Insect 59 51.8% 187 47.2% 109 52.4% 72 57.6% 80 68.4% 507 53% Weeds 10 8.8% 39 9.8% 58 27.9% 1 0.8% 1 0.9% 109 11% Nematodes 1 0.9% 0 0.0% 5 2.4% 1 0.8% 0 0.0% 7 1% Total 114 100.0% 396 100.0% 208 100.0% 125 100.0% 117 100.0% 960 100% 3.1.9. Places Where Farmers Acquire Pesticides Table 5 reveals the primary channels through which small-scale farmers obtain pesticides. The overwhelming majority—513 out of 540 respondents, or 95.0%, purchased their pesticides from licensed selling shops. This indicates that regulated, formal retail outlets are the dominant source for pesticide procurement, suggesting a potentially positive environment for ensuring product quality, proper labeling, and regulatory compliance. In contrast, a small proportion of farmers rely on less formal sources: 3.7% (20 respondents) acquire pesticides from open markets, and just 1.3% (7 respondents) obtain them directly from vendors. These informal channels may pose risks, including the possibility of counterfeit products, lack of proper usage instructions, and limited safety assurances. Table 5 information of pesticides availability Variable n % Places where Pesticides are brought At licensed pesticides selling shops 513 95.0% At open market 20 3.7% From pesticides vendors 7 1.3% Total 540 100.0% 3.1.10. Use Category of Pesticides by Regions for Farmers Table 6 outlines the distribution of pesticide types used by small-scale farmers, categorized into fungicides, insecticides, and herbicides. Of the total 926 pesticide applications reported, insecticides constitute the largest share, with 469 instances, accounting for 50.65%. This aligns with earlier findings that insect pests are the most pressing agricultural challenge, reinforcing the heavy reliance on insecticidal solutions. Fungicides follow, comprising 323 applications or 34.88% of the total. This substantial use reflects the prominence of fungal diseases as a significant threat to crop health. Herbicides, while still relevant, are used less frequently—accounting for 134 applications or 14.47% of the total. The comparatively lower use of herbicides may indicate either a reduced prevalence of weed pressure across surveyed farms or a preference for alternative weed management strategies. Table 6 Details of the categories of pesticides Variable n % Use category of pesticides Fungicide 323 34.88% Insecticide 469 50.65% Herbicide 134 14.47% Total 926 100.00% 3.1.11. Management of empty pesticides containers Figure 5 illustrates the methods by which farmers dispose of empty pesticide containers. The most common practice is leaving used containers unattended on the farm, accounting for 45.4% of responses. This method poses serious environmental and health risks, as unattended containers may leak residues, contaminate soil or water, and be accessed by children or animals. Burning empty containers in the open farmyard spaces is the second most prevalent approach, representing 30.9% of disposal practices. While burning may reduce physical waste volume, it can release harmful chemical residues into the air, creating inhalation hazards and potentially contaminating nearby areas. A further 16.7% of farmers report burying containers in the farm, which may limit surface exposure but can lead to soil contamination and leaching into groundwater if not done properly. Finally, only 7.0% of respondents rinse, puncture, and leave containers in the farmyard method that, while still not ideal, indicates some awareness of safer disposal practices. 3.2. Results and Inferences for Pesticide Sellers Figure 6 presents the regional distribution of pesticide sellers across the surveyed areas. Iringa leads with the largest share, encompassing 36% of all pesticide sellers. Following Iringa, Morogoro accounts for 24% of sellers, while Shinyanga represents 15%, Mwanza holds 14%, and Arusha has the smallest proportion at 11%. This distribution suggests that pesticide retail activity is more concentrated in Iringa and Morogoro, possibly reflecting higher agricultural activity, better-developed retail infrastructure, or stronger market demand in those regions. Conversely, the lower representation in Arusha may indicate a smaller retail network or limited access to pesticide products in that area. 3.2.1. Gender Distribution of Pesticides Retailers Table 7 presents the gender composition of the pesticide retailers surveyed. Of the 102 retailers, 52 (51%) are male and 50 (49%) are female. This near-equal distribution contrasts with the male-dominated pattern observed among small-scale farmers in Table 2 . The balanced representation indicates that women are actively involved in the agricultural input supply chain, particularly in pesticide retailing. Table 7 Distribution of Pesticides Retailers based on sex Variable Sex n % Gender of respondent Female 50 49% Male 52 51% Total 102 100% 3.2.2. Education Level of Pesticides Retailers Figure 7 illustrates the educational attainment of pesticide sellers. The highest proportion, 31.1%, completed Form IV (equivalent to secondary school level). This is closely followed by those holding a degree—27.3% of sellers. Certificates and Standard VII (primary education) each account for 15.5%, while Form VI (advanced secondary) represents 9.7%. Only 1% of sellers have never attended formal school. 3.2.3. Age Group of Pesticides Sellers Figure 8 provides an age distribution profile of pesticide retailers. The largest segment, comprising 54.4% of respondents, falls within the 21–30 years age group. The next most represented group is those aged 31–40 years, accounting for 30.1%. Older age groups are markedly smaller in number: 5.8% of retailers are aged 51–60 years, 4.9% are over 60, 2.9% are 20 years and below, and just 1.9% fall in the 41–50 years category. 3.2.4. Training on Pesticides Risk Reduction for Pesticides Sellers Table 8 sheds light on the prevalence of pesticide risk reduction training among retailers across five Tanzanian regions. Out of 103 surveyed sellers, a majority—62.1% (64 individuals)—have received training on safe pesticide use, while 37.9% (39 individuals) have not. Regionally, Morogoro exhibits the highest training coverage, with 18 of 19 retailers trained and just one untrained. Arusha follows with 22 trained versus 14 untrained retailers. Iringa shows moderate engagement, with 12 trained and five untrained. Table 8 Details of training to the pesticide’s sellers Variable Region of respondent Total Arusha Iringa Morogoro Mwanza Shinyanga n % n % n % n % n % n % Any training in pesticides No 14 35.9% 5 12.8% 1 2.6% 5 12.8% 14 35.9% 39 37.9% Yes 22 34.4% 12 18.8% 18 28.1% 6 9.4% 6 9.4% 64 62.1% Total 36 35.0% 17 16.5% 19 18.4% 11 10.7% 20 19.4% 103 100.0% 3.2.5. Service Providers for Training on Pesticides Risk Reduction for Pesticide Sellers : Figure 9 highlights the key organizations responsible for providing training on pesticide risk reduction to pesticide sellers. Tanzania Plant Health and Pesticides Authority (TPHPA) initially called the Tropical Pesticides Research Institute (TPRI), through its PM2 courses, stands out as the dominant provider, accounting for 48.2% of the training delivered. This underscores TPRI’s central role in equipping retailers with essential skills and knowledge. The next most significant contributor is non-governmental organizations (NGOs), which deliver 10.8% of the training, followed by pesticide companies at 4.8%. Smaller contributions come from institutions such as Hort-Tengeru, TOSC, TFDA, and district extension officers, each delivering around 1.2% to 2.4% of training. 3.3. Results and Inferences for Health Care Providers 3.3.1. Incidences of pesticides poisoning Table 9 presents data on the incidence of pesticide exposure-related cases reported by healthcare providers across five Tanzanian regions. Out of 515 total responses, 58.8% (303 cases) indicated occurrences of pesticide-related exposures or poisoning, while 41.2% (212 cases) reported no such incidents. Regionally, Iringa stands out with the highest prevalence of reported incidents—68.5% of respondents noted pesticide exposure cases—followed by Arusha at 62.7%, Mwanza at 62.0%, and Morogoro at 57.9%. In contrast, Shinyanga reported the lowest incidence, with only 32.5% of respondents acknowledging pesticide exposure cases, and 67.5% reporting none. Table 9 Incidences of pesticides poisoning Variable Region of respondent Total Arusha Iringa Morogoro Mwanza Shinyanga n % n % n % n % n % n % Incidents related to exposure pesticides No 22 37.3% 58 31.5% 51 42.1% 27 38.0% 54 67.5% 212 41.2% Yes 37 62.7% 126 68.5% 70 57.9% 44 62.0% 26 32.5% 303 58.8% Total 59 100.0% 184 100.0% 121 100.0% 71 100.0% 80 100.0% 515 100.0% 3.3.2. Information of management of Pesticides Poisoning Cases Table 10 highlights critical gaps in healthcare providers' preparedness and knowledge regarding pesticide poisoning. Among 62 respondents, a striking 93.5% (58 individuals) reported having no formal training in treating pesticide intoxications, leaving only 6.5% (4 individuals) with such training. Regarding awareness of pesticides commonly used by farmers in their facility’s catchment area, only 54.7% (35 out of 64 respondents) indicated familiarity, while 45.3% (29 individuals) lacked this knowledge. Similarly, when asked about pesticides most frequently associated with poisoning or exposure incidents, just under 49.2% (31 out of 63 respondents)—claimed awareness, while 50.8% (32 individuals) did not. Table 10 Knowledge and prevalence of pesticides poisoning cases Variable n % Any training in treatment of pesticide intoxications No 58 93.5% Yes 4 6.5% Total 62 100.0% Knowledge of pesticides commonly used by farmers in the areas of health facility No 29 45.3% Yes 35 54.7% Total 64 100.0% Knowledge of pesticides most often reported to cause poisoning/exposures No 32 50.8% Yes 31 49.2% Total 63 100.0% 3.3.3. Challenges on Management of Pesticides poisoning cases Table 11 reveals that a significant majority of healthcare providers—60% (37 out of 62 respondents) reported encountering challenges when providing first aid or treatment for pesticide intoxication cases, while only 40% (25 respondents) indicated no difficulties. This finding underscores the substantial obstacles faced by medical personnel in effectively managing pesticide-related emergencies. These challenges may stem from factors such as inadequate training, limited access to necessary medical supplies, lack of standardized treatment protocols, or insufficient knowledge of the specific pesticides involved. Table 11 Challenge encounter in handling pesticide poisoning variable n % Any challenges in providing first aid/treatment of pesticides intoxications cases No 25 40% Yes 37 60% Total 62 100% 4. Discussion The distribution of survey participants varied notably by region, with Iringa and Morogoro showing the highest representation. This likely reflects differences in agricultural intensity, climate, or local governance structures that influence pesticide use and safety practices (Alyaseri, 2021 ). Regions with more respondents may also have been easier to access for data collection, suggesting potential sampling bias in coverage. A marked gender imbalance emerged among smallholder farmers, with far more men than women participating. This aligns with broader research showing that men often dominate farming roles, while women remain underrepresented due to cultural norms and limited access to resources (Mwakalasya et al., 2025 ). Women’s marginalization in training and decision-making may elevate their vulnerability to unsafe pesticide use (Abasilim et al., 2025 ; A. Ngowi et al., 2017 ). Tailored, gender-sensitive interventions are therefore essential to ensure equitable access to safety training. Educational attainment among farmers was generally low, primarily limited to primary schooling. This educational gap can impede the comprehension of pesticide labels and safety protocols, reducing the effectiveness of training programs (Atreya et al., 2012 ; Ngoya et al., 2023 ). Addressing this requires training that is context-appropriate and accessible to those with limited formal education. A substantial portion of farmers lacked formal training in pesticide risk reduction, particularly in certain regions This deficiency increases risks to both human health and the environment (Heredia et al., 2015 ; Kim et al., 2017 ) The uneven geographic distribution of training underscores the need for targeted outreach in underserved areas. This study identified that agricultural extension officers were the main providers of pesticide risk reduction training, yet reliance on this single source may strain available resources. Expanding partnerships to include NGOs, agro-dealers, and farmer groups could improve reach and diversify training methods, enhancing overall program effectiveness. Similar efforts have been reported in neighbor countries such as Kenya and Uganda (Mukasa et al., 2015 ; Muriithi et al., 2024 ) Sources of information on safe use of pesticides to the famers are very important (Kariathi et al., 2016 ). This study suggests that farmers involved in this suggest depending to the pesticide sellers for technical guidance, followed by product labels and extension staff. While accessible, seller-provided information often lacks safety focus, and labels may be difficult to understand similar findings were reported by E. E. Lekei et al., 2014b while he conducting assessment to pesticides retailers. Strengthening extension services and ensuring accuracy across all information sources is critical for promoting safe practices. In Tanzania the common infested pests in agriculture are insects, fungi, weeds, Insect, rodent, birds, nematodes (A. V. F. Ngowi et al., 2007 ). The findings of this study identified insects, and fungal diseases were the most reported threats, driving high use of insecticides and fungicides. Interventions should therefore concentrate on improving safe handling and application of these pesticide types. The relatively lower concern for weeds and nematodes may reflect either lower prevalence or gaps in awareness, underscoring the need for region-specific education. This study shows that pest prevalence varies by region, with insect pests being universal but other pest types differ significantly by location. This underscores the need for locally adapted pest management strategies and extension messaging (Smith et al., 2018). The findings show that most farmers purchased pesticides from licensed retailers. This presents an opportunity to reinforce safe handling through regulated channels, though the limited presence of informal supply chains highlights the necessity of continuous monitoring to safeguard product safety and reliability (Kimani & Mwaniki, 2020). This study identified usage patterns revealed insecticides as the most frequently used category, followed by fungicides and herbicides. Such evidence suggests that safety training should prioritize these products while also addressing proper herbicide use and environmental considerations (Osei et al., 2017). Unsafe disposal of empty pesticide containers was widespread, with common practices such as abandonment and open burning posing environmental and public health risks; therefore, interventions should include training on safe disposal techniques and provision of designated facilities (Mburu & Ngugi, 2016). Iringa and Morogoro exhibited higher concentrations of pesticide retailers, making them suitable hubs for training and compliance monitoring, whereas regions like Arusha with fewer retailers may benefit from mobile or targeted outreach strategies to reach dispersed stakeholders (Chikoye et al., 2015). In contrast to the farming community, gender distribution among pesticide retailers was more balanced; engaging female retailers in training efforts could enhance the dissemination of safety messages, particularly to women farmers who are frequently underrepresented (Alhassan & Salifu, 2019). Retailers generally possessed moderate to high educational levels, with the majority holding secondary or tertiary qualifications; however, the existence of a small minority with no formal education emphasizes the importance of inclusive training materials that cater to varying literacy levels (Mwangi & Kariuki, 2014). The retail workforce was predominantly young (under 41), which may facilitate the adoption of new safety practices, though the limited presence of older, more experienced individuals signals a need for mentorship and intergenerational knowledge transfer (Dossou & Mitchell, 2021). Training among pesticide retailers displayed regional disparities, with Mwanza and Shinyanga showing notable gaps, indicating the importance of region-specific capacity-building initiatives to ensure consistent safe handling practices (Abate et al., 2013). Training was primarily delivered by formal institutions, with minimal involvement from NGOs or private actors, suggesting that expanded collaboration could enhance both reach and sustainability of training programs (Van den Berg & Jiggins, 2007). Incidence of pesticide poisoning varied by region, with higher rates in Iringa, Arusha, Mwanza, and Morogoro, possibly due to factors such as limited training, unsafe handling, or inadequate use of protective equipment, necessitating tailored prevention and response strategies (Jaga & Dharmani, 2005). Most healthcare providers lacked training in pesticide poisoning management and were unfamiliar with many commonly used pesticides, highlighting the need for cross-sector collaboration to strengthen health sector capacity for improved diagnosis and treatment (London et al., 2012). Healthcare providers also reported significant challenges in treating pesticide poisoning, underscoring the need for specialized training, improved access to medical supplies, and stronger coordination between agricultural and health sectors to effectively mitigate health risks (Ngowi et al., 2001 ). In summary, this study reveals significant regional, gender, and educational disparities in pesticide use, safety practices, and access to information across Tanzania’s agricultural sector. High pesticide usage, particularly of insecticides and fungicides, coupled with widespread unsafe disposal practices, underscores urgent needs for targeted training and improved regulatory oversight. The predominance of men among farmers and the marginalization of women and less-educated individuals highlights the necessity for gender-sensitive, inclusive interventions. Regional disparities in retailer concentration, training availability, and healthcare preparedness further emphasize the importance of locally adapted strategies and cross-sector collaboration. Expanding the roles of NGOs, private actors, and female retailers—while strengthening extension services and healthcare capacity—will be vital for promoting safe pesticide use and reducing health and environmental risks. Ultimately, a multifaceted and context-specific approach is essential to address the complex challenges identified, ensuring equitable and sustainable improvements in pesticide management and rural health outcomes. 5. Conclusion This study provides a detailed and regionally nuanced understanding of pesticide use, safety practices, and associated health risks among small-scale farmers, pesticide retailers, and healthcare providers in five key agricultural regions of Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. The findings reveal significant gaps and challenges at multiple points along the agricultural value chain, as well as opportunities for targeted interventions. Policy and practice should prioritize the expansion of accessible, context-appropriate training programs for farmers, retailers, and healthcare providers; strengthen regulatory enforcement and monitoring of pesticide distribution and use; promote safer disposal methods for pesticide waste; and enhance collaboration between government, non-governmental organizations, and the private sector. Gender-sensitive approaches and tailored interventions for underserved regions are essential for equitable progress. Ultimately, advancing pesticide risk reduction in Tanzania will require sustained commitment, increased resources, and coordinated efforts at all levels—from local communities to national authorities—to protect human health, preserve environmental integrity, and support the country’s agricultural development. 6. Recommendation This study recommends to expand the practical and inclusive training programs, strengthening regulatory enforcement and monitoring programs, Improve pesticides waste management, enhance agricultural extension Services equipped with updated knowledge, design and implement gender-sensitive strategies to empower women on pesticides on safe use of pesticides and pesticides risk reduction, strengthen healthcare capacity through integrating pesticide poisoning management into the training curricula of healthcare providers, encourage ongoing research and surveillance on pesticide use, health impacts, and environmental outcomes, extending beyond the five regions studied here in to inform policy adjustments and enable timely, evidence-based interventions. Through implementing these recommendations, Tanzania can advance toward safer and more sustainable agricultural practices, reducing risks to human health and the environment while supporting the productivity and well-being of small-scale farming communities. 7. Limitation of the study The project faced several limitations, and this included, time allocated for the project being limited as compared to the magnitude of the workload which needed more time to comprehend exhaustively the required information. The survey report findings and interpretation are for the five regions under the project which were Arusha, Iringa, Mwanza, Shinyanga and Morogoro and these do not reflect the general situation of the country, and hence more survey is objectively important. Declarations Ethics approval and accordance All experimental protocols involving human participants were reviewed and approved by the Tanzania’s National Institute of Medical Research (NIMR) with Reference No. NIRM/HQ/R.8a/Vol.IX/2742. Ethical Guidelines (Helsinki Declaration) This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and its later amendments or comparable ethical standards. Acknowledgements The authors express their gratitude to the institutions and academics that provided access to this survey. Consent to Participants Participation in the study was voluntary, and informed consent was obtained from all participants prior to completing the survey. Availability of data and materials All data generated or analyzed in this study are included within this article. Competing interests The authors declare no competing interest. Funding The study was funded by the Food and Agriculture Organization of the United Nations (FAO) through the project on Capacity-Building Related to Multilateral Environmental Agreements in ACP Countries - Phase 3 ("ACP/MEAs 3" – GCP/GLO/006/EC) Authors' contributions RM, JB, RO, and DM were responsible for developing the manuscript, while JK, SR, MD, WH, IS, KT and JV contributed by reviewing and editing. Authors' affiliations 1 Tanzania Plant Health and Pesticide Authority (TPHPA), Directorate of Pesticide, P.O. Box 3024, Arusha, Tanzania 2 Department of Global Health and Biomedical Sciences, Nelson Mandela African Institution of Science and Technology, P. O. Box 447, Arusha-Tanzania. 3 Department of Internal Medicine, Kilimanjaro Christian Medical Centre, Moshi, Tanzania 4 Department of Internal Medicine, KCMC University, Moshi, Tanzania 5 Food and Agriculture Organization of the United Nations (FAO). 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09:12:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54320,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eService providers of pesticides safe use training to farmers\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/f9d6f8ac0e9a8839b4d86891.png"},{"id":102982095,"identity":"04105441-b8ea-4366-9ca1-0c79620aa8f4","added_by":"auto","created_at":"2026-02-19 09:12:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89337,"visible":true,"origin":"","legend":"\u003cp\u003eSources of technical support for pesticides use\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/acf8266b74da6e506b892420.png"},{"id":102982099,"identity":"15b98677-9622-4adc-8f2a-a27633a14e1c","added_by":"auto","created_at":"2026-02-19 09:12:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":59064,"visible":true,"origin":"","legend":"\u003cp\u003eMain Reported Agricultural Pests\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/80a1bc08f7d33fabfde40a5e.png"},{"id":102982033,"identity":"8a4bf0d5-0b3b-4bf6-a96f-da8a27020393","added_by":"auto","created_at":"2026-02-19 09:12:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":89015,"visible":true,"origin":"","legend":"\u003cp\u003eManagement of empty pesticide containers\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/917d108eea80ae4e17da713a.png"},{"id":102982074,"identity":"4dacea3f-7bd9-4f9a-8f1c-d2a7ac775265","added_by":"auto","created_at":"2026-02-19 09:12:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":107299,"visible":true,"origin":"","legend":"\u003cp\u003eRegional Coverage of Pesticides Sellers\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/f6041349ce0dd7a6254ea9df.png"},{"id":102982072,"identity":"b0332706-5def-4094-9cf6-6c294a50136e","added_by":"auto","created_at":"2026-02-19 09:12:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":90746,"visible":true,"origin":"","legend":"\u003cp\u003eEducation Level of Pesticides Sellers\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/3ad9a4aa1ac1b0dc34ed1e7b.png"},{"id":102982092,"identity":"5d912db1-659d-435d-959b-0e8e7dcbf455","added_by":"auto","created_at":"2026-02-19 09:12:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":36210,"visible":true,"origin":"","legend":"\u003cp\u003eAge groups of pesticides retailers\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/777446570846e563c77eb74e.png"},{"id":102982100,"identity":"26faed53-fc9d-4dbe-8bd9-ce5de2eacb65","added_by":"auto","created_at":"2026-02-19 09:12:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":17931,"visible":true,"origin":"","legend":"\u003cp\u003eService providers for training on pesticides safe use for pesticides retailers\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/ad4e55f66e909581585d4f4d.png"},{"id":102982186,"identity":"a1f39ed1-cba6-456d-a2d3-c4269bfe96b3","added_by":"auto","created_at":"2026-02-19 09:12:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2514213,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8540934/v1/bb20775a-abfa-4dba-a12f-7b09ec2084fa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePesticide Use Safety Practices and Knowledge Gaps Among Small-scale Farmers, Retailers and Healthcare Providers in Tanzania\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAgriculture remains the cornerstone of Tanzania\u0026rsquo;s economy, employing over two-thirds of the nation\u0026rsquo;s workforce and contributing substantially to food security, rural livelihoods, and national GDP(Mwabulambo et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The sector is predominantly characterized by small-scale farming, which forms the backbone of rural economies and sustains millions of households (Kariathi et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, agricultural productivity in Tanzania, as in many developing countries, is persistently threatened by biotic stresses such as pests, diseases, and weeds (A. V. F. Ngowi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). To combat these challenges and achieve higher yields, smallholder farmers have increasingly turned to the use of pesticides.\u003c/p\u003e \u003cp\u003ePesticides, encompassing insecticides, herbicides, fungicides, and other agrochemicals, play a critical role in modern agricultural systems by protecting crops from pest infestations and minimizing yield losses (Jones A. Kapeleka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their judicious use can significantly enhance agricultural productivity, food quality, and income for farming communities. Nevertheless, the intensification of pesticide use, especially among small-scale farmers in developing contexts, raises significant concerns regarding human health, environmental sustainability, and the resilience of rural production systems.\u003c/p\u003e \u003cp\u003eIn Tanzania, the expanding dependency on pesticides is a double-edged sword (Urasa et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On one hand, it is a response to the increased incidence of pest outbreaks, changing climatic conditions, and the adoption of high-yield crop varieties that are often more susceptible to pests and diseases (Alexander Cogut, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nesheim et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). On the other, it exposes farmers, their families, consumers, and ecosystems to various risks (Aung \u0026amp; Chang, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Commission \u0026amp; Directorate-general, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These risks include acute and chronic health effects from exposure, contamination of soil and waterways, biodiversity loss, and the development of pesticide resistance among target pest populations.\u003c/p\u003e \u003cp\u003eA growing body of evidence suggests that the safe and effective use of pesticides in Tanzania is hampered by several interrelated factors (Calista et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jones A. Kapeleka et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These include limited farmer education, inadequate access to extension services, insufficient training on pesticide risk reduction, weak regulatory enforcement, and the prevalence of informal pesticide supply chains (Urasa et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Many smallholder farmers lack formal education and rely on experiential knowledge or information from pesticide sellers, whose advice may be influenced by commercial interests rather than safety considerations (E. E. Lekei et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). Furthermore, the labeling and instructions on pesticide containers are often not tailored to the literacy levels of rural farmers, reducing the effectiveness of critical safety communications.\u003c/p\u003e \u003cp\u003eCompounding these challenges is the issue of pesticide availability and distribution. While the majority of small-scale farmers obtain pesticides from licensed retailers, a notable fraction still accesses products through informal markets or unregulated vendors (Shao \u0026amp; Edward, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These sources may sell counterfeit, expired, or improperly labeled products, exacerbating the risk of misuse and accidental poisoning (CENTRE FOR POLICY RESEARCH AND ADVOCACY, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, the management of pesticide waste, particularly empty containers, remains a major concern. Unsafe disposal practices, such as burning, burying, or abandoning containers in the environment, are widespread and pose direct threats to human health and local ecosystems.\u003c/p\u003e \u003cp\u003ePesticide-related health risks extend beyond the immediate farming community (Jones Ackson Kapeleka et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Mrema et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Healthcare providers in rural Tanzania frequently encounter cases of pesticide exposure and poisoning, yet many report inadequate training and resources to manage such incidents effectively (E. Lekei et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This gap highlights the critical intersection between the agricultural and health sectors and underscores the need for integrated approaches to pesticide risk reduction education, surveillance, and response.\u003c/p\u003e \u003cp\u003eIn response to these multifaceted challenges, a diverse array of actors has emerged to support safe pesticide use in Tanzania. Government agricultural extension officers remain central to disseminating information and training, but their reach is often limited by resource constraints (Manyilizu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). NGOs, private sector companies, farmer associations, and international development partners also contribute to safety education, albeit on a smaller scale. Despite these efforts, coverage remains patchy, and significant gaps persist, especially in remote and underserved regions.\u003c/p\u003e \u003cp\u003e The regulatory landscape for pesticides in Tanzania has evolved over recent decades, with the establishment of bodies such as the Tanzania Plant Health and Pesticides Authority (TPHPA, formerly TPRI), which oversees registration, training, and compliance (Plant Health act cap No. 133). However, enforcement of regulations on pesticide sales, usage, and waste management is challenged by limited capacity, logistical barriers, and the complexity of informal supply chains that operate parallel to formal distributors.\u003c/p\u003e \u003cp\u003eUnderstanding the patterns of pesticide use and safety among small-scale farmers, retailers, and healthcare providers is fundamental to developing targeted interventions (Barraza et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chilipweli et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pedersen et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Previous research in Tanzania and other sub-Saharan African countries has highlighted persistent knowledge gaps, risky behaviors, and systemic constraints, but region-specific insights are often lacking (E. E. Lekei et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Ndosi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; a Ngowi et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Regional diversity in agro-ecological conditions, crop types, pest pressures, and socio-economic factors means that one-size-fits-all solutions are unlikely to be effective.\u003c/p\u003e \u003cp\u003eAgainst this backdrop, the present study provides a comprehensive assessment of pesticide use and safety practices across five key regions of Tanzania: Mwanza, Shinyanga, Morogoro, Iringa, and Arusha (Chilipweli et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jones A. Kapeleka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Jones Ackson Kapeleka et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These regions were purposefully selected for their prominence in agricultural productivity, diversity in cropping systems, and known intensity of pesticide application. By drawing on the perspectives and experiences of small-scale farmers, pesticide retailers, and healthcare providers, the study seeks to illuminate the complexities of pesticide management in real-world settings.\u003c/p\u003e \u003cp\u003eThis study contributes to that understanding by offering detailed, regionally nuanced evidence from the perspectives of those most directly involved in the agricultural value chain. The ultimate goal is to support the transition toward safer, more sustainable farming systems that protect both human health and the environment, ensuring continued agricultural productivity and rural well-being for generations to come.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area\u003c/h2\u003e \u003cp\u003eThe research was undertaken in five regions of Tanzania: Mwanza, Shinyanga, Morogoro, Iringa, and Arusha. These regions were specifically selected due to their prominence in agricultural productivity and the intensive use of pesticides attributed to high levels of crop cultivation. The diversity in agro-ecological conditions, crop types, and farming practices across these regions allowed for a comprehensive assessment of pesticide use and safety (Chilipweli et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jones A. Kapeleka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jones Ackson Kapeleka et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Study sites within each region were further stratified to encompass both peri-urban and rural settings, ensuring the inclusion of a wide array of small-scale farmers, pesticides retailers, and healthcare providers. This regional selection provided a representative overview of the pesticide risk reduction landscape in Tanzania\u0026rsquo;s key agricultural zones.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study Design\u003c/h2\u003e \u003cp\u003eThis research adopted a cross-sectional study design, which involved collecting data at a single point in time from a diverse sample of participants. The cross-sectional approach was chosen to capture a snapshot of pesticide use practices, knowledge, and safety measures among the target groups. By surveying farmers, retailers, and healthcare providers concurrently, the study was able to compare perspectives and experiences across the agricultural value chain. The design is advantageous for identifying prevalent behaviors, risk factors, and gaps in knowledge or resources related to pesticide risk reduction in the agricultural sector.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data Collection\u003c/h2\u003e \u003cp\u003eData were gathered using semi-structured questionnaires developed for three distinct respondent groups: pesticide sellers, small-scale farmers, and healthcare providers. The questionnaires were created through a rigorous process, including literature review, expert consultation, and pilot testing to ensure clarity and relevance. Each instrument was tailored to address the unique experiences, roles, and responsibilities of the respondent group:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFor pesticides sellers\u003c/b\u003e: questions focused on their knowledge and experience with pesticides, inventory and sales records (2020/2021), management practices for health and environmental safety, and regulatory compliance.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFor small-scale farmers\u003c/b\u003e: the survey assessed knowledge and experience with pesticide use, pest and disease challenges, types and quantities of pesticides used per cropping season, sources of pesticides, risk management practices, and awareness of environmental and health risks.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFor healthcare providers\u003c/b\u003e: the questionnaire examined their knowledge and experience with pesticide poisoning, capacity and training to treat poisoning cases, and their recommendations for improving pesticide risk reduction and health outcomes.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eData collection was conducted through face-to-face interviews by trained research assistants, ensuring high response quality and the opportunity to clarify ambiguous responses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Prior Information to Local Authorities\u003c/h2\u003e \u003cp\u003ePrior to commencing data collection, the research team conducted courtesy visits to relevant local authorities in each study area. The purpose was to inform and obtain formal permission from district-level officials, including District Agriculture, Irrigation and Cooperative Officers (DAICO), District Executive Directors (DED), Ward Executive Officers (WEO), Ward Agricultural Executive Officers (WAEO), and Village Executive Officers (VEO). During these visits, the objectives, scope, and methodology of the study were explained, and official letters of introduction and authorization were secured. This process facilitated cooperation, ensured community entry, and promoted transparency and trust with stakeholders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data Analysis\u003c/h2\u003e \u003cp\u003eData were coded, entered, and analyzed using the R Statistical Package, Version 2025.09.2\u0026thinsp;+\u0026thinsp;418. Descriptive statistics (frequencies, percentages, means, and standard deviations) were generated to summarize participant demographics, knowledge levels, and reported practices. The analyses provided an overview of age, sex, educational attainment, occupation, and regional distribution, enabling the identification of trends and patterns relevant to pesticide use and safety. The robust use of descriptive statistics allowed for a clear presentation of findings that can inform policy and targeted interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Inclusion and Exclusion criteria\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.6.1. Inclusion Criteria\u003c/h2\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSmall-scale farmers actively engaged in crop production within the selected regions and with direct experience in pesticide use.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLicensed pesticides retailers operating within the study regions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHealthcare providers (doctors, nurses, clinical officers) employed in health facilities within the target areas and involved in treating pesticide poisoning or related health conditions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAll participants had to be at least 18 years of age and willing to provide informed consent.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.6.2. Exclusion Criteria\u003c/h2\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIndividuals are not directly involved in pesticide use, sale, or management.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRespondents under the age of 18.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eParticipants are unwilling or unable to provide informed consent.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLarge-scale commercial farmers, as the focus was on smallholder systems.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Sample Size and Sampling Procedure\u003c/h2\u003e \u003cp\u003eThe sample size was determined based on the estimated population of small-scale farmers, pesticides retailers, and healthcare providers in the selected regions, using standard sample size calculation formulas to ensure representativeness and statistical power. Multistage sampling was employed: regions were purposively selected, followed by random selection of wards, villages, and respondents within each group. Proportional allocation was used to ensure adequate representation from each region. Replacement sampling was applied where initial respondents were unavailable or declined participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Quality Control\u003c/h2\u003e \u003cp\u003eTo ensure data quality and reliability, research assistants were recruited from local hospitals and underwent comprehensive training led by subject matter experts. Training covered the study\u0026rsquo;s objectives, ethical considerations, and rigorous administration of the data collection instruments. Field supervisors conducted spot checks and regular debriefings to address challenges and maintain consistency in data collection. Pilot testing of the questionnaires was also performed to refine question clarity and instrument reliability prior to full-scale deployment.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Results and Inferences for Farmers\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Distribution of respondents per region\u003c/h2\u003e \u003cp\u003eThe results from Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provide valuable insights into the distribution of participants across various regions in Tanzania. A total of 528 respondents were surveyed, which allows for a diverse representation that is crucial for understanding pesticide use and safety. The region of Iringa has the highest number of respondents, totaling 191, which accounts for 36.2% of the overall sample. This significant representation suggests that findings from Iringa may substantially influence the overall conclusions and recommendations derived from the study. Following Iringa, Morogoro has 129 respondents (24.4%), contributing another notable proportion of the dataset. This region's presence further enriches the understanding of agricultural practices and challenges faced in pesticide management. In contrast, Arusha has the smallest representation, with 56 respondents (10.6%). While the insights from Arusha are valuable, the limited sample size may restrict the generalizability of findings from this area. Mwanza and Shinyanga present intermediate contributions to the dataset, with 72 (13.6%) and 80 (15.2%) respondents, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eRegion of respondent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArusha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIringa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMorogoro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMwanza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShinyanga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Gender of farmers\u003c/h2\u003e \u003cp\u003eThe results presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provide critical insights into the demographic composition of the survey participants regarding gender. Out of the total of \u003cb\u003e528 respondents\u003c/b\u003e, a significant majority are \u003cb\u003emale\u003c/b\u003e, with \u003cb\u003e416 participants\u003c/b\u003e, representing \u003cb\u003e78.7%\u003c/b\u003e of the sample. In contrast, the \u003cb\u003efemale respondents\u003c/b\u003e total \u003cb\u003e112\u003c/b\u003e, accounting for \u003cb\u003e21.3%\u003c/b\u003e of the total participants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGender distribution among respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGender of respondent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3. Education Level of Farmers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the distribution of education levels among small-scale farmers in the survey sample. The results indicate a clear predominance of farmers with lower formal education. Specifically, the majority of respondents, 69.7%, reported completing Standard VII, which corresponds to primary education. This is followed by 19.2% who completed Form IV, representing secondary education. Only a small fraction of farmers achieved higher levels of education: 1.9% reached Form VI, 1.1% attained certificates, 1.3% obtained diplomas, and 1.7% held degrees. Notably, 5.0% of the farmers surveyed had never attended formal school at all.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4. Farmers‟ Access to Pesticides Safe Use Training\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides an overview of farmers\u0026rsquo; access to training on the safe use of pesticides across five regions in Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. The data reveals that a significant majority of farmers have not received any formal training on pesticide risk reduction. Overall, 78.1% (406 out of 520) of respondents indicated they had not received such training, while only 21.9% (114 respondents) reported having participated in training sessions.\u003c/p\u003e \u003cp\u003eRegionally, Iringa demonstrates the highest proportion of trained farmers, with 29.9% having received training, followed by Morogoro at 23.4%. In contrast, Arusha, Mwanza, and Shinyanga lag behind, with only 16.1%, 12.5%, and 13.8% of respondents, respectively, reporting any form of pesticide risk reduction training. The data also shows that the majority of farmers in these regions, especially in Arusha (83.9%), Mwanza (87.5%), and Shinyanga (86.3%) lack essential training on safe pesticide handling.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003edetails related to training on safe use of pesticides\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAny training in pesticides\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e \u003cp\u003eRegion of respondent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eArusha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIringa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMorogoro\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMwanza\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eShinyanga\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e87.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e86.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e78.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e13.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e184\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e128\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e520\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.1.5. Service Providers of Pesticides Safe Use Training to Farmers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the various organizations and entities that provide training on the safe use of pesticides to farmers. The most significant contributor is the agricultural extension officers, who account for 35.5% of the training provided. This highlights the central role that government and public extension services play in disseminating critical safety information to small-scale farmers. The next most prominent provider is the Vegetable Seeds Company, responsible for 15.5% of the training, followed by \"Feed the Future,\" an initiative or organization contributing 12.7%.\u003c/p\u003e \u003cp\u003eOther sources of training include TAHA, SUA, Nafaka USAID, and Osho, each accounting for 3.6% or less, and a range of additional organizations such as Syngenta, Seedco, various private companies, and specific farmer training centers, each with smaller shares of the training landscape. Notably, a long tail of organizations\u0026mdash;including NGOs, farmer associations, and commodity boards\u0026mdash;provide marginal but nonetheless important support, often tailored to specific crops or local needs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.1.6. Farmers\u0026rsquo; Source of Information on Pesticides Use\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrates where farmers most commonly seek technical information and support regarding pesticide use. The data reveal that the majority of farmers rely on pesticide sellers as their primary source of technical guidance, with 53.2% of respondents identifying sellers as their main point of information. This underscores the influential role that pesticide retailers play in shaping farmers\u0026rsquo; knowledge and practices with respect to pesticide application and safety.\u003c/p\u003e \u003cp\u003eThe second most utilized source is pesticide labels, referenced by 43.8% of farmers. This finding points to the importance of clear, comprehensible labeling on pesticide products, as many farmers turn directly to the product itself for guidance. Agricultural extension staff are the third most common source, cited by 24.1% of respondents. While extension officers are recognized as important trainers, their reach appears to be more limited compared to sellers and labels.\u003c/p\u003e \u003cp\u003eAdditionally, 23.5% of farmers report relying on their own knowledge, which may be based on personal experience or informal learning, while a small fraction (2.3%) turns to fellow farmers for advice. The relatively low reliance on peer-to-peer information sharing suggests that formal and commercial sources dominate the flow of technical support.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.1.7. Information on Agriculture pests\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the types of agricultural pests most reported by small-scale farmers as affecting crop production. The data reveal that insect pests are overwhelmingly perceived as the primary challenge, with 96.2% of respondents identifying them as the main threat to their crops. This finding underscores the significant impact of insect infestations on agricultural productivity and the likely heavy reliance on insecticides in pest management strategies.\u003c/p\u003e \u003cp\u003eFungal diseases are the second most frequently reported issue, cited by 63.9% of respondents. This indicates that plant pathogens also represent a substantial threat to yields and may necessitate the use of fungicides as a common crop protection measure. Weeds are reported as a major concern by 20.7% of farmers, reflecting the ongoing battle with unwanted plants that compete for nutrients and resources. Nematodes are the least frequently mentioned, with only 1.3% of farmers identifying them as a significant problem.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.1.8. Agriculture pests and regions\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides a detailed breakdown of the types of agricultural pests reported by farmers across five key regions in Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. Across all regions, insect pests emerge as the most pervasive problem, accounting for 53% of all pest issues reported (507 out of 960 cases). This trend is particularly pronounced in Shinyanga, where 68.4% of respondents identified insect pests as their primary challenge, as well as in Mwanza (57.6%) and Morogoro (52.4%). Iringa and Arusha also report high incidences of insect pests, at 47.2% and 51.8% respectively.\u003c/p\u003e \u003cp\u003eFungal diseases are the next most common pest type, making up 35% of reported cases. Iringa stands out with 42.9% of farmers reporting fungal problems, closely followed by Mwanza (40.8%) and Arusha (38.6%). In contrast, Morogoro reports a lower incidence of fungal diseases at 17.3%, suggesting regional variation in crop vulnerability or pathogen prevalence.\u003c/p\u003e \u003cp\u003eWeeds are a significant concern in Morogoro, where 27.9% of farmers identified them as a primary pest, compared to less than 10% in most other regions. This suggests localized weed management challenges that may be tied to specific cropping systems or environmental factors.\u003c/p\u003e \u003cp\u003eNematode infestations are rare across all regions, comprising just 1% (7 cases) of the total reports, with occasional cases in Arusha, Morogoro, and Mwanza, and none in Iringa and Shinyanga.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Regions and infestation of agricultural pests\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c12\" namest=\"c3\"\u003e \u003cp\u003eRegion of Respondent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c14\" namest=\"c13\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eARUSHA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIRINGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMOROGORO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eMWANZA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eSHINYANGA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFungal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e40.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e30.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInsect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e57.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e68.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeeds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e27.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNematodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.1.9. Places Where Farmers Acquire Pesticides\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e reveals the primary channels through which small-scale farmers obtain pesticides. The overwhelming majority\u0026mdash;513 out of 540 respondents, or 95.0%, purchased their pesticides from licensed selling shops. This indicates that regulated, formal retail outlets are the dominant source for pesticide procurement, suggesting a potentially positive environment for ensuring product quality, proper labeling, and regulatory compliance.\u003c/p\u003e \u003cp\u003eIn contrast, a small proportion of farmers rely on less formal sources: 3.7% (20 respondents) acquire pesticides from open markets, and just 1.3% (7 respondents) obtain them directly from vendors. These informal channels may pose risks, including the possibility of counterfeit products, lack of proper usage instructions, and limited safety assurances.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003einformation of pesticides availability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"3\" nameend=\"c2\" namest=\"c1\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003ePlaces where Pesticides are brought\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAt licensed pesticides selling shops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAt open market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrom pesticides vendors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e540\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.1.10. Use Category of Pesticides by Regions for Farmers\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e outlines the distribution of pesticide types used by small-scale farmers, categorized into fungicides, insecticides, and herbicides. Of the total 926 pesticide applications reported, insecticides constitute the largest share, with 469 instances, accounting for 50.65%. This aligns with earlier findings that insect pests are the most pressing agricultural challenge, reinforcing the heavy reliance on insecticidal solutions.\u003c/p\u003e \u003cp\u003eFungicides follow, comprising 323 applications or 34.88% of the total. This substantial use reflects the prominence of fungal diseases as a significant threat to crop health. Herbicides, while still relevant, are used less frequently\u0026mdash;accounting for 134 applications or 14.47% of the total. The comparatively lower use of herbicides may indicate either a reduced prevalence of weed pressure across surveyed farms or a preference for alternative weed management strategies.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of the categories of pesticides\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eUse category of\u003c/p\u003e \u003cp\u003epesticides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFungicide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eInsecticide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.65%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHerbicide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.47%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e926\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.00%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e3.1.11. Management of empty pesticides containers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the methods by which farmers dispose of empty pesticide containers. The most common practice is leaving used containers unattended on the farm, accounting for 45.4% of responses. This method poses serious environmental and health risks, as unattended containers may leak residues, contaminate soil or water, and be accessed by children or animals.\u003c/p\u003e \u003cp\u003eBurning empty containers in the open farmyard spaces is the second most prevalent approach, representing 30.9% of disposal practices. While burning may reduce physical waste volume, it can release harmful chemical residues into the air, creating inhalation hazards and potentially contaminating nearby areas.\u003c/p\u003e \u003cp\u003eA further 16.7% of farmers report burying containers in the farm, which may limit surface exposure but can lead to soil contamination and leaching into groundwater if not done properly. Finally, only 7.0% of respondents rinse, puncture, and leave containers in the farmyard method that, while still not ideal, indicates some awareness of safer disposal practices.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Results and Inferences for Pesticide Sellers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the regional distribution of pesticide sellers across the surveyed areas. Iringa leads with the largest share, encompassing 36% of all pesticide sellers. Following Iringa, Morogoro accounts for 24% of sellers, while Shinyanga represents 15%, Mwanza holds 14%, and Arusha has the smallest proportion at 11%. This distribution suggests that pesticide retail activity is more concentrated in Iringa and Morogoro, possibly reflecting higher agricultural activity, better-developed retail infrastructure, or stronger market demand in those regions. Conversely, the lower representation in Arusha may indicate a smaller retail network or limited access to pesticide products in that area.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Gender Distribution of Pesticides Retailers\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e presents the gender composition of the pesticide retailers surveyed. Of the 102 retailers, 52 (51%) are male and 50 (49%) are female. This near-equal distribution contrasts with the male-dominated pattern observed among small-scale farmers in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The balanced representation indicates that women are actively involved in the agricultural input supply chain, particularly in pesticide retailing.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Pesticides Retailers based on sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable Sex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender of respondent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e102\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Education Level of Pesticides Retailers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates the educational attainment of pesticide sellers. The highest proportion, 31.1%, completed Form IV (equivalent to secondary school level). This is closely followed by those holding a degree\u0026mdash;27.3% of sellers. Certificates and Standard VII (primary education) each account for 15.5%, while Form VI (advanced secondary) represents 9.7%. Only 1% of sellers have never attended formal school.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3. Age Group of Pesticides Sellers\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e provides an age distribution profile of pesticide retailers. The largest segment, comprising 54.4% of respondents, falls within the 21\u0026ndash;30 years age group. The next most represented group is those aged 31\u0026ndash;40 years, accounting for 30.1%. Older age groups are markedly smaller in number: 5.8% of retailers are aged 51\u0026ndash;60 years, 4.9% are over 60, 2.9% are 20 years and below, and just 1.9% fall in the 41\u0026ndash;50 years category.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4. Training on Pesticides Risk Reduction for Pesticides Sellers\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e sheds light on the prevalence of pesticide risk reduction training among retailers across five Tanzanian regions. Out of 103 surveyed sellers, a majority\u0026mdash;62.1% (64 individuals)\u0026mdash;have received training on safe pesticide use, while 37.9% (39 individuals) have not. Regionally, Morogoro exhibits the highest training coverage, with 18 of 19 retailers trained and just one untrained. Arusha follows with 22 trained versus 14 untrained retailers. Iringa shows moderate engagement, with 12 trained and five untrained.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of training to the pesticide\u0026rsquo;s sellers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c13\" namest=\"c3\"\u003e \u003cp\u003eRegion of respondent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c15\" namest=\"c14\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eArusha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIringa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMorogoro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eMwanza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eShinyanga\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAny training in pesticides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e35.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e37.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e62.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e35.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e18.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e10.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e19.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e\u003cb\u003e103\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section3\"\u003e \u003ch2\u003e3.2.5. \u003cb\u003eService Providers for Training on Pesticides Risk Reduction for Pesticide Sellers\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e highlights the key organizations responsible for providing training on pesticide risk reduction to pesticide sellers. Tanzania Plant Health and Pesticides Authority (TPHPA) initially called the Tropical Pesticides Research Institute (TPRI), through its PM2 courses, stands out as the dominant provider, accounting for 48.2% of the training delivered. This underscores TPRI\u0026rsquo;s central role in equipping retailers with essential skills and knowledge. The next most significant contributor is non-governmental organizations (NGOs), which deliver 10.8% of the training, followed by pesticide companies at 4.8%. Smaller contributions come from institutions such as Hort-Tengeru, TOSC, TFDA, and district extension officers, each delivering around 1.2% to 2.4% of training.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Results and Inferences for Health Care Providers\u003c/h2\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. Incidences of pesticides poisoning\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e presents data on the incidence of pesticide exposure-related cases reported by healthcare providers across five Tanzanian regions. Out of 515 total responses, 58.8% (303 cases) indicated occurrences of pesticide-related exposures or poisoning, while 41.2% (212 cases) reported no such incidents. Regionally, Iringa stands out with the highest prevalence of reported incidents\u0026mdash;68.5% of respondents noted pesticide exposure cases\u0026mdash;followed by Arusha at 62.7%, Mwanza at 62.0%, and Morogoro at 57.9%. In contrast, Shinyanga reported the lowest incidence, with only 32.5% of respondents acknowledging pesticide exposure cases, and 67.5% reporting none.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncidences of pesticides poisoning\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c13\" namest=\"c3\"\u003e \u003cp\u003eRegion of respondent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c16\" namest=\"c14\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eArusha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIringa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMorogoro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eMwanza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eShinyanga\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c16\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eIncidents related to exposure pesticides\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e38.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e41.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c16\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e62.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e32.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e58.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c16\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e184\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e121\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e\u003cb\u003e515\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c16\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. Information of management of Pesticides Poisoning Cases\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e highlights critical gaps in healthcare providers' preparedness and knowledge regarding pesticide poisoning. Among 62 respondents, a striking 93.5% (58 individuals) reported having no formal training in treating pesticide intoxications, leaving only 6.5% (4 individuals) with such training. Regarding awareness of pesticides commonly used by farmers in their facility\u0026rsquo;s catchment area, only 54.7% (35 out of 64 respondents) indicated familiarity, while 45.3% (29 individuals) lacked this knowledge. Similarly, when asked about pesticides most frequently associated with poisoning or exposure incidents, just under 49.2% (31 out of 63 respondents)\u0026mdash;claimed awareness, while 50.8% (32 individuals) did not.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKnowledge and prevalence of pesticides poisoning cases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAny training in treatment of pesticide intoxications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of pesticides commonly used by farmers in the areas of health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of pesticides most often reported to cause poisoning/exposures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. Challenges on Management of Pesticides poisoning cases\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e reveals that a significant majority of healthcare providers\u0026mdash;60% (37 out of 62 respondents) reported encountering challenges when providing first aid or treatment for pesticide intoxication cases, while only 40% (25 respondents) indicated no difficulties. This finding underscores the substantial obstacles faced by medical personnel in effectively managing pesticide-related emergencies. These challenges may stem from factors such as inadequate training, limited access to necessary medical supplies, lack of standardized treatment protocols, or insufficient knowledge of the specific pesticides involved.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChallenge encounter in handling pesticide poisoning\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAny challenges in providing first aid/treatment of pesticides intoxications cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe distribution of survey participants varied notably by region, with Iringa and Morogoro showing the highest representation. This likely reflects differences in agricultural intensity, climate, or local governance structures that influence pesticide use and safety practices (Alyaseri, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regions with more respondents may also have been easier to access for data collection, suggesting potential sampling bias in coverage. A marked gender imbalance emerged among smallholder farmers, with far more men than women participating. This aligns with broader research showing that men often dominate farming roles, while women remain underrepresented due to cultural norms and limited access to resources (Mwakalasya et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Women\u0026rsquo;s marginalization in training and decision-making may elevate their vulnerability to unsafe pesticide use (Abasilim et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; A. Ngowi et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Tailored, gender-sensitive interventions are therefore essential to ensure equitable access to safety training.\u003c/p\u003e \u003cp\u003eEducational attainment among farmers was generally low, primarily limited to primary schooling. This educational gap can impede the comprehension of pesticide labels and safety protocols, reducing the effectiveness of training programs (Atreya et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ngoya et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Addressing this requires training that is context-appropriate and accessible to those with limited formal education. A substantial portion of farmers lacked formal training in pesticide risk reduction, particularly in certain regions This deficiency increases risks to both human health and the environment (Heredia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) The uneven geographic distribution of training underscores the need for targeted outreach in underserved areas.\u003c/p\u003e \u003cp\u003eThis study identified that agricultural extension officers were the main providers of pesticide risk reduction training, yet reliance on this single source may strain available resources. Expanding partnerships to include NGOs, agro-dealers, and farmer groups could improve reach and diversify training methods, enhancing overall program effectiveness. Similar efforts have been reported in neighbor countries such as Kenya and Uganda (Mukasa et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Muriithi et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSources of information on safe use of pesticides to the famers are very important (Kariathi et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This study suggests that farmers involved in this suggest depending to the pesticide sellers for technical guidance, followed by product labels and extension staff. While accessible, seller-provided information often lacks safety focus, and labels may be difficult to understand similar findings were reported by E. E. Lekei et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e while he conducting assessment to pesticides retailers. Strengthening extension services and ensuring accuracy across all information sources is critical for promoting safe practices.\u003c/p\u003e \u003cp\u003eIn Tanzania the common infested pests in agriculture are insects, fungi, weeds, Insect, rodent, birds, nematodes (A. V. F. Ngowi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The findings of this study identified insects, and fungal diseases were the most reported threats, driving high use of insecticides and fungicides. Interventions should therefore concentrate on improving safe handling and application of these pesticide types. The relatively lower concern for weeds and nematodes may reflect either lower prevalence or gaps in awareness, underscoring the need for region-specific education.\u003c/p\u003e \u003cp\u003eThis study shows that pest prevalence varies by region, with insect pests being universal but other pest types differ significantly by location. This underscores the need for locally adapted pest management strategies and extension messaging (Smith et al., 2018). The findings show that most farmers purchased pesticides from licensed retailers. This presents an opportunity to reinforce safe handling through regulated channels, though the limited presence of informal supply chains highlights the necessity of continuous monitoring to safeguard product safety and reliability (Kimani \u0026amp; Mwaniki, 2020). This study identified usage patterns revealed insecticides as the most frequently used category, followed by fungicides and herbicides. Such evidence suggests that safety training should prioritize these products while also addressing proper herbicide use and environmental considerations (Osei et al., 2017). Unsafe disposal of empty pesticide containers was widespread, with common practices such as abandonment and open burning posing environmental and public health risks; therefore, interventions should include training on safe disposal techniques and provision of designated facilities (Mburu \u0026amp; Ngugi, 2016).\u003c/p\u003e \u003cp\u003eIringa and Morogoro exhibited higher concentrations of pesticide retailers, making them suitable hubs for training and compliance monitoring, whereas regions like Arusha with fewer retailers may benefit from mobile or targeted outreach strategies to reach dispersed stakeholders (Chikoye et al., 2015). In contrast to the farming community, gender distribution among pesticide retailers was more balanced; engaging female retailers in training efforts could enhance the dissemination of safety messages, particularly to women farmers who are frequently underrepresented (Alhassan \u0026amp; Salifu, 2019). Retailers generally possessed moderate to high educational levels, with the majority holding secondary or tertiary qualifications; however, the existence of a small minority with no formal education emphasizes the importance of inclusive training materials that cater to varying literacy levels (Mwangi \u0026amp; Kariuki, 2014). The retail workforce was predominantly young (under 41), which may facilitate the adoption of new safety practices, though the limited presence of older, more experienced individuals signals a need for mentorship and intergenerational knowledge transfer (Dossou \u0026amp; Mitchell, 2021).\u003c/p\u003e \u003cp\u003eTraining among pesticide retailers displayed regional disparities, with Mwanza and Shinyanga showing notable gaps, indicating the importance of region-specific capacity-building initiatives to ensure consistent safe handling practices (Abate et al., 2013). Training was primarily delivered by formal institutions, with minimal involvement from NGOs or private actors, suggesting that expanded collaboration could enhance both reach and sustainability of training programs (Van den Berg \u0026amp; Jiggins, 2007). Incidence of pesticide poisoning varied by region, with higher rates in Iringa, Arusha, Mwanza, and Morogoro, possibly due to factors such as limited training, unsafe handling, or inadequate use of protective equipment, necessitating tailored prevention and response strategies (Jaga \u0026amp; Dharmani, 2005). Most healthcare providers lacked training in pesticide poisoning management and were unfamiliar with many commonly used pesticides, highlighting the need for cross-sector collaboration to strengthen health sector capacity for improved diagnosis and treatment (London et al., 2012). Healthcare providers also reported significant challenges in treating pesticide poisoning, underscoring the need for specialized training, improved access to medical supplies, and stronger coordination between agricultural and health sectors to effectively mitigate health risks (Ngowi et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In summary, this study reveals significant regional, gender, and educational disparities in pesticide use, safety practices, and access to information across Tanzania\u0026rsquo;s agricultural sector. High pesticide usage, particularly of insecticides and fungicides, coupled with widespread unsafe disposal practices, underscores urgent needs for targeted training and improved regulatory oversight. The predominance of men among farmers and the marginalization of women and less-educated individuals highlights the necessity for gender-sensitive, inclusive interventions. Regional disparities in retailer concentration, training availability, and healthcare preparedness further emphasize the importance of locally adapted strategies and cross-sector collaboration. Expanding the roles of NGOs, private actors, and female retailers\u0026mdash;while strengthening extension services and healthcare capacity\u0026mdash;will be vital for promoting safe pesticide use and reducing health and environmental risks. Ultimately, a multifaceted and context-specific approach is essential to address the complex challenges identified, ensuring equitable and sustainable improvements in pesticide management and rural health outcomes.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study provides a detailed and regionally nuanced understanding of pesticide use, safety practices, and associated health risks among small-scale farmers, pesticide retailers, and healthcare providers in five key agricultural regions of Tanzania: Arusha, Iringa, Morogoro, Mwanza, and Shinyanga. The findings reveal significant gaps and challenges at multiple points along the agricultural value chain, as well as opportunities for targeted interventions. Policy and practice should prioritize the expansion of accessible, context-appropriate training programs for farmers, retailers, and healthcare providers; strengthen regulatory enforcement and monitoring of pesticide distribution and use; promote safer disposal methods for pesticide waste; and enhance collaboration between government, non-governmental organizations, and the private sector. Gender-sensitive approaches and tailored interventions for underserved regions are essential for equitable progress. Ultimately, advancing pesticide risk reduction in Tanzania will require sustained commitment, increased resources, and coordinated efforts at all levels\u0026mdash;from local communities to national authorities\u0026mdash;to protect human health, preserve environmental integrity, and support the country\u0026rsquo;s agricultural development.\u003c/p\u003e"},{"header":"6. Recommendation","content":"\u003cp\u003eThis study recommends to expand the practical and inclusive training programs, strengthening regulatory enforcement and monitoring programs, Improve pesticides waste management, enhance agricultural extension Services equipped with updated knowledge, design and implement gender-sensitive strategies to empower women on pesticides on safe use of pesticides and pesticides risk reduction, strengthen healthcare capacity through integrating pesticide poisoning management into the training curricula of healthcare providers, encourage ongoing research and surveillance on pesticide use, health impacts, and environmental outcomes, extending beyond the five regions studied here in to inform policy adjustments and enable timely, evidence-based interventions. Through implementing these recommendations, Tanzania can advance toward safer and more sustainable agricultural practices, reducing risks to human health and the environment while supporting the productivity and well-being of small-scale farming communities.\u003c/p\u003e"},{"header":"7. Limitation of the study","content":"\u003cp\u003eThe project faced several limitations, and this included, time allocated for the project being limited as compared to the magnitude of the workload which needed more time to comprehend exhaustively the required information. The survey report findings and interpretation are for the five regions under the project which were Arusha, Iringa, Mwanza, Shinyanga and Morogoro and these do not reflect the general situation of the country, and hence more survey is objectively important.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and accordance\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;All experimental protocols involving human participants were reviewed and approved by the Tanzania’s National Institute of Medical Research (NIMR) with Reference No. NIRM/HQ/R.8a/Vol.IX/2742.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Guidelines (Helsinki Declaration)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to the institutions and academics that provided access to this survey.\u003c/p\u003e\n\u003ch1\u003eConsent to Participants\u0026nbsp;\u003c/h1\u003e\n\u003cp\u003eParticipation in the study was voluntary, and informed consent was obtained from all participants prior to completing the survey.\u003c/p\u003e\n\u003ch1\u003eAvailability of data and materials\u003c/h1\u003e\n\u003cp\u003eAll data generated or analyzed in this study are included within this article.\u003c/p\u003e\n\u003ch1\u003eCompeting interests\u003c/h1\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003ch1\u003eFunding\u003c/h1\u003e\n\u003cp\u003eThe study was funded by the Food and Agriculture Organization of the United Nations (FAO) through the project on \u003cem\u003eCapacity-Building Related to Multilateral Environmental Agreements in ACP Countries - Phase 3 (\"ACP/MEAs 3\" – GCP/GLO/006/EC)\u003c/em\u003e\u003c/p\u003e\n\u003ch1\u003eAuthors' contributions\u003c/h1\u003e\n\u003cp\u003eRM, JB, RO, and DM were responsible for developing the manuscript, while JK, SR, MD, WH, IS, KT and JV contributed by reviewing and editing.\u003c/p\u003e\n\u003ch1\u003eAuthors' affiliations\u0026nbsp;\u003c/h1\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eTanzania Plant Health and Pesticide Authority (TPHPA), Directorate of Pesticide, P.O. Box 3024, Arusha, Tanzania\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eDepartment of Global Health and Biomedical Sciences, Nelson Mandela African Institution of Science and Technology, P. O. Box 447, Arusha-Tanzania.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eDepartment of Internal Medicine, Kilimanjaro Christian Medical Centre, Moshi, Tanzania\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eDepartment of Internal Medicine, KCMC University, Moshi, Tanzania\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eFood and Agriculture Organization of the United Nations (FAO). FAO Headquarters - Rome, Italy.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eFood and Agriculture Organization of the United Nations (FAO), Dodoma, Tanzania\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eFood and Agriculture Organization of the United Nations (FAO), Harare, Zimbabwe.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eFood and Agriculture Organization of the United Nations (FAO), Dar es Salaam, Tanzania.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbasilim C, Persky V, Sargis RM, Day T, Tsintsifas K, Daviglus M, Cai J, Freels S, Grieco A, Peters BA, Isasi CR, Talavera GA, Thyagarajan B, Davis M, Jones R, Sjodin A, Turyk ME. (2025). 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(2024). \u003cem\u003eParkinson \u0026rsquo; s Disease in Sub-Saharan Africa: Pesticides as a Double-Edged Sword\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3233/JPD-230409\u003c/span\u003e\u003cspan address=\"10.3233/JPD-230409\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pesticide risk reduction, small-scale farmers, pesticide retailers, healthcare providers, Tanzania, agricultural practices, training, environmental health","lastPublishedDoi":"10.21203/rs.3.rs-8540934/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8540934/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eAgriculture is a cornerstone of Tanzania\u0026rsquo;s economy, with most production driven by small-scale farmers. In efforts to manage pest-related crop losses, pesticide use has increased significantly, heightening concerns related to human health, environmental sustainability, and regulatory compliance. This study examines the knowledge gaps, practices, and systemic factors influencing pesticide risk reduction among small-scale farmers, pesticide retailers, and healthcare providers in five agriculturally significant regions of Tanzania.\u003c/p\u003e\u003ch2\u003eMethodology:\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted in Arusha, Iringa, Morogoro, Mwanza, and Shinyanga, purposively selected for their agricultural productivity and diversity. Data was collected via semi-structured questionnaires from 528 farmers, 102 pesticide retailers, and 64 healthcare providers, focusing on pesticide practices, risk reduction knowledge, training, and health outcomes. Multistage sampling ensured diverse representation, and data were analyzed using descriptive statistics with the R Statistical Package.\u003c/p\u003e\u003ch2\u003eResults and Discussion\u003c/h2\u003e \u003cp\u003eFindings revealed considerable regional and demographic variation in pesticide use and risk reduction practices. Most respondents were male (78.7%) and had primary-level education (69.7%), with limited access to pesticide risk reduction training\u0026mdash;only 21.9% of farmers reported formal training. Pesticide sellers were more gender-balanced but had uneven training coverage, especially in Mwanza and Shinyanga. Most farmers sourced pesticides from licensed retailers (95%), yet unsafe disposal of empty containers (e.g., leaving on-site or burning) was common, posing environmental hazards. Technical information was mainly acquired from pesticide sellers (53.2%) and product labels (43.8%), while agricultural extension officers played a key but limited role in safety training. Insect pests and fungal diseases dominated as crop threats, driving high insecticide (50.7%) and fungicide (34.9%) use. Healthcare providers reported frequent pesticide exposure cases (58.8%), particularly in Iringa, but 93.5% lacked formal training in managing poisoning incidents. Most healthcare providers faced significant challenges in treating such cases.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe study reveals significant gaps in pesticide risk-reduction knowledge, training, and practice among smallholder farmers and related sectors in Tanzania. Key recommendations include expanding practical training for farmers and retailers, strengthening regulatory enforcement, improving pesticide waste disposal, and enhancing coordination among government, NGOs, and the private sector. Addressing gender and regional disparities is also essential to ensure inclusive progress. The findings highlight the urgent need for integrated actions to protect human health, the environment, and agricultural productivity.\u003c/p\u003e","manuscriptTitle":"Pesticide Use Safety Practices and Knowledge Gaps Among Small-scale Farmers, Retailers and Healthcare Providers in Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 09:10:25","doi":"10.21203/rs.3.rs-8540934/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-02T12:23:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T10:54:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T09:16:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304931570212477871868107371816787943083","date":"2026-02-18T08:40:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99291964658583243087688691491591653309","date":"2026-02-15T09:04:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333315226549613530735223430072076526224","date":"2026-02-13T08:31:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-13T08:14:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-13T08:13:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-24T16:34:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-24T11:51:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-01-24T11:46:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02c0fe57-d279-4e3f-89b0-57937e725851","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T11:54:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 09:10:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8540934","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8540934","identity":"rs-8540934","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}