Knowledge, Attitude, and Practice of Antibiotic Use and Resistance among Poultry Farmers in Nepal
Bibliographic record
Abstract
The abuse and misuse of antibiotics is one of the main drivers of antimicrobial resistance (AMR). Globally, AMR in food-producing animals is a significant public health concern. This study, therefore, assessed the knowledge, attitudes, and practices related to antibiotic usage (AMU) and AMR among poultry farmers in Nepal. We conducted a cross-sectional survey of 605 poultry farmers from six districts of Nepal from May to June 2022 to assess the status of knowledge, attitude, as well as practices toward prudent antibiotic usage (AMU) and AMR. The majority of the participants in our study were from the Chitwan district (31.6%; n = 191/605), aged 30–44 (54.2%; n = 328/605), males (70.4%; n = 426/605), and farmers with a higher secondary (28.76%; n = 174/605) level of education. The tetracyclines (28%, n = 228/828), aminoglycosides (23%, n = 188/828), and fluoroquinolones (15%, n = 126/828) were the most used antibiotics classes among poultry farmers. Although 87.8% (n = 531/605) of poultry farmers used antibiotics, 49.8% (n = 301/605) of them were aware of AMR, and 55.7% (n = 337/605) knew that the misuse of antimicrobials could affect human and environmental health. There were significant differences in the knowledge, attitude, and practices toward prudent AMU and AMR among farmers who reared different birds. The mean knowledge, attitude, and practice score of the respondents were 7.81 ± 3.26, 5.8 ± 2.32, and 7.59 ± 3.38 when measured on a scale of 12, 10, and 15, respectively. Based on a cut-off of 75% of the maximum score, 49.4% (n = 299/605), 62.8% (n = 380/605), and 12.73% (n = 77/605) of the respondents had good knowledge, attitude, and practices toward prudent AMU and AMR, respectively. The multivariable logistic regression analyses revealed that the positive predictors of good knowledge and attitude were male gender, higher level of education, district, and the types of birds (layers). Similarly, those of the male gender (OR: 3.36; 95% CI: 1.38–8.20; p = 0.008) and those that rear layers (OR: 4.63; 95% CI: 1.75–12.25; p = 0.003) were more likely to practice prudent usage of antimicrobials. The findings of this study show poor practice toward prudent antibiotic usage despite good knowledge of AMR. This study provides essential baseline data on the knowledge, attitudes, and practices of poultry farmers in Nepal and offers valuable insights that could help in the design of interventions and policies aimed at addressing illicit AMU and AMR in poultry in Nepal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".