Assessment of Unintentional Acute Pesticide Poisoning (UAPP) Amongst Cotton Farmers in Tanzania
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Study Population, Sample Size Determination, and Sampling
2.3. Data Collection
2.4. Data Analysis
3. Results
3.1. Social Demographic Characteristics of Respondents
3.2. Conditions of Use of Pesticides in Cotton Production
3.3. Pesticide Poisoning
3.4. Symptoms Reported
4. Discussion
4.1. Pesticides of Concern
4.2. Health and Economic Consequences of UAPP
4.3. Conditions of Use
4.4. Pests Targeted by HHPs and Available Alternatives
Method | Example | Country | Reference |
---|---|---|---|
Cultural control | Cotton intercropped with maize had significantly less damage (0.5%) than monocropped cotton (5–9%). In the cotton–maize intercropping system, H. armigera preferred to lay eggs on the maize plants. | China | Chi, Zhang and Dong [88] |
Cotton–basil intercropping significantly reduced total pest infestation and led to a 50% reduced abundance of the pink bollworm (Pectinophora gossypiella) in comparison with non-intercropped plots. | Egypt | Schader, et al. [102] | |
Intercropping cotton with sesame and the release of Trichogramma. chilonis adults alternated with neem provided significantly better control of spotted bollworm, Earias vittella, and pink bollworm, Pectinophora gossypiella, compared to the control. | India | Devi, et al. [103] | |
Field experiments conducted over a 6-year period showed that the densities of H. armigera, Earias spp., and Sudan bollworm, Diparopsis watersi, were significantly lower in topped compared with non-topped cotton plots. | Mali | Renou, et al. [104] | |
Biological control | Application of a supplementary food spray product attracted beneficial insects and significantly reduced the number of pests (including Helicoverpa spp.) and increased cotton yields and profitability. | Ethiopia/Benin | Mensah, Vodouhe, Sanfillippo, Assogba and Monday [83]; Amera, Mensah and Belay [84] |
Biopesticdes | Application of neem oil in the laboratory and the field resulted in a considerable reduction in the hatching of the eggs of H. armigera. | India | Patel, et al. [105] |
100% mortality of red cotton stainers was reported following treatment with B. bassiana isolates. | India | Moorthi, et al. [106] | |
B. bassiana and Metarhizium rileyi were as effective as lambda-cyhalothrin or chlorpyrifos against cotton stainers, with no significant difference in seed cotton yield. | South Africa | Malinga and Laing [97] | |
Treatment with Nomuraea rileyi led to 87% mortality of H. armigera. | South Africa | Hatting [107] | |
Treatment with B. thuringiensis led to a 95–100% and 76% H. armigera mortality under laboratory and field conditions, respectively. | South Africa | Malinga and Laing [96] | |
Integrated package | CABI Plantwise guidance for H. armigera management in cotton in Tanzania recommends regular scouting for pests and using neem-based products a max. of 3 times (usually 2.5–3 litres/ha or 50–60 mL/20 litres of water, or 20–50 g of neem seed cake or powder/litre water) to control small 1st–2nd instars of larvae if the ratio is less than 1:2 (bollworm: beneficial organisms). Field sanitation involving the removal of cotton plant debris and ratoon cotton as soon as harvesting is over is also recommended. | Tanzania | Ndomba and Kitandu [90] |
CABI Plantwise guidance for D. cingulatus management in Tanzania includes regular monitoring, hand-picking, and destroying the bugs in small plots at the beginning of infestations or spraying fresh custard apple leaf extract or pyrethrum powder. Field sanitation involving the removal of cotton plant debris and ratoon cotton as soon as harvesting is over is also recommended. | Tanzania | Mussa [77] |
4.5. Limitations
5. Conclusions and Recommendations
- Phase out highly hazardous pesticides and prioritise the elimination of the four pesticides most commonly involved in poisoning incidents in this study—namely profenofos, cypermethrin, chlorpyrifos, and lambda-cyhalothrin.
- Make less hazardous alternatives available and support farmers to access them.
- Enforce regulatory control measures to prevent exposure to banned or restricted pesticides.
- Provide information and training to farmers and farm workers on pesticide hazards and on ways to reduce pesticide-related risks, including PPE and, more importantly, on alternative pest management strategies that are based on agroecological or IPM principles.
- Scale up community self-surveillance to complement poison centre/hospital-based pesticide poisoning surveillance.
- More research into the health effects of co-formulations is needed, particularly those containing pyrethroids and organophosphates.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Gender | ||||
---|---|---|---|---|
Total n (%) | Male n (%) | Female n (%) | ||
Gender | 1074 (100) | 881 (82) | 193 (18) | |
Age | 14–18 | 8 (1) | 7 (1) | 1 (1) |
18–40 | 567 (53) | 464 (53) | 103 (53) | |
40–60 | 407 (38) | 331 (38) | 76 (39) | |
60+ | 84 (8) | 71 (8) | 13 (7) | |
Missing information | 8 (1) | 8 (1) | 0 | |
Occupation Type | Work on family farm * | 903 (85) | 746 (85) | 157 (81) |
Work on family farm and do hired work | 54 (5) | 48 (5) | 6 (3) | |
Only do hired work | 111 (10) | 81 (9) | 30 (16) | |
Missing information | 6 (1) | 6 (1) | 0 |
Activity When Poisoned (n = 501) | Total n (%) | Male n (%) | Female n (%) |
---|---|---|---|
Applying pesticides to a crop | 464 (93) | 418 (95) | 46 (73) |
Mixing/loading the pesticide ready to use | 23 (5) | 17 (4) | 6 (10) |
Entering a field treated with pesticides | 6 (1) | 0 | 6 (10) |
Other (please specify) | 5 (1) | 0 | 5 (8) |
Using pesticides in the home | 3 (1) | 3 (1) | 0 |
Variable | Category | B | S.E. | Wald | df | Sig. | Exp(B) | 95.0% C.I. for EXP(B) | |
---|---|---|---|---|---|---|---|---|---|
Lower | Upper | ||||||||
PPE | 0 items | 2.594 | 3 | 0.459 | |||||
1 item | 0.442 | 0.345 | 1.639 | 1 | 0.200 | 1.555 | 0.791 | 3.058 | |
2–3 items | 0.284 | 0.350 | 0.657 | 1 | 0.418 | 1.328 | 0.668 | 2.640 | |
>3 items | 0.297 | 0.362 | 0.672 | 1 | 0.412 | 1.345 | 0.662 | 2.735 | |
Occupation type | Work on family farm * | 1.363 | 2 | 0.506 | |||||
Work on family farm and do hired work | −0.191 | 0.206 | 0.862 | 1 | 0.353 | 0.826 | 0.551 | 1.237 | |
Only do hired work | 0.032 | 0.339 | 0.009 | 1 | 0.925 | 1.032 | 0.532 | 2.005 | |
Gender | 0.503 | 0.166 | 9.179 | 1 | 0.002 | 1.654 | 1.194 | 2.290 | |
Access to training | 0.265 | 0.147 | 3.267 | 1 | 0.041 | 1.303 | 0.978 | 1.737 | |
Age | −0.060 | 0.096 | 0.385 | 1 | 0.535 | 0.942 | 0.780 | 1.138 | |
Farm size | <1 ha | 3.785 | 3 | 0.286 | |||||
1–5 ha | 0.336 | 0.363 | 0.860 | 1 | 0.354 | 1.400 | 0.687 | 2.850 | |
5–15 ha | 0.453 | 0.256 | 3.149 | 1 | 0.076 | 1.574 | 0.954 | 2.597 | |
15 ha | 0.296 | 0.269 | 1.217 | 1 | 0.270 | 1.345 | 0.794 | 2.277 | |
Pesticides sold in original container | −0.276 | 0.321 | 0.738 | 1 | 0.390 | 0.759 | 0.405 | 1.424 | |
Constant | −1.590 | 0.729 | 4.763 | 1 | 0.029 | 0.204 |
Body System | Total n (%) | Male n (%) | Female n (%) |
---|---|---|---|
Nervous system | 476 (100) | 414 (100) | 62 (100) |
Hematopoietic system | 476 (100) | 414 (100) | 62 (100) |
Local effects on the skin | 367 (77) | 327 (79) | 40 (65) |
Respiratory system | 132 (28) | 109 (26) | 23 (37) |
Local effects on the eyes | 109 (23) | 100 (24) | 9 (15) |
Metabolic balance | 52 (11) | 44 (11) | 8 (13) |
Muscular system | 21 (4) | 21 (5) | 0 (0) |
Gastrointestinal system | 20 (4) | 16 (4) | 4 (6) |
Cardiovascular system | 18 (4) | 15 (4) | 3 (5) |
Renal system | 10 (2) | 9 (2) | 1 (2) |
Number of Occurrences | Total n (%) | Male n (%) | Female n (%) |
---|---|---|---|
1 | 236 (50) | 200 (48) | 36 (58) |
2 | 125 (26) | 108 (26) | 17 (27) |
3 | 73 (15) | 68 (16) | 5 (8) |
4 | 22 (5) | 19 (5) | 3 (4) |
5 | 10 (2) | 10 (2) | 0 |
6 | 8 (2) | 8 (2) | 0 |
8 | 1 (0.2) | 1 (0.2) | 0 |
11 | 1 (0.2) | 0 | 1 (2) |
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Kapeleka, J.A.; Ngowi, A.V.; Mng’anya, S.; Willis, S.E.; Salmon, J.P.; Tyrell, K.F.; Williamson, S.; Eddleston, M.; Stuart, A.M. Assessment of Unintentional Acute Pesticide Poisoning (UAPP) Amongst Cotton Farmers in Tanzania. Toxics 2025, 13, 300. https://doi.org/10.3390/toxics13040300
Kapeleka JA, Ngowi AV, Mng’anya S, Willis SE, Salmon JP, Tyrell KF, Williamson S, Eddleston M, Stuart AM. Assessment of Unintentional Acute Pesticide Poisoning (UAPP) Amongst Cotton Farmers in Tanzania. Toxics. 2025; 13(4):300. https://doi.org/10.3390/toxics13040300
Chicago/Turabian StyleKapeleka, Jones Ackson, Aiwerasia Vera Ngowi, Silvani Mng’anya, Sheila E. Willis, Joey P. Salmon, Keith F. Tyrell, Stephanie Williamson, Michael Eddleston, and Alexander M. Stuart. 2025. "Assessment of Unintentional Acute Pesticide Poisoning (UAPP) Amongst Cotton Farmers in Tanzania" Toxics 13, no. 4: 300. https://doi.org/10.3390/toxics13040300
APA StyleKapeleka, J. A., Ngowi, A. V., Mng’anya, S., Willis, S. E., Salmon, J. P., Tyrell, K. F., Williamson, S., Eddleston, M., & Stuart, A. M. (2025). Assessment of Unintentional Acute Pesticide Poisoning (UAPP) Amongst Cotton Farmers in Tanzania. Toxics, 13(4), 300. https://doi.org/10.3390/toxics13040300